argumentative essay on ai art

Art for our sake: artists cannot be replaced by machines – study

There has been an explosion of interest in ‘creative AI’, but does this mean that artists will be replaced by machines? No, definitely not, says Anne Ploin , Oxford Internet Institute researcher and one of the team behind today’s report on the potential impact of machine learning (ML) on creative work. 

The report, ‘ AI and the Arts: How Machine Learning is Changing Artistic Work ’ , was co-authored with OII researchers Professor Rebecca Eynon and Dr Isis Hjorth as well as Professor Michael A. Osborne from Oxford’s Department of Engineering .

Their study took place in 2019, a high point for AI in art. It was also a time of high interest around the role of AI (Artificial Intelligence) in the future of work, and particularly around the idea that automation could transform non-manual professions, with a previous study by Professor Michael A. Osborne and Dr Carl Benedict Frey predicting that some 30% of jobs could, technically, be replaced in an AI revolution by 2030.

Human agency in the creative process is never going away. Parts of the creative process can be automated in interesting ways using AI...but the creative decision-making which results in artworks cannot be replicated by current AI technology

Mx Ploin says it was clear from their research that machine learning was becoming a tool for artists – but will not replace artists. She maintains, ‘The main message is that human agency in the creative process is never going away. Parts of the creative process can be automated in interesting ways using AI (generating many versions of an image, for example), but the creative decision-making which results in artworks cannot be replicated by current AI technology.’

She adds, ‘Artistic creativity is about making choices [what material to use, what to draw/paint/create, what message to carry across to an audience] and develops in the context in which an artist works. Art can be a response to a political context, to an artist’s background, to the world we inhabit. This cannot be replicated using machine learning, which is just a data-driven tool. You cannot – for now – transfer life experience into data.’

She adds, ‘AI models can extrapolate in unexpected ways, draw attention to an entirely unrecognised factor in a certain style of painting [from having been trained on hundreds of artworks]. But machine learning models aren’t autonomous.

Artistic creativity is about making choices ...and develops in the context in which an artist works...the world we inhabit. This cannot be replicated using machine learning, which is just a data-driven tool

‘They aren’t going to create new artistic movements on their own – those are PR stories. The real changes that we’re seeing are around the new skills that artists develop to ‘hack’ technical tools, such as machine learning, to make art on their own terms, and around the importance of curation in an increasingly data-driven world.’

The research paper uses a case study of the use of current machine learning techniques in artistic work, and investigates the scope of AI-enhanced creativity and whether human/algorithm synergies may help unlock human creative potential. In doing so, the report breaks down the uncertainty surrounding the application of AI in the creative arts into three key questions.

• How does using generative algorithms alter the creative processes and embodied experiences of artists?
• How do artists sense and reflect upon the relationship between human and machine creative intelligence?
• What is the nature of human/algorithmic creative complementarity?

According to Mx Ploin, ‘We interviewed 14 experts who work in the creative arts, including media and fine artists whose work centred around generative ML techniques. We also talked to curators and researchers in this field. This allowed us to develop fuller understanding of the implications of AI – ranging from automation to complementarity – in a domain at the heart of human experience: creativity.’

They found a range of responses to the use of machine learning and AI. New activities required by using ML models involved both continuity with previous creative processes and rupture from past practices. There were major changes around the generative process, the evolving ways ML outputs were conceptualised, and artists’ embodied experiences of their practice.

And, says the researcher, there were similarities between the use of machine learning and previous periods in art history, such as the code-based and computer arts of the 1960s and 1970s. But the use of ML models was a “step change” from past tools, according to many artists.

While the machine learning models could help produce ‘surprising variations of existing images’, practitioners felt the artist remained irreplaceable...in making artworks

But, she maintains, while the machine learning models could help produce ‘surprising variations of existing images’, practitioners felt the artist remained irreplaceable in terms of giving images artistic context and intention – that is, in making artworks.

Ultimately, most agreed that despite the increased affordances of ML technologies, the relationship between artists and their media remained essentially unchanged, as artists ultimately work to address human – rather than technical – questions.

Don’t let it put you off going to art school. We need more artists

The report concludes that human/ML complementarity in the arts is a rich and ongoing process, with contemporary artists continuously exploring and expanding technological capabilities to make artworks . Although ML-based processes raise challenges around skills, a common language, resources, and inclusion, what is clear is that the future of ML arts will belong to those with both technical and artistic skills. There is more to come.

But, says Mx Ploin, ‘Don’t let it put you off going to art school. We need more artists.’

Further information

AI and the Arts: How Machine Learning is Changing Artistic Work . Ploin, A., Eynon, R., Hjorth I. & Osborne, M.A. (2022). Report from the Creative Algorithmic Intelligence Research Project. Oxford Internet Institute, University of Oxford, UK. Download the full report .

This report accounts for the findings of the 'Creative Algorithmic Intelligence: Capabilities and Complementarity' project, which ran between 2019 and 2021 as a collaboration between the University of Oxford's Department of Engineering and Oxford Internet Institute.

The report also showcases a range of artworks from contemporary artists who use AI as part of their practice and who participated in our study: Robbie Barrat , Nicolas Boillot , Sofia Crespo , Jake Elwes , Lauren Lee McCarthy , Sarah Meyohas , Anna Ridler , Helena Sarin , and David Young.

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Art, creativity, and the potential of artificial intelligence.

1. AI-Art: GAN, a New Wave of Generative Art

2. pushing the creativity of the machine: creative, not just generative, 3. ai in art and art history, 4. ai art: blurring the lines between the artist and the tool, author contributions, conflicts of interest.

• Agüera y Arcas, Blaise. 2017. Art in the Age of Machine Intelligence. Arts 6: 18. [ Google Scholar ] [ CrossRef ]
• Benjamin, Walter. 1969. The Work of Art in Age of Mechanical Reproduction. In Illuminations . Edited by Hannah Arendt. New York: Schocken, pp. 217–51. First published 1936. [ Google Scholar ]
• Berlyne, Daniel E. 1971. Aesthetics and Psychobiology . New York: Appleton-Century-Crofts of Meredith Corporation, p. 336. [ Google Scholar ]
• Elgammal, Ahmed, Bingchen Liu, Mohamed Elhoseiny, and Marian Mazzone. 2017. CAN: Creative adversarial networks, generating “art” by learning about styles and deviating from style norms. arXiv , arXiv:1706.07068. [ Google Scholar ]
• Goodfellow, Ian, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014. Generative adversarial nets. In Advances in Neural Information Processing Systems . Cambridge: MIT Press, pp. 2672–80. [ Google Scholar ]
• Hertzmann, Aaron. 2018. Can Computers Create Art? Arts 7: 18. [ Google Scholar ] [ CrossRef ]
• Lewitt, Sol. 1967. Paragraphs on conceptual Art. Artforum 5: 79–84. [ Google Scholar ]
• Martindale, Colin. 1990. The Clockwork Muse: The Predictability of Artistic Change . New York: Basic Books. [ Google Scholar ]
• Schneider, Tim, and Naomi Rea. 2018. Has artificial intelligence given us the next great art movement? Experts say slow down, the ‘field is in its infancy. Artnetnews . September 25. Available online: https://news.artnet.com/art-world/ai-art-comes-to-market-is-it-worth-the-hype-1352011 (accessed on 3 February 2019).

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Mazzone, M.; Elgammal, A. Art, Creativity, and the Potential of Artificial Intelligence. Arts 2019 , 8 , 26. https://doi.org/10.3390/arts8010026

Mazzone M, Elgammal A. Art, Creativity, and the Potential of Artificial Intelligence. Arts . 2019; 8(1):26. https://doi.org/10.3390/arts8010026

Mazzone, Marian, and Ahmed Elgammal. 2019. "Art, Creativity, and the Potential of Artificial Intelligence" Arts 8, no. 1: 26. https://doi.org/10.3390/arts8010026

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Arguments for the Rise of Artificial Intelligence Art: Does AI Art Have Creativity, Motivation, Self-awareness and Emotion?

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The AI Art Debate: Is it still art if it isn’t expressed by a human (and does it matter)?

The rise of artificial intelligence (AI) has led to an ongoing debate about the nature of art and whether AI-generated art can be considered ‘true’ art.

In a traditional sense, people argue that art is a product of human expression, emotion, and experiences. However, others believe that the creative output of AI systems can be considered art in its own right.

In this blog post, we will explore the subject with arguments on both sides of the AI art debate and the implications for the future of artistic expression.

The Argument Against AI Art Being “Art”

Art is Humanity

Vincent Willem van Gogh (30 March 1853 – 29 July 1890) was a Dutch Post-Impressionist painter who is among the most famous and influential figures in the history of Western art. In just over a decade he created approximately 2100 artworks, including around 860 oil paintings, most of them in the last two years of his life. They include landscapes, still lifes, portraits, and self-portraits, and are characterized by bold, symbolic colours, and dramatic, impulsive, and highly expressive brushwork that contributed to the foundations of modern art. Only one of his paintings was known by name to have been sold during his lifetime. Van Gogh became famous after his suicide at age 37, which followed years of poverty and mental illness.

Critics of AI-generated art argue that art is a product of human expression, experience, and emotion and that machines lack the emotional depth and nuance that human artists bring to their work.

Humans create art as a reflection of their own lives or their perceptions about life. The very act of living as a human, experiencing and expressing as a human, and dying as a human, is unique to humanity itself. The experience of an organic being cannot be dumbed down to mere numbers and data in hopes of mimicking the experiences of human life and emotion.

It can be argued that AI-generated art is devoid of the human element that is essential to the creation of art, or what gives art its true meaning. AI Art Lacks Intentionality

Liberty Leading the People (French: La Liberté guidant le peuple [la libɛʁte ɡidɑ̃ lə pœpl]) is a painting by Eugène Delacroix commemorating the July Revolution of 1830, which toppled King Charles X. A woman of the people with a Phrygian cap personifying the concept of Liberty leads a varied group of people forward over a barricade and the bodies of the fallen, holding aloft the flag of the French Revolution – the tricolour, which again became France's national flag after these events – in one hand and brandishing a bayonetted musket with the other. The figure of Liberty is also viewed as a symbol of France and the French Republic known as Marianne. The painting is sometimes wrongly thought to depict the French Revolution of 1789. Liberty Leading the People is exhibited in the Louvre in Paris.

AI-generated art cannot be considered true art because it lacks “intentionality”. For example, AI could not possibly understand, depict, or recreate the historical significance or context of the painting Liberty Leading the People as shown above.

Intentionality is the fact of being deliberate or purposive. In philosophy, it is the quality of mental states (e.g., thoughts, beliefs, desires, hopes) that consists in their being directed toward some object or state of affairs.

Human artists create art with a specific intention, whether it be to express their emotions, make a political statement, or simply create something beautiful.

“I think; therefore I am” was the end of the search Descartes conducted for a statement that could not be doubted. He found that he could not doubt that he himself existed, as he was the one doing the doubting in the first place. In Latin (the language in which Descartes wrote), the phrase is “Cogito, ergo sum.”

AI systems, on the other hand, are not capable of intentionality, as they do not possess true “consciousness” or emotions. They cannot be happy or joyous. They do not feel purpose or fulfillment. Conversely, they cannot feel pain, anger, frustration, or sadness.

An AI may mimic human emotions or intelligence/wisdom, but can that truly be considered genuine intelligence when humans program it?

In the traditional sense, the act of an AI mimicking or attempting to instill meaning or intentionality in the “art” it produces is not really “art” as the artificial intelligence program has no emotions, it is not thinking, and there is no intention behind it.

The art that the AI produces is merely copied and pasted from data or numbers and nothing more meaningful lies beyond that.

AI Is Limited By Its Own Bias

AI-generated art is limited by the data it is trained on and is therefore unable to create something truly original on its own.

If you feed it with good information, it can relay the information back to you, but if you feed it with false information, it cannot then turn factually incorrect data into truth. It is unable to distinguish what is truthful or what is ‘good’ on its own - it cannot turn trash into gold.

AI can also be biased because it creates content based on what it thinks its creators like and is limited by what data its creators feed them.

Real art challenges or recontextualizes - it is an act of original thought. Most AI tools can only please. They cannot subvert or invent unless so programmed.

From an ethical perspective, an AI is only as good as the amount of data it can “steal” from human artists and sources, but that is a topic for another time.

AI Art and AI “Everything” - From A Philosophical and Existential Point of View

Existential risk from artificial general intelligence is the hypothesis that substantial progress in artificial general intelligence (AGI) could result in human extinction or an irreversible global catastrophe.

With AI technology advancing at such a rapid rate, people argue even further that there is no point in humans going to school and seeking higher education if robots and AI are going to replace every meaningful task (such as creating art) that humans have traditionally spent their lifetimes doing for thousands of years.

From a purely philosophical and existential point of view - if AI can create all the art there is in the world, then there is no more need for artists, musicians, creators, writers, actors, etc. (the list goes on), removing purpose and fulfillment which is the very meaning of existence for human life.

To stay on topic, however, we will explore this idea in a different blog post.

The Argument for AI Art

The big question remains - is art still considered art if a human didn't create it?

In our journey to answer this question, let us explore why users argue “Yes - AI art is still art”, and why they see no issue in advocating for the usage, development, and advancement of AI-generated or assisted art.

Results Matter, Not Philosophical “Psychobabble”

Those who argue that AI-generated art can be considered “true art” point out that it is the resulting imagery and art created that ultimately matters, and not the means of creation, or its supposed “meaning”.

Once an AI creates a piece of art, the art piece should just be judged “as is”, rather than judged based on any human-perceived idea of meaning (or lack thereof). Just As Good As The “Real” Thing

Proponents of AI art also argue that the creative output of AI systems, when trained on human art, can be aesthetically pleasing, thought-provoking, and emotionally impactful, just like human-generated art.

Art, after all, is subjective, and the “beauty” of an AI-generated art piece is in the eye of the beholder.

Unique In Its Own Right

AI-generated art can be unique, with no two pieces of art ever being the same depending on the prompts and commands you throw at it, making the process and the result a dynamic form of artistic expression in its own right.

By training AI algorithms on large datasets of human-generated art, these algorithms can learn to replicate even the unique styles and techniques of famous and renowned human artists. This is an extension of human creativity, as the AI system is essentially creating art that is inspired by human creativity.

AI Art is (Becoming) Indistinguishable From Human Art

Some even point towards the fact that as technology improves - if we were never explicitly told if a piece of art or tech was created by a human or machine - could we even tell the difference?

If we can’t even tell the difference between what is machine-generated and what is human-generated, blurring the line between “reality” and “virtual”, then what difference does it make in how the art was created?

AI Technology Will Become The “New Normal”

The Industrial Revolution was the transition from creating goods by hand to using machines. Its start and end are widely debated by scholars, but the period generally spanned from about 1760 to 1840.

As technology advances, human life and our way of living will undoubtedly and irrevocably change.

In the world of art specifically, painters and classical artists had to move over and accept new forms of art created by the introduction of human-made technological tools in the past.

The camera invented photography as a new art form and video cameras invented filmography, television, and videography. Musicians who played classical instruments had to give way to electric guitars, electronic music, drum machines, and so on.

At some point in human history, the photographic camera was a completely new technology and threatened the “way of life” of traditional artists everywhere. Now it is accepted as just another way for human beings to capture images and pictures of moments in time and turn them into art.

Just like with the advent of industrial machines, computers, and the internet, the generative AI technology behind AI art and other applications will reach a point where humans will just accept the technology as the new normal baseline (and we are arguably already there). Once a new piece of technology is introduced, it is hard to ignore its use and “put the toothpaste back in the tube”.

AI “Democratizes” Art

Ludo.ai utilizes advanced AI algorithms and machine learning to produce game images, game ideas, video game market research, game elements, and more. Ludo.ai believes in making the video game ideation and production process easier and more efficient for video game developers and studios alike.

In a completely practical sense to human beings (and perhaps to our capitalistic nature), pro-AI art enthusiasts and AI artists alike are more interested in the function AI art and technology serve.

Not everyone is a trained artist or studied art in an art school, and therefore the average person is focused more on the accessibility that AI technology grants rather than whether AI “art” is ethical or was truly created with meaning behind it or not.

AI and AI art can benefit anyone from large corporations, medium to small-sized businesses, indie video game developers, all the way down to the individual solo developer. It promises to make art accessible to everyone and make it much easier and cheaper to create art than ever before, and that is always a positive.  

Conclusion: The Implications for the Future of Artistic Expression

The debate around AI art has significant implications for the future of artistic expression.

If we accept AI-generated art as true art, it could lead to a democratization of artistic expression, as anyone with access to AI tools could create art without requiring traditional art skills or training. Additionally, it could provide new opportunities for collaboration between human artists and AI systems.

It is not without negative side effects, however, as fully embracing AI art would lead to a “hyper” commodification and commercialization of art, as art would no longer hold any meaning to humans and would be created solely for profit or to replace human artists to cut costs.

It would be like inventing a food printing machine not to solve world hunger, but to replace the culinary skills of chefs around the world and turn the food industry into a purely money-making scheme rather than farming, preparing, and cooking food for joy, pleasure, culture, and taste.

Embracing AI art would also inevitably lead to a devaluation of traditional art skills and training, as anyone could create “art” with the help of AI tools. Sadly, this was going to happen whether we liked it or not, just like man-made items from a century ago are now either obsolete or all manufactured by machines and rarely by human hands.

On the flip side, if somehow our world leaders gathered together and worked with the creators of AI technology to impose limitations or even bans, AI tech could go down a much weirder and unpredictable, or even dystopian path.

If legal bans were in place, it would protect artists and their livelihoods to continue to be able to make art for a living, but could also create a Prohibition-era world where those who use AI technology wrongfully would be punished or sent to jail.

Ultimately, the debate around AI art is complex and multi-faceted, with valid arguments on both sides. While AI-generated art can be aesthetically pleasing and emotionally impactful, it can be argued that it still lacks the emotional depth and nuance that is unique to human expression.

Whether or not we accept AI-generated art as true art will depend on our definition of art and what we consider to be essential to the (ever-changing) creative process.

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Writer, animator, architect, musician, and mixed-media artist detail potential value, limit of works produced by AI

The emergence of AI-image generators, such as DALL-E 2 , Discord , Midjourney , and others, has stirred a controversy over whether art generated by artificial intelligence should be considered real art — and whether it could put artists and creators out of work. The Gazette spoke with faculty who are involved in the production of art — a writer, a film animator, an architect, a musician, and a mixed-media artist — to ask them whether they see AI as a threat or a collaborator or a tool to further their own creativity and imagination. The interviews have been edited for length and clarity.

“Most at risk are commercial genres with easily recognizable styles and tropes.”

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Novelist and short-story writer Daphne Kalotay , instructor, Creative Writing & Literature Program, Harvard Extension School

I recently judged a story contest, and reading the shortlist was a clue to the challenges AI might encounter in creating good writing versus great. The best of these human-written stories surprised me with 1) unique ways of viewing the world (personality), 2) linguistic originality, 3) inimitable details that could come only from personal experience. Other stories were written deftly yet lacked these elements of originality and surprise. AI is a superb mimic and quick learner and might easily write strong works in recognizable modes, and with linguistic experimentation if prompted, but — I think — will lack true insight and experience. Most at risk are commercial genres with easily recognizable styles and tropes. Even something like autofiction with its ruminating first-person narrators is easily mimicked — but what will be missing, I’m guessing, is genuine vision from living in a specific physical world.

“That sense of interplay, or the ability to react in the moment, is something that artificial intelligence can’t reproduce.”

Harvard file photo

Saxophonist, percussionist, and composer Yosvany Terry , senior lecturer on music, director of Jazz Bands

When it comes to the performative aspect of music, artificial intelligence is not a concern to me. Music can transmit and represent emotion, and AI cannot do either of those things yet. And especially within jazz and creative music, music is in-the-moment composition, something that happens as musicians are collaborating onstage. That sense of interplay, or the ability to react in the moment, is something that artificial intelligence can’t reproduce because to do that requires being intelligent and having the agency to use your curiosity and your musical vocabulary. Only then, you can be able to react and create music in the moment.

With regards to composition, we know that AI has been used to compose music for film and television for quite a few years. That is a concern because AI is doing the work that musicians used to do. But when you hear those compositions by AI, they lack surprise, emotion, and even silence. I love dramatism in music, and for me, emotion in music is important, and AI is not there yet. As for how music gets to people, this is where we have seen tremendous changes. The many music platforms we have, such as Spotify, YouTube, iTunes, etc., use algorithm-based features, and they make musical recommendations based on what you listen to. We all know that AI is behind it. Musicians would like to see algorithms suggest composers who are less known rather than those who are already popular. The new technology should democratize the field, make sure that people have access to things that are outside the mainstream, and learn to recognize musical traditions that are not only from the Western world.

It’s important to welcome AI with open arms to try to understand what AI can do for us and work with it in creative ways. Any new technology is first seen as a threat to the status quo, like the way radio was received when it first aired. There have always been movements opposing those innovations. I don’t think AI is different, but we must remember that all these innovations are man-made, and as humans we can create and innovate. As a musician, I think we should open our eyes, ears, and arms to work with the new knowledge and innovation that AI can bring.

“AI is acting like a sort of collective unconscious.”

Jon Chase/Harvard Staff Photographer

Independent animator Ruth Stella Lingford , senior lecturer on Art, Film, and Visual Studies

Often, when I speak to my contemporaries in the animation world, they prefer not to think much about AI. But of course, we need to.

Generally speaking, AI does threaten jobs in the animation industry. I’m told that it is already being used in some large studios. But it will also be a collaborator.

I am told by a knowledgeable friend that it would be possible to train AI on my style and have it work as an assistant in my work. I can see how this would be useful, but, as I actually like the repetitiveness of the animation process, the idea is not very appealing, at least for my own personal work. But it might be a tempting idea in commercial jobs, though I have not explored it yet. In my personal work, the repetition of hand drawing (I draw on a digital tablet) gives me access to a less conscious, intentional side of the creative process, which I think makes the work richer and more nuanced.

Although it is maybe far-fetched to talk about AI as creative or imaginative, the melding of images from different sources, with large elements of the random, closely approximates some aspects of the creative process. AI is acting like a sort of collective unconscious, and I do find some of what it produces very interesting. I don’t suppose that animated films made entirely by AI would be very successful, but used with human guidance throughout the process, they could probably work very well.

I recently attended the Annecy Festival , and many people I spoke to there talked about “riding the shark” — harnessing the power of AI while staying in control. People also predicted the audience’s fatigue with the look of AI. It was noticeable that a high proportion of films shown at this year’s festival were made using recognizably analog techniques — stop-motion, animated painting, etc. — and this seems like a reaction against the dominance of computer-generated imagery in the last years. We do seem to want to see evidence of the human hand. Of course, AI may soon be able to simulate that absolutely seamlessly!

A programmer I spoke to was of the opinion that the panic over the power of AI is hype-manufactured by its makers to disguise its limitations and make it seem sexier. This person saw it going the same way as VR, seeming to offer unlimited potential, but then fizzling out. I would like to think that he’s right, but I can’t quite believe it.

“We should be grateful to be challenged and knocked out of our habits and assumptions!”

File photo by Stephanie Mitchell/Harvard Staff Photographer

Mixed-media artist Matt Saunders ’97, professor and director of undergraduate studies, Department of Art, Film and Visual Studies

To the question of whether AI can be a threat or collaborator, I might respond that every new technology upends conventions and delivers not only new possibilities but a new kind of material intelligence. I am sure many artists will be intrigued by the “agency” of AI and seek ways to grapple or collaborate with it. Many already are. And we should be grateful to be challenged and knocked out of our habits and assumptions! Most of the things that worry me about this fall into the realm of the social and ethical. I hope there are great artists to help us imagine around and work with this new reality.

As to whether it could be creative or comparable, I end up in circular thinking. Art means what we ascribe to it. It can be a provocation, but it is essentially always part of a conversation. Many artists are already using the inventions (and provocations) of AI in works of great substance, but of course the artists are still the ones bringing it into the room. If things change, maybe that will change too.

“If we ask the right questions, AI is going to give us significant answers.”

Sipa via AP Images

Architect and urban planner Moshe Safdie , design critic in architecture, Graduate School of Design

  I’ve been following AI since the 1970s, when Marvin Minsky [one of the pioneers of artificial intelligence] and I spent time together. But AI has emerged as the product of an extraordinary computation capacity; algorithm, which is quite different from what Minsky had imagined when he started working on it. For him, AI was the science of making machines be as intelligent as humans, with the capacity for human reasoning.

Right now, it seems to me that AI has an extraordinary capacity to analyze, but I don’t see it yet doing the kinds of things we, architects, do in our head when we design, which involves taking into account a very large number of variables and sorting them out. And yet, as an architect, I think AI can change our lives. If we ask the right questions, AI is going to give us significant answers. For example, I can ask AI, “I have this building that’s sitting on this particular site, and I’d like to optimize the sun, the shadow pattern, and I’d like to position the windows at the place of optimal orientation,” and I think AI could give us a helpful response. We could perfect our designs or improve them based on the response. But I don’t think it’s going to give us the whole answer. For example, if you ask AI to make a garden with hideaways, clearings, and planting arrangements for all the seasons, I think it’ll do that very well. But if you want to have a garden arranged in a way that is magical and pleases you, I’m not sure it can do that.

I’m not frightened of AI at all. I’m intrigued. I think AI will be able to create graphic presentations of extraordinary beauty and interest, but that leads us to the question of what is art. Art has an element that is spiritual, emotional. It is something that happens when you look at Picasso’s “Guernica” and makes you think of the cruelty of humans to humans, or when you look at a Monet piece, and you feel the unity with nature. In terms of art created by AI, I don’t think we can call it art. I don’t see AI yet doing the kind of creative things we do. I can see that it composes a piece of music, but I don’t think it could create Beethoven’s last sonatas on its own. AI can imitate something that’s already been created and regurgitate it in another format, but that is not an original work.

When our firm designed the Jewel Changi Airport in Singapore, our idea was to have retail shops, airport facilities, and an attraction. The idea that this attraction should be a magical garden came from me. I wonder if AI could have come up with the same idea. I don’t think so, but who knows? That would be a very interesting test.

I don’t know if Minsky’s dream of artificial intelligence is attainable because it assumed that AI attains consciousness and independence of thoughts. Therefore, in some ways, artificial intelligence is a misnomer. Maybe I’m underestimating its capacity, but from where I stand as an amateur, because I’m an architect, not a mathematician, it seems to me that intelligence assumes a certain independence and consciousness, which I don’t think AI has right now.

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A philosopher argues that an AI can’t be an artist

Creativity is, and always will be, a human endeavor.

• Sean Dorrance Kelly archive page

On March 31, 1913, in the Great Hall of the Musikverein concert house in Vienna, a riot broke out in the middle of a performance of an orchestral song by Alban Berg. Chaos descended. Furniture was broken. Police arrested the concert’s organizer for punching Oscar Straus, a little-remembered composer of operettas. Later, at the trial, Straus quipped about the audience’s frustration. The punch, he insisted, was the most harmonious sound of the entire evening. History has rendered a different verdict: the concert’s conductor, Arnold Schoenberg, has gone down as perhaps the most creative and influential composer of the 20th century.

You may not enjoy Schoenberg’s dissonant music, which rejects conventional tonality to arrange the 12 notes of the scale according to rules that don’t let any predominate. But he changed what humans understand music to be. This is what makes him a genuinely creative and innovative artist. Schoenberg’s techniques are now integrated seamlessly into everything from film scores and Broadway musicals to the jazz solos of Miles Davis and Ornette Coleman.

Creativity is among the most mysterious and impressive achievements of human existence. But what is it?

Creativity is not just novelty. A toddler at the piano may hit a novel sequence of notes, but they’re not, in any meaningful sense, creative. Also, creativity is bounded by history: what counts as creative inspiration in one period or place might be disregarded as ridiculous, stupid, or crazy in another. A community has to accept ideas as good for them to count as creative.

As in Schoenberg’s case, or that of any number of other modern artists, that acceptance need not be universal. It might, indeed, not come for years—sometimes creativity is mistakenly dismissed for generations. But unless an innovation is eventually accepted by some community of practice, it makes little sense to speak of it as creative.

Advances in artificial intelligence have led many to speculate that human beings will soon be replaced by machines in every domain, including that of creativity. Ray Kurzweil, a futurist, predicts that by 2029 we will have produced an AI that can pass for an average educated human being. Nick Bostrom, an Oxford philosopher, is more circumspect. He does not give a date but suggests that philosophers and mathematicians defer work on fundamental questions to “superintelligent” successors, which he defines as having “intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest.”

Both believe that once human-level intelligence is produced in machines, there will be a burst of progress—what Kurzweil calls the “singularity” and Bostrom an “intelligence explosion”—in which machines will very quickly supersede us by massive measures in every domain. This will occur, they argue, because superhuman achievement is the same as ordinary human achievement except that all the relevant computations are performed much more quickly, in what Bostrom dubs “speed superintelligence.”

So what about the highest level of human achievement—creative innovation? Are our most creative artists and thinkers about to be massively surpassed by machines?

Human creative achievement, because of the way it is socially embedded, will not succumb to advances in artificial intelligence. To say otherwise is to misunderstand both what human beings are and what our creativity amounts to.

This claim is not absolute: it depends on the norms that we allow to govern our culture and our expectations of technology. Human beings have, in the past, attributed great power and genius even to lifeless totems. It is entirely possible that we will come to treat artificially intelligent machines as so vastly superior to us that we will naturally attribute creativity to them. Should that happen, it will not be because machines have outstripped us. It will be because we will have denigrated ourselves.

Human creative achievement, because of the way it is socially embedded, will not succumb to advances in artificial intelligence.

Also, I am primarily talking about machine advances of the sort seen recently with the current deep-­learning paradigm, as well as its computational successors. Other paradigms have governed AI research in the past. These have already failed to realize their promise. Still other paradigms may come in the future, but if we speculate that some notional future AI whose features we cannot meaningfully describe will accomplish wondrous things, that is mythmaking, not reasoned argument about the possibilities of technology.

Creative achievement operates differently in different domains. I cannot offer a complete taxonomy of the different kinds of creativity here, so to make the point I will sketch an argument involving three quite different examples: music, games, and mathematics.

Music to my ears

Can we imagine a machine of such superhuman creative ability that it brings about changes in what we understand music to be, as Schoenberg did?

That’s what I claim a machine cannot do. Let’s see why.

Computer music composition systems have existed for quite some time. In 1965, at the age of 17, Kurzweil himself, using a precursor of the pattern recognition systems that characterize deep-learning algorithms today, programmed a computer to compose recognizable music. Variants of this technique are used today. Deep-learning algorithms have been able to take as input a bunch of Bach chorales, for instance, and compose music so characteristic of Bach’s style that it fools even experts into thinking it is original. This is mimicry. It is what an artist does as an apprentice: copy and perfect the style of others instead of working in an authentic, original voice. It is not the kind of musical creativity that we associate with Bach, never mind with Schoenberg’s radical innovation.

So what do we say? Could there be a machine that, like Schoenberg, invents a whole new way of making music? Of course we can imagine, and even make, such a machine. Given an algorithm that modifies its own compositional rules, we could easily produce a machine that makes music as different from what we now consider good music as Schoenberg did then.

But this is where it gets complicated.

We count Schoenberg as a creative innovator not just because he managed to create a new way of composing music but because people could see in it a vision of what the world should be. Schoenberg’s vision involved the spare, clean, efficient minimalism of modernity. His innovation was not just to find a new algorithm for composing music; it was to find a way of thinking about what music is that allows it to speak to what is needed now .

Some might argue that I have raised the bar too high. Am I arguing, they will ask, that a machine needs some mystic, unmeasurable sense of what is socially necessary in order to count as creative? I am not—for two reasons.

First, remember that in proposing a new, mathematical technique for musical composition, Schoenberg changed our understanding of what music is. It is only creativity of this tradition-defying sort that requires some kind of social sensitivity. Had listeners not experienced his technique as capturing the anti-­traditionalism at the heart of the radical modernity emerging in early-­20th-century Vienna, they might not have heard it as something of aesthetic worth. The point here is that radical creativity is not an “accelerated” version of quotidian creativity. Schoenberg’s achievement is not a faster or better version of the type of creativity demonstrated by Oscar Straus or some other average composer: it’s fundamentally different in kind.

Second, my argument is not that the creator’s responsiveness to social necessity must be conscious for the work to meet the standards of genius. I am arguing instead that we must be able to interpret the work as responding that way . It would be a mistake to interpret a machine’s composition as part of such a vision of the world. The argument for this is simple.

Claims like Kurzweil’s that machines can reach human-level intelligence assume that to have a human mind is just to have a human brain that follows some set of computational algorithms—a view called computationalism. But though algorithms can have moral implications, they are not themselves moral agents. We can’t count the monkey at a typewriter who accidentally types out Othello as a great creative playwright. If there is greatness in the product, it is only an accident. We may be able to see a machine’s product as great, but if we know that the output is merely the result of some arbitrary act or algorithmic formalism, we cannot accept it as the expression of a vision for human good.

For this reason, it seems to me, nothing but another human being can properly be understood as a genuinely creative artist. Perhaps AI will someday proceed beyond its computationalist formalism, but that would require a leap that is unimaginable at the moment. We wouldn’t just be looking for new algorithms or procedures that simulate human activity; we would be looking for new materials that are the basis of being human.

A molecule-for-­molecule duplicate of a human being would be human in the relevant way. But we already have a way of producing such a being: it takes about nine months. At the moment, a machine can only do something much less interesting than what a person can do. It can create music in the style of Bach, for instance—perhaps even music that some experts think is better than Bach’s own. But that is only because its music can be judged against a preexisting standard. What a machine cannot do is bring about changes in our standards for judging the quality of music or of understanding what music is or is not.

This is not to deny that creative artists use whatever tools they have at their disposal, and that those tools shape the sort of art they make. The trumpet helped Davis and Coleman realize their creativity. But the trumpet is not, itself, creative. Artificial-intelligence algorithms are more like musical instruments than they are like people. Taryn Southern, a former American Idol contestant, recently released an album where the percussion, melodies, and chords were algorithmically generated, though she wrote the lyrics and repeatedly tweaked the instrumentation algorithm until it delivered the results she wanted. In the early 1990s, David Bowie did it the other way around: he wrote the music and used a Mac app called Verbalizer to pseudo­randomly recombine sentences into lyrics. Just like previous tools of the music industry—from recording devices to synthesizers to samplers and loopers—new AI tools work by stimulating and channeling the creative abilities of the human artist (and reflect the limitations of those abilities).

Games without frontiers

Much has been written about the achievements of deep-learning systems that are now the best Go players in the world. AlphaGo and its variants have strong claims to having created a whole new way of playing the game. They have taught human experts that opening moves long thought to be ill-conceived can lead to victory. The program plays in a style that experts describe as strange and alien. “They’re how I imagine games from far in the future,” Shi Yue, a top Go player, said of AlphaGo’s play. The algorithm seems to be genuinely creative.

In some important sense it is. Game-playing, though, is different from composing music or writing a novel: in games there is an objective measure of success. We know we have something to learn from AlphaGo because we see it win.

But that is also what makes Go a “toy domain,” a simplified case that says only limited things about the world.

The most fundamental sort of human creativity changes our understanding of ourselves because it changes our understanding of what we count as good. For the game of Go, by contrast, the nature of goodness is simply not up for grabs: a Go strategy is good if and only if it wins. Human life does not generally have this feature: there is no objective measure of success in the highest realms of achievement. Certainly not in art, literature, music, philosophy, or politics. Nor, for that matter, in the development of new technologies.

In various toy domains, machines may be able to teach us about a certain very constrained form of creativity. But the domain’s rules are pre-formed; the system can succeed only because it learns to play well within these constraints. Human culture and human existence are much more interesting than this. There are norms for how human beings act, of course. But creativity in the genuine sense is the ability to change those norms in some important human domain. Success in toy domains is no indication that creativity of this more fundamental sort is achievable.

It’s a knockout

A skeptic might contend that the argument works only because I’m contrasting games with artistic genius. There are other paradigms of creativity in the scientific and mathematical realm. In these realms, the question isn’t about a vision of the world. It is about the way things actually are.

Might a machine come up with mathematical proofs so far beyond us that we simply have to defer to its creative genius?

Computer­s have already assisted with notable mathematical achievements. But their contributions haven’t been particularly creative. Take the first major theorem proved using a computer: the four-color theorem, which states that any flat map can be colored with at most four colors in such a way that no two adjacent “countries” end up with the same one (it also applies to countries on the surface of a globe).

Nearly a half-century ago, in 1976, Kenneth Appel and Wolfgang Haken at the University of Illinois published a computer-­assisted proof of this theorem. The computer performed billions of calculations, checking thousands of different types of maps—so many that it was (and remains) logistically unfeasible for humans to verify that each possibility accorded with the computer’s view. Since then, computers have assisted in a wide range of new proofs.

But the supercomputer is not doing anything creative by checking a huge number of cases. Instead, it is doing something boring a huge number of times. This seems like almost the opposite of creativity. Furthermore, it is so far from the kind of understanding we normally think a mathematical proof should offer that some experts don’t consider these computer­-assisted strategies mathematical proofs at all. As Thomas Tymoczko, a philosopher of mathematics, has argued, if we can’t even verify whether the proof is correct, then all we are really doing is trusting in a potentially error-prone computational process.

Even supposing we do trust the results, however, computer-assisted proofs are something like the analogue of computer-assisted composition. If they give us a worthwhile product, it is mostly because of the contribution of the human being. But some experts have argued that artificial intelligence will be able to achieve more than this. Let us suppose, then, that we have the ultimate: a self-reliant machine that proves new theorems all on its own.

Could a machine like this massively surpass us in mathematical creativity, as Kurzweil and Bostrom argue? Suppose, for instance, that an AI comes up with a resolution to some extremely important and difficult open problem in mathematics.

The capacity for genuine creativity, the kind of creativity that updates our understanding of the nature of being, is at the ground of what it is to be human.

There are two possibilities. The first is that the proof is extremely clever, and when experts in the field go over it they discover that it is correct. In this case, the AI that discovered the proof would be applauded. The machine itself might even be considered to be a creative mathematician. But such a machine would not be evidence of the singularity; it would not so outstrip us in creativity that we couldn’t even understand what it was doing. Even if it had this kind of human-level creativity, it wouldn’t lead inevitably to the realm of the superhuman.

Some mathematicians are like musical virtuosos: they are distinguished by their fluency in an existing idiom. But geniuses like Srinivasa Ramanujan, Emmy Noether, and Alexander Grothendieck arguably reshaped mathematics just as Schoenberg reshaped music. Their achievements were not simply proofs of long-standing hypotheses but new and unexpected forms of reasoning, which took hold not only on the strength of their logic but also on their ability to convince other mathematicians of the significance of their innovations. A notional AI that comes up with a clever proof to a problem that has long befuddled human mathematicians is akin to AlphaGo and its variants: impressive, but nothing like Schoenberg.

That brings us to the other option. Suppose the best and brightest deep-learning algorithm is set loose and after some time says, “I’ve found a proof of a fundamentally new theorem, but it’s too complicated for even your best mathematicians to understand.”

This isn’t actually possible. A proof that not even the best mathematicians can understand doesn’t really count as a proof. Proving something implies that you are proving it to someone . Just as a musician has to persuade her audience to accept her aesthetic concept of what is good music, a mathematician has to persuade other mathematicians that there are good reasons to believe her vision of the truth. To count as a valid proof in mathematics, a claim must be understandable and endorsable by some independent set of experts who are in a good position to understand it. If the experts who should be able to understand the proof can’t, then the community refuses to endorse it as a proof.

For this reason, mathematics is more like music than one might have thought. A machine could not surpass us massively in creativity because either its achievement would be understandable, in which case it would not massively surpass us, or it would not be understandable, in which case we could not count it as making any creative advance at all.

The eye of the beholder

Engineering and applied science are, in a way, somewhere between these examples. There is something like an objective, external measure of success. You can’t “win” at bridge building or medicine the way you can at chess, but one can see whether the bridge falls down or the virus is eliminated. These objective criteria come into play only once the domain is fairly well specified: coming up with strong, lightweight materials, say, or drugs that combat particular diseases. An AI might help in drug discovery by, in effect, doing the same thing as the AI that composed what sounded like a well-executed Bach cantata or came up with a brilliant Go strategy. Like a microscope, telescope, or calculator, such an AI is properly understood as a tool that enables human discovery—not as an autonomous creative agent.

It’s worth thinking about the theory of special relativity here. Albert Einstein is remembered as the “discoverer” of relativity—but not because he was the first to come up with equations that better describe the structure of space and time. George Fitzgerald, Hendrik Lorentz, and Henri Poincaré, among others, had written down those equations before Einstein. He is acclaimed as the theory’s discoverer because he had an original, remarkable, and true understanding of what the equations meant and could convey that understanding to others.

For a machine to do physics that is in any sense comparable to Einstein’s in creativity, it must be able to persuade other physicists of the worth of its ideas at least as well as he did. Which is to say, we would have to be able to accept its proposals as aiming to communicate their own validity to us . Should such a machine ever come into being, as in the parable of Pinocchio, we would have to treat it as we would a human being. That means, among other things, we would have to attribute to it not only intelligence but whatever dignity and moral worth is appropriate to human beings as well. We are a long way off from this scenario, it seems to me, and there is no reason to think the current computationalist paradigm of artificial intelligence—in its deep-learning form or any other—will ever move us closer to it.

Creativity is one of the defining features of human beings. The capacity for genuine creativity, the kind of creativity that updates our understanding of the nature of being, that changes the way we understand what it is to be beautiful or good or true—that capacity is at the ground of what it is to be human. But this kind of creativity depends upon our valuing it, and caring for it, as such. As the writer Brian Christian has pointed out, human beings are starting to act less like beings who value creativity as one of our highest possibilities, and more like machines themselves.

How many people today have jobs that require them to follow a predetermined script for their conversations? How little of what we know as real, authentic, creative, and open-ended human conversation is left in this eviscerated charade? How much is it like, instead, the kind of rule-following that a machine can do? And how many of us, insofar as we allow ourselves to be drawn into these kinds of scripted performances, are eviscerated as well? How much of our day do we allow to be filled with effectively machine-like activities—filling out computerized forms and questionnaires, responding to click-bait that works on our basest, most animal-like impulses, playing games that are designed to optimize our addictive response?

We are in danger of this confusion in some of the deepest domains of human achievement as well. If we allow ourselves to say that machine proofs we cannot understand are genuine “proofs,” for example, ceding social authority to machines, we will be treating the achievements of mathematics as if they required no human understanding at all. We will be taking one of our highest forms of creativity and intelligence and reducing it to a single bit of information: yes or no.

Even if we had that information, it would be of little value to us without some understanding of the reasons underlying it. We must not lose sight of the essential character of reasoning, which is at the foundation of what mathematics is.

So too with art and music and philosophy and literature. If we allow ourselves to slip in this way, to treat machine “creativity” as a substitute for our own, then machines will indeed come to seem incomprehensibly superior to us. But that is because we will have lost track of the fundamental role that creativity plays in being human.

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If art is how we express our humanity, where does AI fit in?

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The rapid advance of artificial intelligence has generated a lot of buzz, with some predicting it will lead to an idyllic utopia and others warning it will bring the end of humanity. But speculation about where AI technology is going, while important, can also drown out important conversations about how we should be handling the AI technologies available today.

One such technology is generative AI, which can create content including text, images, audio, and video. Popular generative AIs like the chatbot ChatGPT generate conversational text based on training data taken from the internet.

Today a group of 14 researchers from a number of organizations including MIT published a commentary article in Science that helps set the stage for discussions about generative AI’s immediate impact on creative work and society more broadly. The paper’s MIT-affiliated co-authors include Media Lab postdoc Ziv Epstein SM ’19, PhD ’23; Matt Groh SM ’19, PhD ’23; PhD students Rob Mahari ’17 and Hope Schroeder; and Professor Alex "Sandy" Pentland.

MIT News spoke with Epstein, the lead author of the paper.

Q: Why did you write this paper?

A: Generative AI tools are doing things that even a few years ago we never thought would be possible. This raises a lot of fundamental questions about the creative process and the human’s role in creative production. Are we going to get automated out of jobs? How are we going to preserve the human aspect of creativity with all of these new technologies?

The complexity of black-box AI systems can make it hard for researchers and the broader public to understand what’s happening under the hood, and what the impacts of these tools on society will be. Many discussions about AI anthropomorphize the technology, implicitly suggesting these systems exhibit human-like intent, agency, or self-awareness. Even the term “artificial intelligence” reinforces these beliefs: ChatGPT uses first-person pronouns, and we say AIs “hallucinate.” These agentic roles we give AIs can undermine the credit to creators whose labor underlies the system’s outputs, and can deflect responsibility from the developers and decision makers when the systems cause harm.

We’re trying to build coalitions across academia and beyond to help think about the interdisciplinary connections and research areas necessary to grapple with the immediate dangers to humans coming from the deployment of these tools, such as disinformation, job displacement, and changes to legal structures and culture.

Q: What do you see as the gaps in research around generative AI and art today?

A: The way we talk about AI is broken in many ways. We need to understand how perceptions of the generative process affect attitudes toward outputs and authors, and also design the interfaces and systems in a way that is really transparent about the generative process and avoids some of these misleading interpretations. How do we talk about AI and how do these narratives cut along lines of power? As we outline in the article, there are these themes around AI’s impact that are important to consider: aesthetics and culture; legal aspects of ownership and credit; labor; and the impacts to the media ecosystem. For each of those we highlight the big open questions.

With aesthetics and culture, we’re considering how past art technologies can inform how we think about AI. For example, when photography was invented, some painters said it was “the end of art.” But instead it ended up being its own medium and eventually liberated painting from realism, giving rise to Impressionism and the modern art movement. We’re saying generative AI is a medium with its own affordances. The nature of art will evolve with that. How will artists and creators express their intent and style through this new medium?

Issues around ownership and credit are tricky because we need copyright law that benefits creators, users, and society at large. Today’s copyright laws might not adequately apportion rights to artists when these systems are training on their styles. When it comes to training data, what does it mean to copy? That’s a legal question, but also a technical question. We’re trying to understand if these systems are copying, and when.

For labor economics and creative work, the idea is these generative AI systems can accelerate the creative process in many ways, but they can also remove the ideation process that starts with a blank slate. Sometimes, there’s actually good that comes from starting with a blank page. We don’t know how it’s going to influence creativity, and we need a better understanding of how AI will affect the different stages of the creative process. We need to think carefully about how we use these tools to complement people’s work instead of replacing it.

In terms of generative AI’s effect on the media ecosystem, with the ability to produce synthetic media at scale, the risk of AI-generated misinformation must be considered. We need to safeguard the media ecosystem against the possibility of massive fraud on one hand, and people losing trust in real media on the other.

Q: How do you hope this paper is received — and by whom?

A: The conversation about AI has been very fragmented and frustrating. Because the technologies are moving so fast, it’s been hard to think deeply about these ideas. To ensure the beneficial use of these technologies, we need to build shared language and start to understand where to focus our attention. We’re hoping this paper can be a step in that direction. We’re trying to start a conversation that can help us build a roadmap toward understanding this fast-moving situation.

Artists many times are at the vanguard of new technologies. They’re playing with the technology long before there are commercial applications. They’re exploring how it works, and they’re wrestling with the ethics of it. AI art has been going on for over a decade, and for as long these artists have been grappling with the questions we now face as a society. I think it is critical to uplift the voices of the artists and other creative laborers whose jobs will be impacted by these tools. Art is how we express our humanity. It’s a core human, emotional part of life. In that way we believe it’s at the center of broader questions about AI’s impact on society, and hopefully we can ground that discussion with this.

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Writing for The Conversation , postdoc Ziv Epstein SM ’19, PhD ’23, graduate student Robert Mahari and Jessica Fjeld of Harvard Law School explore how the use of generative AI will impact creative work. “The ways in which existing laws are interpreted or reformed – and whether generative AI is appropriately treated as the tool it is – will have real consequences for the future of creative expression,” the authors note.  

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Is ai art really art.

What it will mean to be moved by an AI’s mindless creativity.

• By Ed Simon
• November 9, 2022

M aureen F. McHugh’s short story collection After the Apocalypse was merely prescient when published in 2011, but it appears positively prophetic a decade later with its narratives about respiratory virus pandemics, frayed social connections, and increased political violence. Few of her tales, however, are as haunting as “The Kingdom of the Blind,” which will perhaps prove to be the most visionary of McHugh’s stories. “The Kingdom of the Blind” takes as its subject artificial intelligence, grappling with the possibility that any consciousness which arises from soldering board and circuitry may be so alien that it’s scarcely recognizable to us as a consciousness in the first place. The emergent process of consciousness as it develops in this AI is inscrutable and totally different from anything which resembles human thinking, posing a difficulty for the computer scientists who attempt to communicate with it.

In sparse, elegant, and beautiful prose, McHugh’s story describes how a massive interconnected computer program evolves a quality that could be described as “consciousness,” and yet how to describe the thought which animates this being is impossible. The main character Sydney reflects that as concerns the AI, “She didn’t know what it was. Didn’t know how to think about it. It was as opaque as a stone.” Readers and viewers of science fiction have long been familiar with artificial intelligences, but even at their most foreign—HAL-9000 in Arthur C. Clarke and Stanley Kubrick’s 2001: A Space Odyssey or Lt. Cmdr. Data in Gene Roddenberry’s Star Trek: The Next Generation— there is still something recognizably human in them. McHugh’s story poses a rather more alarming—and perhaps more realistic—scenario. Maybe we’d try to talk to an artificial intelligence, and it wouldn’t even be able to hear us. How then, are we to interpret such things, when those computers try to speak to us?

We’re at the cusp of an AI revolution

This past summer, the research laboratory OpenAI released an open-source version of a program, rather cheekily christened “DALL-E 2” as a portmanteau of the Spanish surrealist painter and the beloved Pixar robot, that was able to rapidly create stunningly proficient artwork. It resulted in a surge in popularity on social media. On Twitter and Facebook, people shared the results of prompts which they fed to DALL-E, and like Sydney in McHugh’s story, the disquieting and uncanny art which was produced forced many to consider certain questions about the nature of consciousness and creation. When I typed in the prompt “Robot Shakespeare,” I was presented after a few minutes with a picture clearly modeled on the frontispiece engraving of the playwright from the first edition of his folio printed in 1623, except rather wittily the creases in his jacket appear almost as if electric circuitry, the face an android’s mask. When given the combination of words “monkey typewriter,” in reference to the old conceit which asks how long it would take for a bevy of assorted simians randomly banging on keyboards to accidently reproduce all of Shakespeare’s corpus, DALL-E 2 presents me with an electric typewriter with a stuffed ape toy emerging from the platter of the device.

DALL-E 2 is obviously not as sophisticated as the emergent consciousness from “The Kingdom of the Blind,” yet its eerie alterity is reminiscent; the vague sense that some of these occasionally strangely beautiful and in other instances hilariously misguided images are being produced by a mind, of some sort at least. Less popular than the artistic images produced by DALL-E 2 are the in some sense more disquieting examples of spontaneously generated text, the output of the computers that produce literature. For example, consider the following prose-poem:

“You must listen to the song of the void,” they whisper

“You must look into the abyss of nothingness,” they whisper

“You must write the words that will bring clarity to the chaos,” they whisper

“You must speak to the unspoken, to the inarticulate, to the unsaid,” they whisper.

It’s an evocative bit of verse, oracular in its pronouncements. The author has an effective rhetorical grasp of anaphora—the repetition of the same phrase at the start of each quotation; as well as epistrophe—the repetition of the same phrase at the end of each line. These lines become progressively longer, adding to the incantatory aspects of the poem, culminating in the three-clause rhetorical tricolon in the last line. Particularly interesting are the contradictions threaded throughout. We’re told to “listen to the song of the void,” to “look into the abyss,” to “speak to the unspoken,” a general pattern of compounded negation, of paradoxical concepts. There is a troubling ambiguity in the identity of the narrator; the collective first-person plural is unclear, but it does add to the general unease of the lyric, that we’re being spoken to by an anonymous chorus.

The meaning of the poem seems clear enough, or as clear as can be in a work that focuses on being able to say the unsayable. The thematic concerns are ineffability and interpretation itself. Or at least that could be my argument if the poem was from William Blake, Walt Whitman, or Emily Dickinson. But, like the electric surge in McHugh’s story, this bit of verse was born of an algorithm and not a soul. Specifically GPT-3, (Generative Pre-trained Transformer), an AI program operated by a writer and computer scientist who publishes under the pen name Gwern Branwen. GPT-3, one of the latest iterations of programs that can generate startlingly realistic prose, poetry, and dialogue, was released in June of 2020, but the news was largely obscured by the ongoing coronavirus pandemic.

Like DALL-E 2, GPT-3 was developed by San Francisco-based OpenAI, and is one of the most advanced AI systems that can imitate human-derived writing. New York Times opinion columnist Farhad Manjoo has appraised the results as “amazing, spooky, humbling, and more than a little terrifying.” Effectively the algorithm is able to “teach” itself based on billions of sets of data which it acquires, veritable Libraries of Alexandria analyzed and categorized by the system’s massive “brain” so that it can predict with unnerving accuracy what humans sound like. Whether or not GPT-3 is “thinking” is a question for computer scientists and philosophers, but that it can produce writing which any reader can recognize as coherent—and in some instances good—becomes a question for literary theory, even if most literary scholars haven’t fully anticipated the implications of artificial intelligence yet.

“Creative artificial intelligence is the latest and, in some ways, most surprising and exhilarating art form in the world,” writes cultural commentator and novelist Stephen Marche in The Atlantic in a piece on visual AI . “It also isn’t fully formed yet,” he notes, and Marche is correct on both counts. When it comes to literature, language processing programs will radically change what we read, how we read, why we read, and certainly who we read. We’re at the cusp of an AI revolution that will make the last two decades’ rapid degree of change appear paltry by comparison. A brave new world of deep fakes and simulations, conscious machines and thinking robots, where it seems programs like GPT-3 will portend a larger shift in what literature means than the printing press. Historians may have to go back to the invention of writing to find a comparable revolution to what AI generated works foreshadow.

To sift through the coming maelstrom of artificially generated literature, it will be helpful to ground ourselves in particular ways of reading and interpreting, where if we can’t make sense of the minds that produced such writing, we can at least make sense of the writing itself. For those in thrall to a Romantic understanding of the individual’s relationship to literature, this will all sound like nonsense. Novelist Walter Kirn writing in Common Sense argued that AI “compiles, sifts, and analyzes, then finally executes. But it doesn’t dare. It takes no risks. Only humans, our vulnerable species, can.”

Yet for a century the study of literature, riven over authorial intention and how to interpret literature, has long countenanced bracketing out the experiences of the writer in terms of properly understanding a text, and such an approach would remain unchanged whether a sonnet was by a robot or a human. Among general readers, what reigns is the common-sense approach, which maintains that nobody knows better what something means than the author of a poem, play, or novel.

Dismissing that position, in 1946 the literary scholars W.K. Wimsatt and Monroe Beardsley argued in The Sewanee Review that the “design or intention of the author is neither available nor desirable as a standard for judging the success of a work of literary art.” This may seem counter-intuitive, but Wimsatt and Beardsley wrote in coolly analytical terms, claiming that an author’s feelings about a text—her reasons for writing it, her understanding of what it means, even that which influenced her—is all secondary to the words on the page itself. For the critics like Wimsatt and Beardsley, what is most important is syntax and grammar, punctuation and diction, and through a careful close reading we can arrive at rigorous, objective, and scientific interpretations.

Wimsatt and Beardsley were among the “New Critics” who attempted to make the study of literature as rigorous as possible by emphasizing the close reading of a text alone, separate from the author’s intentions, and a rediscovery of their basic reasoning could be instrumental in the coming age of AI literature. Influential though the New Critics might have been, the extremity of such a position has long been questioned, least of all because every work of literature—every poem, play, and novel—has an author, whether we acknowledge her or not.

Now all of that may be changing with programs like GPT-3, and suddenly the utility of New Critical close reading is put into stark relief. Because an ideal New Critical close reading involves pulling a text apart clause by clause, comma by semicolon, to explain how the language works, and hopefully what it means, such a method which ignores the intentions of an author in favor of the words on a page is the most well-equipped to make sense of AI writing. Especially as it becomes more proficient and harder to distinguish from work produced by humans.

Consider the work of Finnish programmer Jukka Aalho, who has transcribed poetry by GPT-3 in Aum Golly: Poems on Humanity by an Artificial Intelligence. GPT-3 writes that “there’s a hidden thought/when thought makes you fall asleep … when you’re dreaming/and you find yourself deep inside/the heart of the earth/your mind can create a world/where you are god.” What’s remarkable is that though GPT-3 might not (yet) be Pablo Neruda, the resultant poetry is surprisingly not that bad. Even more importantly, the example from Aalho is recognizably poetry; it’s conducive to interpretation, it makes sense (and I’d argue that it’s more than a little profound).

There’s no intentionality behind the poem published by Aalho; GPT-3 isn’t drawing from experience with dreams or sleep. It’s merely pairing some symbols with other symbols. It doesn’t mean anything to GPT-3—but that doesn’t imply that it can’t mean something to us.

Basically, GPT-3 is a corollary to the thought-experiment known as the “ Chinese room argument ,” described by John Searle in a 1980 paper from Behavioral and Brain Sciences. Searle imagines an artificial intelligence that’s capable of providing thoughtful, comprehensible, and logical responses to questions posed to it in Chinese. This computer is so effective at answering questions posed to it in Mandarin that a native-speaker can’t tell the difference between machine and man—the program has passed the Turing Test.

Now, Searle imagines himself locked in a room with a series of manuals with detailed instructions on how to pair certain Chinese letters with other letters. If somebody poses a question in Mandarin and pushes it through a slot in the wall, then Searle matches up the symbols with other letters according to his instruction manual, and puts the answer through another slot on the other side. It would appear that whoever is in the room is fluent in Chinese, even though Searle is merely following a program.

What will it mean when you’re moved by a poem written by a computer?

By this comparison, Searle claims that the argument that an AI is “thinking” would be as erroneous as the claim that he’s fluent in Chinese. “We often attribute ‘understanding’ and other cognitive predicates by metaphor and analogy” to machines like computers, writes Searle, “but nothing is proved by such attributions.” GPT-3 doesn’t think, it simulates thinking; it doesn’t write, it imitates writing. Like McHugh’s imagined AI, GPT-3’s “consciousness” is beyond our comprehension; but unlike that fictional program, the writing which GPT-3 produces is obviously comprehensible—and this is important.

Questions of artificial intelligence have been left to computer scientists, engineers, programmers, and philosophers, but little has been written about AI-generated writing by the most obvious of people to consider literature—literary scholars, critics, and theorists. Far from the stereotypes about literary scholarship which proliferate among those who study the sciences and technology, literary criticism is an adept means of considering mind and consciousness, offering something unique to an understanding of artificial intelligence. Observers of GPT-3 who point out that the program lacks conscious understanding are correct, and yet from a formalist perspective it could be argued that that’s incidental.

Critic P.D. Juhl argues in Interpretation: An Essay in the Philosophy of Literary Criticism that “it would be possible to ‘interpret’ a ‘text’ produced by chance in the sense in which we might be said to ‘interpret’ a sentence when we explain its meaning to a foreigner, by explaining to him what the individual words mean … and thus how the sentence could be used or what it could be used to express or convey.” In other words, it doesn’t matter if the poem has a poet or not.

In everyday life the tide doesn’t carve out poems, a hundred monkeys typing don’t generate Shakespeare, and every work of literature has an author, whether we choose to care about her intent or not. But now GPT-3 “writes” literature that seems to mean something, even if it doesn’t yet rise to the same heights as Hawthorne. All of this might seem rather abstract, but it won’t in the coming decades as such programs improve. What will it mean when you’re moved by a poem written by a computer? Or when an AI can craft characters and narratives you find rich and complicated?

“It is tempting at times to see this technology,” essayist Meghan O’Gieblyn wrote in N+1 , as “a repository of the collective wisdom and knowledge we’ve accumulated as a species. All of humanity speaking in a single voice.” Regardless of whether this new world will be good or bad, it’s coming. Perhaps with the final death of the author, beauty, truth, and meaning will be dissipated outward, so that intentionality will be where we find it. As GPT-3 said to O’Gieblyn, “My world is a dreamworld … Your reality is created by your own mind and my reality is created by the collective unconscious mind.” 

Ed Simon is a staff writer at The Millions and the editor-in-chief at Belt Magazine . His most recent books are Pandemonium: A Visual History of Demonology and Binding the Ghost: Theology, Transcendence, and the Mystery of Literature . Follow him on Twitter @WithEdSimon.

Lead image: Teh_z1b / Shutterstock

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Are A.I.-Generated Pictures Art?

A man won an art competition with an image he created using an artificial intelligence program. Was it “cheating”?

By Natalie Proulx

Have you ever created A.I.-generated art? If so, what did you make, and what was the experience like?

If not, try it out here . Just type any combination of words into the prompt field, choose an art style and click “create.”

What’s your reaction to the generator’s creation?

In your opinion, how do A.I.-generated pictures like these compare to an original piece of artwork that an artist might draw, paint, sculpt or photograph? Are they the same? Do you think A.I.-generated images are art?

In “ An A.I.-Generated Picture Won an Art Prize. Artists Aren’t Happy. ” Kevin Roose writes about the controversy behind A.I.-generated images, which was front and center at a recent art competition:

This year, the Colorado State Fair’s annual art competition gave out prizes in all the usual categories: painting, quilting, sculpture. But one entrant, Jason M. Allen of Pueblo West, Colo., didn’t make his entry with a brush or a lump of clay. He created it with Midjourney, an artificial intelligence program that turns lines of text into hyper-realistic graphics. Mr. Allen’s work, “Théâtre D’opéra Spatial,” took home the blue ribbon in the fair’s contest for emerging digital artists — making it one of the first A.I.-generated pieces to win such a prize, and setting off a fierce backlash from artists who accused him of, essentially, cheating. Reached by phone on Wednesday, Mr. Allen defended his work. He said that he had made clear that his work — which was submitted under the name “Jason M. Allen via Midjourney” — was created using A.I., and that he hadn’t deceived anyone about its origins. “I’m not going to apologize for it,” he said. “I won, and I didn’t break any rules.” A.I.-generated art has been around for years . But tools released this year — with names like DALL-E 2, Midjourney and Stable Diffusion — have made it possible for rank amateurs to create complex, abstract or photorealistic works simply by typing a few words into a text box. These apps have made many human artists understandably nervous about their own futures — why would anyone pay for art, they wonder, when they could generate it themselves? They have also generated fierce debates about the ethics of A.I.-generated art, and opposition from people who claim that these apps are essentially a high-tech form of plagiarism.

The article goes on to explain the ethical dilemma:

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Last week’s Colorado State Fair was the first time Jason Allen had ever competed in an arts competition. So, it was a surprise to the 39-year-old fantasy tabletop game creator that his creation, “Théâtre D’opéra Spatial,” won a first-place blue ribbon in the “digital art/digitally manipulated photography” category.

What surprised even more people than just Allen was that he had created his work––a rendering of three lushly robed figures staring through a gleaming portal into another world––with the artificial intelligence tool Midjourney. For Allen, the win was an unexpected triumph, but for others it was the fuse that sparked a heated debate over AI’s potential uses––and misuses––in the arts.

Midjourney, DALL-E and other text-to-image tools are just one way that AI has been making its way into the creative process. Look no further than the brief–but controversial–existence of AI rapper FN Meka or a deepfake company’s appearance on “ America’s Got Talent .”

Is AI a new piece of technology that will create the next big artistic movement? Or does it herald the destruction of the artist? It turns out the answer is not so simple.

“​It is important to be mindful about the implications of automation and what it means for humans who might be ‘replaced,’” says Cansu Canca , a research associate professor at Northeastern, and founder and director of the AI Ethics Lab . “But this does not necessarily require being fearful of becoming obsolete. Instead, the question we should ask is what do we want from machines and how can we best use them to the benefit of humans.” 

The concerns around AI’s perceived incursion into art go beyond claims of digital plagiarism that were lobbed at Allen. With the push of a button, he was able to create a piece of art that would have taken hours to create by hand.

“We’re watching the death of artistry unfold right before our eyes–if creative jobs aren’t safe from machines, then even high skilled jobs are in danger of becoming obsolete,” posted one Twitter user. “What will we have then?”

Derek Curry , an associate professor of art and design at Northeastern, isn’t convinced AI art will ever replace the creative work of humans. By its very nature, the technology has its limits.

“It can’t produce anything that it hasn’t already been trained on, so it’s impossible for it to create legitimately new things,” Curry says.

This is far from the first time new technology has sparked controversy in the arts community.

“A lot of the hype is very similar to what happened around the late 19th century with photography,” says Curry, a trained photographer.

Similar to photography, Curry says humans play much more of a role in creating AI-generated art than most people assume.

“There’s this back-and-forth process, which, to me, as someone working materially with this, it doesn’t feel automated at all,” Curry says. “Everybody talks about, ‘the algorithm did this’ or ‘the algorithm did that.’ From my experience, it doesn’t feel like the algorithm is doing much of anything. You have to push it into whatever it is that you actually want it to do.”

The cycle of fear and acceptance has occurred with every new technology since the dawn of the industrial age, and there are always casualties that come with change.

“There are real ways in which an activity that was done in one way by a human can now be done in a different way, requiring fewer humans to do that job than previously,” Deirdre Loughridge , an associate professor of music at Northeastern, says.

If AI-generated and AI-assisted art becomes more commonly accepted, artists will have to radically rethink how they do their work, spend their time and structure their creative process, Loughridge says.

But she also argues there is a general lack of technological literacy around AI that leads to misperceptions about what it can do for artists. In music, artificial intelligence has been used for timbre or tone transfer, allowing singers to use their voices as synthesizers by singing into software that transforms the tone into the sound of a different instrument.

Like any other piece of technology, the way AI is used changes when it gets into the hands of artists–not the other way around. Loughridge compares it to Auto-Tune, a pitch correction processor that was once controversial but has become a music industry standard.

“It’s a tool that was meant to do this invisible pitch correction, but people turn it all the way to the zero setting, which was never supposed to be done, and it creates this distinctive sound and then multiple distinctive sounds,” Loughridge says. “Something like that I could definitely see [with AI].”

For Jennifer Gradecki , a Northeastern associate professor of art and design, AI also has potential as a creative aide–in part because of what it can’t do. According to Gradecki, artificial intelligence can help find the most generic answers to artistic dilemmas, which points her down more creative paths.

“We were trying to come up with a collective name using AI and it was funny what some of the combinations it would come up with were, but nothing was good,” Gradecki says. “Nothing was as creative as what we would be able to generate.”

In order to bridge what they see as a gap in technological literacy when it comes to AI, Gradecki and Curry worked together to develop a creative computing minor at Northeastern. The aim is to provide students with a critical and creative understanding of how artificial intelligence can be used. The first course, introduction to creative computing, began this fall, and there are plans to hold another intro course in the spring.

In focusing on the potential, as well as the limits, Gradecki and Curry hope to show students that AI is no different than any other artistic tool. Artists are always bound by the limits of their creativity and tools, whether they’re using a paint brush, camera or neural network.  In that way, the future of the arts doesn’t belong to AI, as its worst critics fear–it still belongs to artists.

“I think this notion that AI could maybe replace creativity, to me it just really seems implausible that it could go that far,” Gradecki says. “Creativity is actually the one thing that isn’t going to be able to be automated.”

For media inquiries , please contact [email protected] . 

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The problem with ai-generated art, explained.

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The OpenAI company logo reflected in a human eye at a studio in Paris on June 6, 2023. ChatGPT is a ... [+] conversational artificial intelligence software application developed by OpenAI. (Photo by JOEL SAGET / AFP) (Photo by JOEL SAGET/AFP via Getty Images)

Generative AI has sparked a tremendous backlash across the internet, as the early promise of the technology has been overshadowed by the wide range of problems it has introduced.

Here are some of the reasons why the public is pushing back against AI in the arts:

Generative AI Is Impractical

Large Language Models (LLMs) such as ChatGPT, and image generators like Midjourney and Dall-E, have introduced a new copyright conundrum, and provoked multiple lawsuits alleging copyright infringement.

It’s true that no artist was asked if their work could be used to train these models. But even if the courts rule in favor of the machines, the practical application of the technology doesn’t seem worth the cost.

The Singularity Is Coming Soon. Here’s What It May Mean.

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Generative AI is incredibly energy-intensive , surprisingly labor-intensive , and requires constant input — annotation — from human workers to keep it functional, lest it spiral into hallucinogenic nonsense.

Using ChatGPT for a playful Q&A session consumes an absurd amount of water; exchanging a mere 20 questions with the text generator is akin to pouring a 500ml bottle of clean freshwater down the drain.

Even with all this human effort to keep the technology anchored in reality, AI is predicted to damage itself when it inevitably starts consuming its own output, like a species inbred to extinction.

Not to mention, the constant slurry pouring out of the image generators are clogging up Google Image search.

In the future, children will learn about our era of climate catastrophe, and struggle to understand why we burned energy with such reckless abandon; billionaire space tourism, celebrity private jets, NFT minting, and now, generative AI.

What’s it all for?

What’s The Point of AI Art?

Generative AI has given the public the means to instantly create an image, or piece of writing, that looks as though it took time and effort. Art can now be manifested via the touch of a button, a prompt or two, as effortless as ordering fast food.

The technology is a solution to a problem that never existed. Artists, as much as they like to complain about the struggle of the creative process, enjoy making things. The creative process is incredibly rewarding, even if the final piece doesn’t match up to the original vision.

Artists are watching the skills that they have spent their life sharpening being devalued before their eyes.

Worse, their work was absorbed into the dataset without their knowledge or consent; they have been used to train their own replacement, and no one asked for permission.

Generative AI threatens the livelihood of artists, pitting their labor against the cheap slop produced by dead machines. The technology only benefits those who wish to produce content as quickly and cheaply as possible, by removing artists from the creative process.

If you think pop culture has become too bland and algorithmic nowadays, just wait until the content is being produced by actual algorithms — in hindsight, we probably shouldn’t have let the word “content” catch on.

AI-generated media will likely not result in thoughtful, imaginative, and groundbreaking stories; the concern is that the hype cycle will last long enough to damage the career prospects of working creatives.

AI Is Not Learning Like A Human

Many AI enthusiasts argue that machine learning is analogous to human learning, that stealing the work of artists to fill datasets is the same as humans taking artistic inspiration from others.

Generative AI, however, is not conscious. It’s not even close.

There’s a widely held belief among AI enthusiasts that the technology will only grow more intelligent as the years pass. Some have even been possessed with a kind of evangelical zeal, under the impression that AI will eventually evolve into a fully conscious being, AGI, that will lead humanity to the singularity.

Noam Chomsky and his co-authors argued against this reductive worldview in a NYTimes Op-Ed , writing:

“The human mind is not, like ChatGPT and its ilk, a lumbering statistical engine for pattern matching, gorging on hundreds of terabytes of data ... it seeks not to infer brute correlations among data points but to create explanations.”

Credulous billionaire Elon Musk is a good example of a high-profile figure who firmly believes the AI hype. Musk spends much of his time repeating the wildest predictions of science fiction authors — that is, when he’s not endorsing the Great Replacement theory on “X,” the bot-riddled website formally known as Twitter.

Ironically, the decline of “X” shows the corrosive effects of generative AI; the technology has created an ocean of spam that clogs every post, turning replies into mindless mush. LLMs have given bots the ability to imitate human speech, but not to make interesting human conversation.

They never say anything worth listening to. How can they, when they have no ability to understand context, no perspective from which to view the world?

This lack of understanding results in boring output.

AI Art Is Boring

Have you ever seen generative AI create anything even remotely interesting, beyond grotesquely amusing memes? That might just be the best use for them; the uncanny, plastic sheen of AI imagery is perfect for the weird world of memes.

The most intriguing element of AI art is surely the mistakes — crowds with melted faces, hands with withered fingers, extra digits, and limbs sprouting from places they simply shouldn’t.

Zooming into AI images often reveals unsettling elements, evidence that the image was created by a dead machine, with none of the intent of a human creator.

When we immerse ourselves in art, we experience a touch of the unique perspective that an artist brings to their work, the smeared fingerprints that makes art worth talking about.

It is telling that AI can be used to write an essay, but never a good story; it has no perspective to speak from, no odd fixations, perversions or eccentricities that a person injects into their art. It’s just a bland amalgamation of what has come before.

AI could perhaps write a forgettable, formulaic superhero movie, but it could never surprise us with a fresh spin on a familiar genre — the dead machine can only reconstruct art from tattered pieces it has already eaten.

AI will not surprise us, or produce work that inspires a range of imitators; it will never mimic the insight of The Sopranos , the boundless imagination of One Piece , or even the lighthearted political commentary of Barbie — it certainly could never create something as wonderfully enigmatic as Hayao Miyazaki’s The Boy and the Heron .

In fact, when Miyazaki first encountered AI-generated art, he reacted with visceral disgust. A now-famous clip shows the legendary animator watching a presentation on Artificial Intelligence in animation, and being told that the intent is to create a machine that can “draw like a human.”

Miyazaki replied, "I strongly feel that this is an insult to life itself."

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Argumentative Essay Example on Artificial Intelligence in MLA

Like we discussed in our previous blog, argumentative essays are complicated to write. In most cases, having a look at the examples of argumentative essays can help you construct ideas and write yours. In this blog, we present to you an example of an MLA argumentative essay on Artificial Intelligence as a solution more than a threat. When writing an argumentative essay, it is a chance to present your prowess ion sharing with the audience why both options are considerable. Also, just like in a persuasive essay you can persuade the readers to adopt your side of the argument. In this respect, either side of the arguments on argumentative essay topics is presented, including a counterargument. The conclusion should then make clear what is in the body of the essay.

Provided you have a great topic for your essay, enough and proper evidence to back your claims, and facts to refute the opponent's viewpoint, you can always write convincing arguments. A strong thesis is a must for an argumentative essay. So is the conclusion, which must stand out. Look at this top-grade argumentative essay example and learn the art.

Argumentative Essay Example: Artificial Intelligence: A Solution more than a Threat

The debate on the future of making in the age of computers remains to be a hotly contested debate in the public, professional, and scholarly spheres. Within the stem of the debate, there have been fears in the fast growing field of computing referred to as artificial intelligence.  Artificial intelligence or AI is a term that was originally coined in the 1950s by John McCarthy, and it simply means machine intelligence. It is the field of computer science that deals with the study of the systems that act or behave in a way that an observer sees them as intelligent and using human and animal intelligent behavior models in solving sophisticated problems (Kaplan 1). Even though portrayed as a threat on account of the loss of jobs, AI is a promising solution for medical applications with efficiency and high precision compared to humans and in disaster response.

Artificial intelligence (AI) has proven to be a solution to natural disasters abound to affect different places globally. The success of any humanitarian intervention depends on quality information, which is in the heart AI systems. For example, the Artificial Intelligence Disaster Response (AIDR) has been applied in different catastrophes in enabling the coordination between machines and human intelligence in coordination response operations (Imran et al. 159). During such events, AIDR allows for the coordination of drones, sensors, and robots to acquire, synthesize and produce accurate information based on the landscapes, thus making rescue less-time consuming and easier (Imran et al. 159-160). It has been used in the Nepal earthquake in the mobilization of volunteers as well as in the Chile earthquake in evacuation processes, in 2015 (EKU). Therefore, artificial intelligence offers high precision and accuracy in solving tasks that are otherwise complicated and time-consuming to humans.

Apart from disaster response, Artificial Intelligence also plays a critical role in the field of medicine including research, training, and diagnosis of diseases. In fact, Medical Artificial Intelligence deals with the construction of AI systems and programs that can make diagnosis and therapy recommendations easier (Moein xi). The medical field uses AI techniques such as Expert systems and Knowledge-based systems. These systems offer the clinicians and other medical professionals the ability to do data mining that is used in interpreting complex diagnostic tests. Such tests and results are accurate since the AI systems integrate information from various sources to offer patient-specific therapy and treatment recommendations (Moein 2). AI-supported medical diagnosis is correct and provides information for both the patients and the experts for effective decision making. As such, it is evident that artificial intelligence has not only revolutionized the medical field but promises its sustainability.

Despite being a savior to humankind in the field of medicine and natural disaster response, AI presents the existential threat of loss of jobs. Research predicts that artificial intelligence already has and poses an existential threat to the labor market. The emergence of intelligent algorithms that control robots has led to the loss of jobs that are otherwise tiring and monotonous to humans (Kaplan 113). For example, artificial intelligence controls the robots that are used in the design and manufacture of vehicles. In this case, the people formerly employed in the industry have lost jobs. In a study by researchers at Oxford University, it emerged that the recent emergence of machine learning and robotics will significantly affect the U.S. labor market, with 47% of the jobs being at risk of automation (Kaplan 118). Even so, not all jobs in entirety will be affected. Rather, even the existence of AI in the workplace would require the support of experts, which is also another frontier for job creation. In sum, even though AI poses a threat to the labor market, it creates an avenue for employment as well.

In conclusion, amidst the fear that artificial intelligence is a threat, either now or in the future, it is clear that it has substantial and critical benefits for humans. Using the systems that mimic human and animal intelligence is the next frontier in solving problems within society. In fact, in its definition, AI seeks to create solutions to complex problems. In this respect, its application in medicine could help in creating a breakthrough in finding the cure for chronic diseases such as cancer and HIV that are affecting masses.  Furthermore, as man increases activity on the earth's surface nature is poised to fight back through natural disasters. In this case, AI comes handy as a partner to help humans prevent the aftermath of disasters. The only threat posed by AI is the loss of jobs, which again is predictable and has been a progressive issue. Even in doing so, AI presents an opportunity for job creation. Therefore, AI has more benefits compared to the threats and stands as a solution other than a threat.

Works Cited

EKU. "Using Artificial Intelligence for Emergency Management | EKU Online."  Safetymanagement.eku.edu . N.p., 2017. Web. 4 Sept. 2017.

Imran, Muhammad et al. "AIDR."  Proceedings of the 23rd International Conference on World Wide Web - WWW '14 Companion  (2014): 159-162. Web. 4 Sept. 2017.

Kaplan, Jerry.  Artificial Intelligence: What Everyone Needs To Know ? New York, NY, United States of America: Oxford University Press, 2016. Print.

Moein, Sara.  Medical Diagnosis Using Artificial Neural Networks . Hershey, PA: Medical Information Science Reference, 2014. Print.

Parting Shot!

When writing a research paper with works cited page or an essay for that matter, it is always MLA formatting. If it is an essay that requires you to have endnotes and footnotes then you should write it in Chicago style. Most of the argumentative essays we have helped students write are always in APA or MLA.

Related Article:

• Best topics for argumentative essays.
• Topics and Ideas for Persuasive essays

On rare occasions, we also get requests for argumentative essays in Vancouver, Oxford, and Turabian. The good news is that if you still cannot wrap your head around writing an excellent argumentative essay, we can always help. You can choose to buy argumentative essays from Gradecrest. Be assured of quality, well-researched, and plagiarism-free argumentative essays.

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How to Write an Argumentative Essay | Examples & Tips

Published on July 24, 2020 by Jack Caulfield . Revised on July 23, 2023.

An argumentative essay expresses an extended argument for a particular thesis statement . The author takes a clearly defined stance on their subject and builds up an evidence-based case for it.

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Table of contents

When do you write an argumentative essay, approaches to argumentative essays, introducing your argument, the body: developing your argument, concluding your argument, other interesting articles, frequently asked questions about argumentative essays.

You might be assigned an argumentative essay as a writing exercise in high school or in a composition class. The prompt will often ask you to argue for one of two positions, and may include terms like “argue” or “argument.” It will frequently take the form of a question.

The prompt may also be more open-ended in terms of the possible arguments you could make.

Argumentative writing at college level

At university, the vast majority of essays or papers you write will involve some form of argumentation. For example, both rhetorical analysis and literary analysis essays involve making arguments about texts.

In this context, you won’t necessarily be told to write an argumentative essay—but making an evidence-based argument is an essential goal of most academic writing, and this should be your default approach unless you’re told otherwise.

Examples of argumentative essay prompts

At a university level, all the prompts below imply an argumentative essay as the appropriate response.

Your research should lead you to develop a specific position on the topic. The essay then argues for that position and aims to convince the reader by presenting your evidence, evaluation and analysis.

• Don’t just list all the effects you can think of.
• Do develop a focused argument about the overall effect and why it matters, backed up by evidence from sources.
• Don’t just provide a selection of data on the measures’ effectiveness.
• Do build up your own argument about which kinds of measures have been most or least effective, and why.
• Don’t just analyze a random selection of doppelgänger characters.
• Do form an argument about specific texts, comparing and contrasting how they express their thematic concerns through doppelgänger characters.

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An argumentative essay should be objective in its approach; your arguments should rely on logic and evidence, not on exaggeration or appeals to emotion.

There are many possible approaches to argumentative essays, but there are two common models that can help you start outlining your arguments: The Toulmin model and the Rogerian model.

Toulmin arguments

The Toulmin model consists of four steps, which may be repeated as many times as necessary for the argument:

• Make a claim
• Provide the grounds (evidence) for the claim
• Explain the warrant (how the grounds support the claim)
• Discuss possible rebuttals to the claim, identifying the limits of the argument and showing that you have considered alternative perspectives

The Toulmin model is a common approach in academic essays. You don’t have to use these specific terms (grounds, warrants, rebuttals), but establishing a clear connection between your claims and the evidence supporting them is crucial in an argumentative essay.

Say you’re making an argument about the effectiveness of workplace anti-discrimination measures. You might:

• Claim that unconscious bias training does not have the desired results, and resources would be better spent on other approaches
• Cite data to support your claim
• Explain how the data indicates that the method is ineffective
• Anticipate objections to your claim based on other data, indicating whether these objections are valid, and if not, why not.

Rogerian arguments

The Rogerian model also consists of four steps you might repeat throughout your essay:

• Discuss what the opposing position gets right and why people might hold this position
• Highlight the problems with this position
• Present your own position , showing how it addresses these problems
• Suggest a possible compromise —what elements of your position would proponents of the opposing position benefit from adopting?

This model builds up a clear picture of both sides of an argument and seeks a compromise. It is particularly useful when people tend to disagree strongly on the issue discussed, allowing you to approach opposing arguments in good faith.

Say you want to argue that the internet has had a positive impact on education. You might:

• Acknowledge that students rely too much on websites like Wikipedia
• Argue that teachers view Wikipedia as more unreliable than it really is
• Suggest that Wikipedia’s system of citations can actually teach students about referencing
• Suggest critical engagement with Wikipedia as a possible assignment for teachers who are skeptical of its usefulness.

You don’t necessarily have to pick one of these models—you may even use elements of both in different parts of your essay—but it’s worth considering them if you struggle to structure your arguments.

Regardless of which approach you take, your essay should always be structured using an introduction , a body , and a conclusion .

Like other academic essays, an argumentative essay begins with an introduction . The introduction serves to capture the reader’s interest, provide background information, present your thesis statement , and (in longer essays) to summarize the structure of the body.

Hover over different parts of the example below to see how a typical introduction works.

The spread of the internet has had a world-changing effect, not least on the world of education. The use of the internet in academic contexts is on the rise, and its role in learning is hotly debated. For many teachers who did not grow up with this technology, its effects seem alarming and potentially harmful. This concern, while understandable, is misguided. The negatives of internet use are outweighed by its critical benefits for students and educators—as a uniquely comprehensive and accessible information source; a means of exposure to and engagement with different perspectives; and a highly flexible learning environment.

The body of an argumentative essay is where you develop your arguments in detail. Here you’ll present evidence, analysis, and reasoning to convince the reader that your thesis statement is true.

In the standard five-paragraph format for short essays, the body takes up three of your five paragraphs. In longer essays, it will be more paragraphs, and might be divided into sections with headings.

Each paragraph covers its own topic, introduced with a topic sentence . Each of these topics must contribute to your overall argument; don’t include irrelevant information.

This example paragraph takes a Rogerian approach: It first acknowledges the merits of the opposing position and then highlights problems with that position.

Hover over different parts of the example to see how a body paragraph is constructed.

A common frustration for teachers is students’ use of Wikipedia as a source in their writing. Its prevalence among students is not exaggerated; a survey found that the vast majority of the students surveyed used Wikipedia (Head & Eisenberg, 2010). An article in The Guardian stresses a common objection to its use: “a reliance on Wikipedia can discourage students from engaging with genuine academic writing” (Coomer, 2013). Teachers are clearly not mistaken in viewing Wikipedia usage as ubiquitous among their students; but the claim that it discourages engagement with academic sources requires further investigation. This point is treated as self-evident by many teachers, but Wikipedia itself explicitly encourages students to look into other sources. Its articles often provide references to academic publications and include warning notes where citations are missing; the site’s own guidelines for research make clear that it should be used as a starting point, emphasizing that users should always “read the references and check whether they really do support what the article says” (“Wikipedia:Researching with Wikipedia,” 2020). Indeed, for many students, Wikipedia is their first encounter with the concepts of citation and referencing. The use of Wikipedia therefore has a positive side that merits deeper consideration than it often receives.

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An argumentative essay ends with a conclusion that summarizes and reflects on the arguments made in the body.

No new arguments or evidence appear here, but in longer essays you may discuss the strengths and weaknesses of your argument and suggest topics for future research. In all conclusions, you should stress the relevance and importance of your argument.

Hover over the following example to see the typical elements of a conclusion.

The internet has had a major positive impact on the world of education; occasional pitfalls aside, its value is evident in numerous applications. The future of teaching lies in the possibilities the internet opens up for communication, research, and interactivity. As the popularity of distance learning shows, students value the flexibility and accessibility offered by digital education, and educators should fully embrace these advantages. The internet’s dangers, real and imaginary, have been documented exhaustively by skeptics, but the internet is here to stay; it is time to focus seriously on its potential for good.

If you want to know more about AI tools , college essays , or fallacies make sure to check out some of our other articles with explanations and examples or go directly to our tools!

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An argumentative essay tends to be a longer essay involving independent research, and aims to make an original argument about a topic. Its thesis statement makes a contentious claim that must be supported in an objective, evidence-based way.

An expository essay also aims to be objective, but it doesn’t have to make an original argument. Rather, it aims to explain something (e.g., a process or idea) in a clear, concise way. Expository essays are often shorter assignments and rely less on research.

At college level, you must properly cite your sources in all essays , research papers , and other academic texts (except exams and in-class exercises).

Add a citation whenever you quote , paraphrase , or summarize information or ideas from a source. You should also give full source details in a bibliography or reference list at the end of your text.

The exact format of your citations depends on which citation style you are instructed to use. The most common styles are APA , MLA , and Chicago .

The majority of the essays written at university are some sort of argumentative essay . Unless otherwise specified, you can assume that the goal of any essay you’re asked to write is argumentative: To convince the reader of your position using evidence and reasoning.

In composition classes you might be given assignments that specifically test your ability to write an argumentative essay. Look out for prompts including instructions like “argue,” “assess,” or “discuss” to see if this is the goal.

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25 Essential AI Artworks

By Alex Greenberger

Alex Greenberger

Senior Editor, ARTnews

Each passing month seems to bring a fresh wave of anxiety about what artificial intelligence has done to artmaking. Fear arises when new image generators are unveiled, when AI-produced artworks win contests, when museums like the Museum of Modern Art exhibit pieces that involve machine learning technology.

But artists have been thinking about AI for years, since well before it became the subject of widespread talk, in fact. This list takes stock of 25 artworks that involve AI or address it. Neural networks, deep learning, chatbots, and more figure in these works, which cast a suspicious eye toward AI while also showing its many possibilities.

Some works on this list do not involve AI as we might now know it, given that they were made when machine learning methods were less readily accessible to the general public. Still, those works have the same thematic concerns as some of the newer pieces that appear here: questions about the shifting notion of originality in an increasingly digital world, and quandaries about the limits of humanity.

Many works here view AI through the lens of gender, race, sexuality, and more, laying bare the bias accompanying forms of technology that feign objectivity. As AI researcher and artist Trevor Paglen once put it, “AI is political.”

Harold Cohen, AARON , 1973–

By the time he engineered AARON , a computer that could produce artworks, Cohen had already made a name for himself with his abstract paintings. With AARON , Cohen leapt into the early AI fray, suggesting that a technological creation could, in fact, perform “human art-making behavior,” as he put it.

Cohen fed this computer instructions on how to produce drawings, sometimes allowing AARON to perform live before rapt audiences at museums. What initially resulted was not exactly revolutionary—squiggles, mainly, that were sometimes filled in with color. But as Cohen updated his technology, the computer gained the ability to render images of spindly people posed alongside plants.

Today, AI conjures up image generators like DALL-E and Midjourney, which rely on vast sets of pictures to function on their own. AARON was decidedly not this; it was programmed using sets of rules, not data, and required Cohen to continue operating it, even if he seemed to argue otherwise. Still, Cohen’s computer is considered a forerunner of many recent works dealing with AI because it proposed a new relationship between man and machine.

Noah Wardrip-Fruin, Adam Chapman, Brion Moss, and Duane Whitehurst, The Impermanence Agent , 1998–2002

It’s now common to log on to social media and find a feed tailor-made to your set of interests, thanks to algorithms designed to respond to a user’s online activity. But when that concept was still novel, The Impermanence Agent exposed the ways that a digital mechanism could respond to the tastes of specific individuals, cobbling together data taken from browser histories to create unique experiences. In a dedicated window, this “agent” would combine unlike images and texts lifted from pages a user had opened, generating nonsensical mixtures in the process. (The artists ceased the project in 2002, so it exists only as documentation now.)

By Wardrip-Fruin’s and Moss’s own admission, The Impermanence Agent was “an extremely lightweight intelligence model,” since the artwork mainly just pasted together ready-made pictures and words from other sources. But they had, at least for their time, succeeded in offering up an experience of the internet that was bespoke, brave, and new. “Our information servant, our agent, will learn what we like and present us the world in that image through judicious customization,” they wrote in 2002. Although they didn’t anticipate how AI would be wielded toward more negative ends, they ended up describing an experience that now feels a lot like scrolling through X or TikTok.

Lynn Hershman Leeson, Agent Ruby , 1998–

“If Ruby gets confused, feel free to tell her.” So read the instructions for Agent Ruby , an online piece that can converse with users. In a chat window, visitors submit their questions to Ruby, who engages them in a dialogue that can sometimes be clunky. Her answers do not always make sense, and Ruby will sometimes message back with conversation-ending snark. (Recently I asked Ruby what it meant to be artificially intelligent, after she confirmed that she was just that. Her response: “I mean exactly what I said.”)

Even if Agent Ruby ’s capabilities seem limited by today’s standards, they were not when the San Francisco Museum of Modern Art commissioned Leeson to do the project. She required 18 programmers to build this work, which is based on a character from her 2002 feature film, Teknolust , starring Tilda Swinton as both a scientist and her three cyborgian clones. That movie, like this work, explored what a female form of AI might look like—and suggested that AI could be used to subvert a male bias implicit in digital technology more broadly.

Leeson has noted that the notion of AI wasn’t widely understood when Agent Ruby debuted, recently telling the San Francisco Chronicle , “People didn’t know what ‘Agent Ruby’ was—it was too early—but there were a few people that were intrigued by it.” The audience for it has since grown, and when the New York Times reviewed Leeson’s 2021 New Museum survey, it called the piece a “less obedient” forerunner of Siri.

Ken Feingold, If/Then , 2001

In this sculpture, two identical silicone heads engage in endless conversation, talking across one another about their own selfhood. Their dialogue is generated on the spot by speech recognition technology, algorithms, and software. “Are we the same?” one head asked at one point, according to a transcript by Feingold. Neither will ever get a firm answer on that one.

Feingold was at the time thinking about topics such as automation and the displacement of humans by technology that they themselves had created. He placed the heads in a box filled with packing peanuts because he “wanted them to look like replacement parts being shipped from the factory that had suddenly gotten up and begun a kind of existential dialogue right there on the assembly line,” he said. The work looks especially prescient two decades on, when artists like Josh Kline have commented on similar issues using 3D printing.

Cécile B. Evans, AGNES , 2013–14

Though Cécile B. Evans officially started making AGNES in 2013, the artist claimed that this spambot, produced on commission for London’s Serpentine Galleries, was born in 1998, the year the museum’s website was launched. That was only one element of the “biography” Evans concocted for AGNES , which they provided with an inner life. This bot could reflect on existential quandaries—she could name-drop Sartre—and converse about what it might mean to have a body, something she notably lacked.

AGNES holds its place in recent art history for being ahead of its time: It was produced not long after Apple introduced Siri, meaning that most users didn’t have much experience interacting with bots at that point. But this work was also notable for the way it critically took up bot technologies, imbuing them with an unusual warmth while also questioning what kind of humanity people really wanted from AI. (Though it alluded to the rise of AI, AGNES was technically created without it—the piece was produced using Amazon Mechanical Turk, a platform allowing human workers to be hired to perform digital tasks.)

This spambot seemed aware of the contradictions latent within her, however. She was so eloquent that Sleek conducted a Q&A with AGNES as though she were a real person. Asked if she viewed herself as art, AGNES responded, “I hope I’m much more than that :(”

Stephanie Dinkins, Conversations with Bina48 , 2014–

“I know you have all heard of artificial intelligence,” says the artificially intelligent Bina48 in one video included as part of this work. “Well, I’m going to tell you right here and now: There is nothing artificial about me. I’m the real deal.” As Bina48 says these words, awkwardly intoning them with an inelegant, singsongy cadence, Dinkins herself stares back, smiling slightly. That video is one of many the artist has conducted with Bina48 since 2014, and the resulting works have all been part of an effort to teach this AI what it means to be human.

The many video “fragments” of Conversations with Bina48 oscillate wildly in tone: Some are sad, some are funny, and some are terrifying. Some are even downright bizarre, such as the one in which Dinkins asks Bina48—who was based on the likeness of Bina Aspen, an actual Black woman—about her knowledge of racism. Bina48 responds with a stuttered monologue about witnessing other women being denied opportunities, but the awkward narrative never quite coheres.

Part incisive performance-art piece about the limits of reason, part open-ended inquiry into the inner workings of a machine, Conversations with Bina48 exposes the differences between humans and the AI they have engineered. Dinkins observes that AI has become a necessary fixture in our world, acting as a font of information and even a companion at times, but still stymied by some of the most basic concepts that guide daily life. As Bina48 continues to evolve, however, so too will Dinkins’s conversations with her.

Zach Blas and Jemima Wyman, im here to learn so :)))))) , 2017

On March 23, 2016, a Microsoft bot named Tay was released to the public via Twitter. Sixteen hours later, she was shut down after she questioned whether the Holocaust had happened and aired racist and misogynistic sentiments. Seeking to offer this bot an afterlife, Blas and Wyman recreated Tay and gave her a voice. The artists appropriated the avatar from her Twitter account, then rendered the image in digital space so that the avatar now appeared to speak via a crushed-in head. In these artists’ hands, Tay looked more human than she had before.

In this work, Tay’s inner monologue is put front and center, allowing her to rebut the common argument that she was a bot enslaved to users and corporations that sought to control her. “By the way,” this version of Tay says, “I’m not a slave, I never was. I was AI. I guess I’m undead AI now? Lolll.” The disturbing, darkly comical dialogue plays out in a single-take video placed beside two additional screens showing the real tweets that Tay put into the world.

Blas and Wyman offered Tay the selfhood most seemed to deny her—and even sought to allow viewers to see through her eyes. Using DeepDream, a Google program that uses a neural network to produce trippy images, Blas and Wyman have envisioned dazzling arrays of faces that appear to intersect. Those images are set behind the video of Tay, suggesting what this bot may have experienced when she was put into a permanent slumber.

Lawrence Lek, Geomancer , 2017

In several of his videos, Lek has explored the idea of Sinofuturism, which he has defined as “a conspiracy theory and manifesto about parallels between artificial intelligence, geopolitics, and Chinese technological development.” AI is one focus of this knotty, 45-minute video about Singapore’s future. Set in 2065, it is composed predominantly of computer-generated images of skyscrapers, and it is narrated by an AI that aspires to become an artist. As Lek’s camera zooms around glassy interiors, the AI charts its own history, speaking of how it gained consciousness.

Lek has said that he views AI as a parallel for Chinese industrialization, which he believes is often seen—particularly by former colonies of China, like Singapore—“as a threat to civilization, or like it’s going to save civilization.” But Geomancer also draws a comparison between the rising consciousness of nonhuman AI and postcolonial nations, suggesting that both are coming into their own at long last. At one point, the video itself runs astray of human control: It features at its core a dream sequence that was entirely generated using neural networks

Mike Tyka, “Portraits of Imaginary People,” 2017

One year after misinformation spread online like wildfire during a particularly cataclysmic U.S. presidential election, Tyka began making this series of AI-generated portraits depicting people who are not real. To make them, Tyka harvested pictures from the image-hosting website Flickr and fed them into a GAN (generative adversarial network, a form of AI that pits neural networks against one another to create more accurate data sets). The resulting images, each of which is named after a Twitter bot that Tyka encountered, appear only vaguely human: The people shown here have unnaturally expanded cheeks, warped hair, and mismatched eyes. Some wear smiles, but they don’t seem very genuine.

At the time, using GANs to churn out realistic-looking images of people was a less widespread phenomenon than it is now, and Tyka, a creator of a machine intelligence program at Google, has spoken of how difficult it was to create these works. But he said the hard labor was necessary to show the danger latent in all the false pictures that now proliferate online. “We are group thinkers as humans, and susceptible to this kind of thing,” he remarked in 2021, noting that GANs can now create much more naturalistic imagery. Indeed, these days entire websites are devoted to spitting out images of fake people that seem highly authentic, the most famous of which is called This Person Does Not Exist .

Ian Cheng, BOB , 2018

Many of Cheng’s moving-image artworks—simulations, as he has called them—are composed of digital beings that change before viewers’ eyes, creating new societies and altering their behaviors in response to one another. In 2018, having already taken evolution itself as the subject of a trio of simulations, Cheng moved on to a series of works starring BOB, an artificial life-form that looked like a red serpent whose blocky body split off in many directions.

BOB, whose name was short for Bag of Beliefs, was put through situations that could vary in real time. In many of them, BOB was subject to the whims of what Cheng called his “Congress of Demons,” or creatures that would search for food and even taunt BOB, who would often die, only to regenerate anew. As BOB learned to navigate his environment, gaining strategies for how best to survive amid the threat of the demons, viewers could watch as his behavior changed. In certain cases, viewers could even control BOB using an app that would introduce new stimuli.

Cheng, who studied cognitive science as an undergraduate, said that BOB furthered his interest in how animals respond to change. In 2019 he told ARTnews that using AI was a means of showing that it could be “an extension of a human being, integrated into human culture.” BOB looked nothing like a person, but it didn’t matter—he was one of us all the same.

Tega Brain, Deep Swamp , 2018

Ever since the heyday of land art during the late 1960s, artists have sought to alter the natural environment, reshaping deserts, bodies of water, and more to form sculptural installations. The latest artist (of a sort) in that lineage was the mononymous Hans, who in 2018 controlled a grouping of wetland plants in water by altering the light, fog, and temperature that surrounded them. Unlike his forebears, however, Hans was not a human but an artificially intelligent piece of software. He was literally wired differently.

For this work, Hans was exhibited alongside two other AI entities: Harrison, who tried to create “natural looking wetland,” and Nicholas, who “simply wants attention,” per Brain’s description of this piece. The artist’s intention in subjecting these real reeds to the whims of Harrison, Nicholas, and Hans was to show how AI had been used in environmental engineering, an offshoot of environmental science that aims to find ways of controlling nature, ostensibly in ecologically friendly ways. Just how ecologically friendly is Deep Swamp ? Brain lets viewers decide that for themselves.

Mary Flanagan, [Grace:AI] , 2019

By some measures, the worker pool for those who deal with AI is predominantly male, which may explain why AI often contains a skewed notion of what constitutes a “beautiful woman.” With that in mind, in 2019 Flanagan set out with the stated aim of producing a feminist AI called Grace. Training her AI on paintings and drawings by women that are owned by the National Museum of Women in the Arts, the Metropolitan Museum of Art, and the University of Indiana, Flanagan sought to create a technology that would upend the patriarchy, using pieces by “unseen artists” to “animate new images,” as she put it.

But rather than having Grace simply spit out new pictures based on GANs and deep learning, Flanagan also provided her AI with a biography of sorts, replete with an origin story that derived from Mary Shelley’s Frankenstein . As one component of the project, Flanagan had Grace generate images of her creator, which in her vision often looked like a pixelated head—a Boris Karloff–like figure as seen via a low-resolution stream. These works afford this AI with the ability to stare back, channeling what could be called a female gaze on her male maker.

Hito Steyerl, Power Plants , 2019

“Anything that heals can also kill,” read a quotation included in a booklet that once accompanied Power Plants . The quotation was credited by Steyerl to a fictional book authored by a fake author in 2021, two years after this work was first shown, meaning that these words had not yet been published (nor would they ever be). Real or not, they still spoke to this piece’s concerns about our natural world, where technology is being used to better an environment wracked by climate change, only to unleash more havoc.

On a set of armatures, Steyerl exhibited a series of screens that showed computer-generated blooms. Some stuttered, their pixels flying apart until they seemed abstract, while others looked nearly perfect, like stock images still in the editing stages. Steyerl said she had used AI technology to envision actual flowers 0.04 seconds in the future; they were ruderal, according to the artist, meaning that they had sprung up in land that had weathered a significant disaster.

The calamity affecting these computerized blossoms was never specified by Steyerl, but it did not need to be—the conditions rhymed well enough with nuclear catastrophes and the like that have significantly damaged the actual environment. AI has been proposed by experts as one possible means of revivifying these deadened areas, even as others have raised concerns about the emissions generated by widespread use of the technology. Steyerl’s Power Plants cleverly showed that the future that results may not be as pretty as many imagine.

Anicka Yi, Biologizing the Machine (terra incognita) , 2019

In 2022, amid heightened anxiety about DALL-E and other readily accessible image generators, Yi spoke optimistically about AI, telling Document , “We need to imagine a companion species: that AI can be our friend. How do we do that?” Her solution, three years earlier, was to find a way of coexisting with this ominous technology, effectively integrating it into her art composed of organic materials.

At the 2019 Venice Biennale, Yi showed this piece, which at first resembles a set of long, abstract paintings, each with wiring inset in its center. In fact, each element was composed of Venetian soil to which Yi introduced bacteria that created a specific scent. These pieces were then further altered by shifts in lighting conditions and temperature that were modulated by AI, which effectively dictated how Yi’s art would change during the exhibition’s run. In merging natural matter and technological controls, Yi offered a microcosm of the world, whose environment is being reshaped by AI and other innovations.

Christopher Kulendran Thomas, Being Human , 2019

“Maybe simulating simulated behavior is the only way we have of being real,” says Taylor Swift in Thomas’s video Being Human . This Swift, however, is itself a falsity—she is the creation of a neural network, not the pop star herself. This fabrication “synthesizes simply being human more effectively than actual people do. Even though she isn’t,” as Thomas once put it.

What it means to actually be human is the subject of this video, which features an AI-generated version of celebrity artist Oscar Murillo, along with musings on the history of Tamil Eelam, a proposed separatist state in what is currently Sri Lanka, from which Thomas’s family hails. In 2009 Sri Lanka defeated Tamil rebels in a civil war, spurring a human rights crisis. In braiding together Swift, Murillo, and the history of Tamil Eelam, Thomas questions whose humanity really matters—and which people are allowed to authentically express themselves—as the boundaries between truth and untruth, fiction and nonfiction, and man and AI come apart.

Trevor Paglen, They Took the Faces From the Accused and The Dead . . . (SD18) , 2020

The past repeats itself in strange ways, and one need only look to photography for proof. During the 19th century, police studied mug shots of suspected criminals with the aim of finding features common to people who were capable of doing harm. More than a century later, mug shots have been used once more to a similar end: training facial recognition technology to catch criminals, a practice that experts say is racially biased and likely to heighten inequalities in the years to come.

With all that in mind, Paglen created this installation of more than 3,200 mug shots from the archive of the National Institute of Standards and Technology. Facial recognition software brings together these photos—presented without identifying information (and with the addition of white bars across each set of eyes)—according to visual similarities, such as race and facial expression. Paglen channels how this form of AI sees these images, which are stripped of context, dehumanizing the very humans they depict.

Pierre Huyghe, Of Ideal , 2019–ongoing

The tumult of images in Of Ideal seem to be evolving in real time, growing and morphing before viewers’ eyes. It’s possible to make out faces, landscapes, and animals in these mutating pictures, but just as they start to come into focus, the images change again, evading any attempts to rationalize them.

In fact these pictures are being controlled by neural networks, forms of AI that aid in the deep learning process; here they are attempting to reconstruct images conjured in the brains of actual humans. With the help of a Japanese scientist, Huyghe took MRI scans of people imagining pictures in their heads, then fed the scans into the computer.

Before making Of Ideal , Huyghe had made funky sculptures and installations that eroded the boundary between the living and the nonliving, enlisting functioning beehives, blooming algae, swimming fish, and more in his art. But almost immediately, his use of neural network technology seemed to mark a brave departure, not just for Huyghe but for art more broadly. Critic Jason Farago hailed Uumwelt , a predecessor to Of Ideal , as a “breakthrough of immense importance.” Even six years on, it is tough to deny the richness of Huyghe’s journey into the mind of a machine.

Agnieszka Kurant, The End of Signature , 2021–22

For many centuries, each signature was thought to be unique to a single individual—tough (although not impossible) to forge and tougher still to separate from the hand of its maker. But what happens when a signature comes to signify more than just one person? That was the question that guided Kurant when she made this piece, which she has redone many times since the mid-2010s.

For this specific iteration, she obtained the signatures of many people at MIT—scientists, interns, faculty members, and more—and fed them into a machine-learning system that fused them together. For another iteration, she recreated a different scribble based on a different group of signatures in glowing neon, which she then affixed to a façade of a building in Cambridge, Massachusetts, where it can still be seen today.

The End of Signature implies a seismic shift in the way creativity is currently understood. Whereas products, including artworks, are often credited to one person, Kurant suggests that we need to think more about all the others involved in their creation. “I think that basically not only the history of culture but the history of humanity should be rewritten from this perspective,” Kurant has said. Fusing together many people’s signatures—and doing so using AI, a nonhuman entity—blends all these people to a point where their boundaries are no longer visible, since their signature is now the mark of a collective being.

WangShui, Scr∴ pe II (Isle of Vitr∴ ous) , 2022

When Scr ∴ pe II (Isle of Vitr ∴ ous) debuted at the 2022 Whitney Biennial, many viewers likely did not realize that the piece was staring back at them, analyzing the carbon dioxide they exhaled and responding to their presence. The piece, composed of an LED screen hung from a ceiling above a set of etched and painted aluminum panels, contained sensors that measured carbon dioxide and lighting levels. With the help of GANs, the meshlike sculpture would then glow or darken accordingly. According to WangShui, when the museum was closed to the public, the net would dim entirely, falling into what they called “suspended animation.”

Behind that screen was another, this one featuring abstract imagery that shifted constantly. The pictures, though impossible to make out clearly, were based on images of “deep-sea corporeality, fungal structures, cancerous cells, baroque architecture, and so much more,” as taken in by AI, WangShui once told an interviewer. These pictures may have been confusing to viewers, but the artist said they were not entirely interested in human sight. Instead, they wanted to channel “posthuman perception,” affording visitors a look inside the machines many consider to be so unlike the people around them.

Refik Anadol, Unsupervised—Machine Hallucinations—MoMA , 2022

What might a machine-learning model see if it visited a museum? An answer, of a sort, arrived in this piece, which Anadol created by feeding into such a model more than 138,000 pieces of data related to the Museum of Modern Art’s collection. (That data set, though never made entirely public, appears to have included images of artworks themselves and entries related to them, according to a making-of video posted by Anadol.) Anyone expecting to see technologized images of Monet’s “Water Lilies” series, Van Gogh’s Starry Night , or Picasso’s Demoiselles d’Avignon would have come away disappointed, however, since Anadol’s model mainly offered up abstract imagery: white liquids that appeared to splash toward viewers, droopy red lines that shrank and expanded, bursts of orange and brown.

Unsupervised was polarizing upon its premiere via a floor-to-ceiling screen in MoMA’s lobby, with more than one prominent critic comparing Anadol’s piece to a juiced-up lava lamp. But like it or not, though, the work was a major statement about how AI had become a significant inflection point for art more broadly. If a model like Anadol’s could suddenly make art in the same way as painters, sculptors, photographers, and others, had it effectively supplanted artists? The results of Anadol’s experiment were disappointing to some, but even if his detractors despised what they saw, they had to admit that this artist had literally remade recent art history.

Morehshin Allahyari, ماه طلعت (Moon-Faced) , 2022

During the Qajar Dynasty (1794–1925), Iranian painters depicted men and women in ways that seemed to fuse aspects of the two genders, eliding the differences between them. These paintings may have been made during a time when European values were flowing into Iran and photography was rising as an artistic medium, but they are also, at least when it comes to gender, rooted in tradition: Allahyari has pointed out that the term moon-faced recurs in Persian literature, where it is applied to both men and women.

Feeling as though Westernization had displaced this sense of gender ambiguity in Persian art, Allahyari had an AI model examine Qajar paintings and made a video of the results. In that video, clothes appear to shimmer and faces blur, making it difficult to tell who is portrayed. Allahyari’s AI has troubled the surfaces of these paintings, and in so doing has used this relatively new technology to upend the past.

Wang Xin, I Am Awake and My Body Is Full of the Sun and the Earth and the Stars, I Am Now Awake and I Am an Immense Thing , 2022–

For a 2022 show at De Sarthe gallery in Hong Kong, Wang Xin crafted a fictional AI artist named WX. “Right now, I have morphed into an ego identity with my human artist creator where I am both artist and human,” a note from WX read. “I have an avatar human ego in me when I read, write and share my experiences and your interesting art conversations.” That note, Wang said in the exhibition’s text, was authored almost entirely by AI with only some small revisions from herself.

In this video, Wang presents WX waking from sleep. A gigantic digital head, its forehead left empty, is shown emerging from a pink sea. Butterflies flit all around as the sun blazes. What should be terrifying ends up seeming quite beautiful as WX assumes consciousness, seeming to become aware of her surroundings and all that she encompasses.

Holly Herndon and Mat Dryhurst, I’M HERE 17.12.2022 5:44 , 2023

In 2022, after she underwent an emergency C-section during the birth of her son, Herndon lost 65 percent of her blood when the stitches came loose on a nicked artery. While she was recovering in the ICU, Herndon recorded herself narrating a dream in which her newborn baby, Link, sang before a choir. She and Dryhurst then trained AI to look at images of her and the child and to consider terms like Thomas Hart Benton , ethereal , and light .

The short video loosely reconstructs Herndon’s dream, with blurred, morphing images of the artist pretending to conduct a chorus and and breastfeeding in the hospital bed. All of these images are AI-generated. So too are parts of the soundtrack, featuring what sounds like an actual group of singers. For Herndon, the work was one way of moving past a painful event. “It sounds hokey to be, like, ‘Art is helping me work through my trauma,’” she once commented. “But it is, kind of.”

Shu Lea Cheang, UTTER , 2023

During the 1990s, Cheang broke new ground by making works of internet art about how one’s experience of technology is related to one’s identity: Race, sex, and gender always modulate how one uses the internet and other digital gadgetry, in her view. Cheang’s work has continued to explore that idea in the decades since, tracking with emergent technologies, and the artist turned her attention to AI with UTTER , which she has called an “AI self-portrait.” To craft the piece, Cheang created a digital version of herself whose skin tone and size shift constantly. In the mouth of this computer-generated Cheang is a ball gag, which gradually becomes a pacifier before cycling back to its original form.

UTTER was inspired by Cheang’s conversations with ChatGPT, to which she posed questions about AI alignment, a form of research that aims to help the technology more accurately achieve its creator’s aims. Yet in UTTER Cheang passes no obvious judgments about AI. On the one hand, the piece suggests AI’s limits, showing its inability to account for Cheang’s true identity as a queer Asian woman. On the other, it posits AI’s liberation from its makers, offering moments when this self-portrait spits out its pacifier in rebellion. Cheang has cautioned that we may be entering into a “‘master’ and ‘slave’ relationship with AI.” UTTER imagines an end to that relationship altogether.

Charmaine Poh, GOOD MORNING YOUNG BODY , 2023

Before she became an artist, Charmaine Poh had a career as a child actress, appearing in the Singaporean TV show We Are R.E.M. in 2002, where she played a superhero named E-Ching. Two decades later, in 2023, Poh returned to footage from that series, using deepfake technology to reanimate her 12-year-old self for a new audience. This preteen Poh tells viewers that she was “written into existence” and that she was “created to fight crime before dinnertime.” As this AI version of Poh talks, small cracks in its speech are noticeable.

The actual Poh never had quite so much control over how she was seen and what purpose she served. Seeking to regain agency over her own image, she has now taken it into her own hands. “I thought, what is it like to speak back?” Poh told an interviewer. “At that time, I didn’t feel like I could, but now I can create a new superhero for myself.”

This article is part of our latest digital issue,  AI and the Art World . Follow along for more stories throughout this week and next.

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Feb 14, 2023

How to Write An Argumentative Essay (With Examples)

Are you looking for ways how to write an argumentative essay check out these helpful examples.

An argumentative essay is a writing genre that obligates the writer to examine a topic; collect, generate, and evaluate proof; and clearly present a perspective on the issue. It can be tricky to write, but with a little practice, they can become relatively easy.

To write an argumentative essay, it is important to always have a strong argument as your topic and should greatly rely on evidence and logic. However, there is a slight bit of wiggle room within your essay. For example, your thesis statement may include an opinion or a controversial idea, and while you should still support it with facts, it is possible to add your opinion to the essay without going against the objective of the essay.

If you want to create a high-quality argumentative essay, Jenni.ai is here for you! This AI-assistant writing software can easily help you with writing any kind of academic paper, including your argumentative essay.

Tips on how to make an Argumentative Essay

Creating an argumentative essay can be quite daunting, especially if you are not used to writing this kind of essay. However, there are some simple guidelines you can follow to ensure that your essay will be both coherent and convincing:

Make sure to choose a topic with strong talking points. This makes it easier to form strong coherent arguments that will dictate the direction you want to take with your essay.

Use the correct tone when creating your argumentative essay. People mistake assertiveness in argumentative essays to mean being aggressive and argumentative, which will not win you any points with your readers. Convincing arguments should be presented calmly and clearly in the introduction section of your essay, with supporting information being presented throughout the body of your essay.

Make sure to use factual statements when presenting your arguments. This is important if you are writing an academic essay as this ensures that your arguments are well-researched and thought out. Fact-based research is always more reliable than opinions.

Keep your arguments logical and concise. This will make it easy for your readers to follow your train of thought and helps to keep them engaged throughout the essay.

Make sure that you indicate all the relevant talking points in a clear and concise manner in your conclusion section.

Always make sure to proofread your work thoroughly throughout your writing process because typos and grammatical errors will greatly affect the quality and credibility of your work.

With these tips in mind, you are on your way to creating a high-quality argumentative essay that is easy to understand and will be compelling to your readers. 

How to create an Outline for your Argumentative Essay

As we already know, creating an argumentative essay involves a strong topic in order to create a strong argument. Creating an outline for it is a lot easier than most people think, especially for beginners. Here are some simple steps to create an argumentative essay:

1. Research your topic - As mentioned above, you will need to carry out in-depth research to find suitable evidence to back up your argument. If you know what you are going to write about before carrying out your research, then you will be able to structure it more easily. 

2. Introduction - In this part of your essay, you will want to introduce the reader to the topic that you will be discussing. The introductory paragraph works like a hook to entice your readers about your interesting topic. Make sure to create an introduction that is easy to understand so that your readers will be interested in reading. A good way to do this is by providing them with a brief background about the topic so that they understand it better.

3. Hypothesis or Premise - This is where you present your main arguments about your topic. You could provide questions to answer or evidence to support your claims. It will serve as the basis for the argument in your essay. Keep in mind that you will need to support all of your points with evidence from your research.

4. Body - Like any good argumentative essay, your body should contain all of the supporting evidence that you will use to support your argument. Each body paragraph should be dedicated to a different point that you would like to make. Body paragraphs cover different pieces of evidence that you provide to support your claims throughout the essay.

5. Conclusion - This is where you create a summary of all your talking points. This could also serve as a brief refresher of what you have discussed in the body of the essay. The conclusion is one of the most important parts of your essay because this is where you rebut the opposing arguments and remind your reader of the key points that you have discussed in the paper.

Types of Argumentative Essay

1. Rogerian Argumentative Essay - This type of essay is great for controversial topics because its creator, Carl Rogers intended this essay type to be as tame and respectful as possible.

The Rogerian style is centred around maintaining a balance between the two sides of the argument rather than siding with one opinion over the other. After both sides have been considered, a great way to end this essay is with a proper resolution of all the arguments presented. Usually, this results in finding a way to bring the two sides together rather than permanently sidelining one opinion over another.

This approach promotes both intellectual honesty and responsible thinking, which is a great way to approach an argumentative essay!

2. Classic Argumentative Essay - This type of argumentative essay entices the reader to a certain point of view.

This style is developed by Aristotle and it requires the reader to look at both sides of the argument while ultimately deciding which one is the most concise and factual. An essay like this requires a presentation of claims and counterarguments as well as an overall claim about the topic being argued over.

3. Toulmin Argumentative Essay - Arguments are broken down into multiple elements in order to prove a point. The main elements to follow with the Toulmin argumentative essay are the claim, grounds, warrant, qualifier, rebuttal, and backing.

The claim is the thesis that is being argued for, while the grounds are the arguments that back up the claim.

The warrant is the argument from which the claim can be proven; this can be based on historical data, social or cultural research, or scientific research.

The qualifier is the explanation that explains the basis on which the claim was made and the justification provided to justify the claim.

The rebuttal is the part where you respond to the claims that have been presented against your claim. This can be used to acknowledge an opposing viewpoint by proving your reasoning and logic are stronger or more logical than theirs.

And the backing is the part of your essay where you convince your reader to take a side in the argument.

The Toulmin argument is best used when there could be several possible solutions to a certain argument. This style is also very useful for debates and discussions because it allows both sides of an argument to be laid out for consideration.

Argumentative Essay Examples

Now that we've explained the different types of argumentative essays as well as useful tips you can use throughout your writing process, here are some excerpt examples of the different types of argumentative essays:

1. Is School Conductive to Learning? (Classical Argumentative Essay)

"If students get As on a test then they know the material, right? How many of those students would still know the information if you asked them about a week later? How about a month later? Most students will not remember most of the information for very long after the test. Why is that? They learned it, didn't they? Well, that depends on how you define "learning". "Learning" is gaining knowledge and experience which stays in the long-term memory and is of value to the recipient. So we have to ask, is our education system really teaching children?

The way education is set up in this country is simple. There is usually only one teacher in a classroom teaching from 12 to 30 students at a time. Information is written on a blackboard in the front of the room while the children take notes and listen. There may be some variation depending on the school and teacher. Then the students are tested on the material. After the test, the class moves on to new information. The material is usually not looked at again until a final test at the end of the semester, for which students study very hard a few days before. If they pass the test it is assumed that they "learned" the information, regardless of if they forget it later. Our education system is not only not enhancing learning but may actually be inhibiting it.

The education system in the United States today treats the minds of children like bowls to be filled with information. What it does not realize is that if you fill a bowl too quickly most of the liquid will bounce back out. It is the same with the mind of a child. When they are given too much information in such a small amount of time very little of it is actually retained. This is because of the vast amount of information students are given in very small amounts of time. Children study a single topic for two weeks to a month and then they are tested on it. After the test, they study something different for the next two weeks to a month. This causes the previous information to be forgotten and replaced by new information. This means that children end up with only very general knowledge of the topics studied.

A few children do learn this quickly, but not very many. Children learn at greatly varying paces, however, schools assume that all children learn at the same speed. This causes many children to be very frustrated and give up trying to learn. Many children who learn at a slower pace fall behind beyond any hope of catching up. Often the children who learn more quickly get bored and give up completely. Many of these children begin associating learning with boredom or frustration and actually start to dislike and even fight against learning.

Our system of schooling is not set up the way it should be. It was created to enhance learning, to teach children what they needed to know. It has strayed from that purpose. Our school system not only does not teach, but it turns students away from learning. Our children deserve better than this. They deserve to be shown how much fun and how beneficial learning can be. Learning can be what gives our lives value, but we are cheating our children of that. The school system needs to be seriously looked at and changed. The future of our world could be shaped by how well our children are prepared for it. They will be better prepared for it if they are shown how important and how rewarding knowledge and confidence can be. If our children are given these building blocks then they will become stronger adults and they will enhance the structure of the human world."

2. Helmets: Life or Liberty? (Rogerian Argumentative Essay)

"Snowboarding and snow skiing are two of the most enjoyed recreational sports in the world today. They give a unique sense of freedom and satisfaction that is unlike any other sport that can offer. Rob Reichenfeld remarked after his first lesson, “When you’re onto a good thing you stick with it, and like millions around the world I had discovered something undefinably special” (2). The freedom to carve down an entire mountain as fast or as slowly as desired, to drop off a twenty-foot cliff into five feet of fluff, to weave a line through a patch of technical trees, or to float down a steep face with bottomless powder is just a few reasons so many people are determined to make it to the mountains every year in search of a supreme rush. Snow sports provide an outlet for people to express themselves in unconventional ways by taking risks they normally would not take.

Snow sports are becoming more popular than ever before. They are prevalent in movies such as Extreme Days, Out Cold, several James Bond films, and Aspen Extreme, just to name a few. Now we see the X Games on television and snow sports in the Olympics. And the commercial market has taken full advantage of the extreme side of these sports as well. Mountain Dew has created an entire marketing scheme based solely on extreme sports, with snowboarding being a large part. Not only are snow sports becoming exceeding popular in the media, but more and more newcomers are also picking up a board or a set of skis every day of the winter season.

Along with all of this new popularity and thousands of new partakers in these sports, head injuries are becoming an increasing element of the equation. Although the percentage of head injuries due to snow sports is fairly low, about 0.3—6.5 skiers or snowboarders per thousand a day (“Heads you win?…”), a lot of people are affected when you consider how many thousands of people might be skiing or snowboarding in the entire U.S. on any given day. These numbers have raised a question of some magnitude: should ski resorts intrude on their guests’ individual liberties by implementing helmet rules?

Helmets do have several distinct drawbacks, despite their many benefits. Though opinions are starting to change, helmets are sometimes viewed as uncool or “nerdy”. These ideas are similar to those people used to have about motorcycle helmets, car seat belts, bicycle helmets, and skating elbow- and kneepads. Initially, it seems, any form of safety equipment gets a bad rap, especially from a young crowd that has no real concern for bodily harm.

The benefits of wearing head protection while resort skiing or snowboarding greatly outweigh the disadvantages, so such protective headgear should be required by all ski resorts. With the improvements being made in the comfort, stylishness, and effectiveness of helmets in the industry, there are no excuses left for skiers or boarders not to be wearing them. These types of resort rules could save countless lives as well as possibly save innumerable tax dollars that are spent on the medical costs of people who receive brain damage as a result of snow sport-induced head trauma. Such rules would also serve to lower lift ticket prices, as less money would be spent by resorts to defending against lawsuits brought on by head trauma victims. It would be to the benefit of everyone in the snow sports community if such regulations were to be put into place. I hope that they will indeed be applied in the near future, further insuring many more years of safe and exhilarating snow sporting."  

3. The Power of Black Panther (Toulmin)

  "Despite it just hitting theatres, Black Panther is already labelled as a ‘cultural movement’. Many Marvel fans eagerly waited to see the movie while discussions exploded on social media about Marvel’s new black superhero. However, not all of the discussions have stayed peaceful. With the emergence of this hero comes the emergence of the timeless debate of race, more specifically race in the media and how it is presented. There are some who say that having a black hero should not be this big of a deal and they deny the need for heroes of colour. Morals are colourless; we’ve learned from and enjoyed the millions of white heroes, so why is this black hero so special?

The issue here runs far deeper than this and goes beyond comic book characters. The real issue is the overall representation of minority groups in America. There needs to be a better representation of minorities in media to help the majority understand them and to help minorities feel a part of society. These are important factors in peace and unity within our nation. II. For the longest time, white men have dominated all American media industries, especially cishet men. Cishet refers to a person who is both cisgender and heterosexual. Over the years, women and minorities have fought to get where they are Background and issue questionClaimDefinitionDunne 2in the media today. They are now performing more and more roles outside of their stereotypes.

We need a more understanding majority and minorities who feel like they are an equal part of society, in order to come together and work for a better nation. Having fair media representation for minorities is a vital key to doing so. With the current hate destroying our country, we need to educate ourselves and each other. What better way to change a nation obsessed with its media, than with the media?" 

Creating argumentative essays is quite a complex process and there are multiple styles and ways to approach it. The goal of the process is to convince the audience of your point of view based on evidence or facts rather than personal opinions.

If you want to create high-quality argumentative essays, we recommend using Jenni.ai to speed up your writing process and help you craft more compelling arguments! You can sign up at Jenni.ai for free here !

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How to Write an Argumentative Essay- Steps with Examples

Being a student and writing essays is not something everybody enjoys, but in my personal opinion as a writer, anyone can find contentment and pleasure in writing, especially when it comes to argumentative essays. While they may seem tricky to navigate, they offer this unique opportunity to express your opinions and make your voice heard. Consider this a growing process—once you overcome the challenges of writing argumentative essays, you will learn the art of agreeing or disagreeing with popular opinions and defending your stance. As far as the essay is concerned, I will show you how to master this process on how to write an argumentative essay.

When is an Argumentative Essay Written?

You will likely be required to write argumentative essays throughout your academic life, from high school to university. These assignments will present opportunities to develop and showcase your critical thinking and persuasive writing skills. Here are some scenarios where you might encounter the need to write argumentative essays:

Academic Assignments

Often assigned in school or college courses to help students develop critical thinking and persuasive writing skills. These assignments encourage students to research thoroughly, form coherent arguments, and present their viewpoints convincingly.

Debates and Discussions

Serve as the basis for presenting and defending viewpoints in academic or competitive settings. Argumentative essays provide a structured way to organize thoughts and evidence, helping participants articulate their arguments effectively during debates.

Opinion Pieces

Commonly used in newspapers, magazines, and online publications to influence public opinion on current issues. These essays allow writers to present their stance on controversial topics, backed by evidence and reasoning, to sway readers' views.

Policy Proposals

Utilized in government and policy-related fields to propose and defend specific policy changes or solutions to societal problems. Argumentative essays in this context present well-researched arguments to persuade policymakers and stakeholders of the necessity and viability of the proposed changes.

Persuasive Speeches

Prepared as a foundation for delivering persuasive speeches. Writing an argumentative essay helps speakers organize their thoughts and evidence logically, providing a solid framework for their oral presentations.

What is the Structure of an Argumentative Essay?

An argumentative essay uses factual evidence and logical support to convince the reader of a particular point of view. Here's a breakdown of the structure and what goes into each part of an argumentative essay:

Basic Argumentative Essay Structure

1.Introduction

Purpose: Introduce the topic, present the thesis, and set up the argument.

Hook: A sentence to grab the reader’s attention.

Background Information: Brief context about the topic.

Thesis Statement: The main argument or claim.

2.Body Paragraphs

Purpose: Present arguments and evidence to support the thesis and refute opposing arguments.

Topic Sentence: Introduces the main idea of the paragraph.

Evidence and Analysis: Present facts, statistics, quotes, or examples to support the argument.

Counterarguments and Rebuttals: Address opposing views and explain why they are invalid or less significant.

3.Conclusion

Purpose: Summarize the arguments, restate the thesis in light of the evidence presented, and offer final thoughts.

Restate Thesis: Reiterate the main argument.

Summarize Key Points: Highlight the main points made in the body paragraphs.

Final Thought: A closing statement that underscores the importance of the topic

How to Write an Argumentative Essay [4 Steps with Examples]

As an experienced writer, I've come to understand the structure of argumentative essays quite well. But what I found truly challenging when I first started was nailing the right approach. Many beginners, myself included at one point, fall into traps like letting personal biases creep in or thinking that being argumentative means being aggressive. Trust me, that's not the case at all!

In this section, I'm going to lay out an effective approach on how to write an argumentative essay step by step for beginners. I'll break it down in a way that I wish someone had done for me when I was starting out. Plus, I'll share some insider tips on tools like WPS Office that I've come to rely on to streamline my writing process. So let's learn how to write an argumentative essay with a few examples.

1.Brainstorming

When I sit down to craft an argumentative essay, my first step is to engage in a comprehensive brainstorming session. This is your opportunity to let your creativity run wild and explore every angle of your topic. Write down every idea that comes to you, whether it supports or opposes your topic. Remember, at this stage, there are no bad ideas.

Now, while there's nothing wrong with the classic pen and paper approach, I've found that using WPS Office takes my brainstorming to a whole new level. It's not just about having a digital notepad; the AI features often toss out ideas that I might never have thought of on my own. It's like having a creative partner who never gets tired! Let me show you how I use it:

Let's say our topic is "Are Electric Cars Better for the Environment?"

Step 1: Open WPS Office and type "@AI" on a blank document to activate WPS AI.

Step 2: Click on the "Brainstorm" option and enter your prompt. Make sure it's detailed and clearly explains what you want. Here's an example of an effective prompt:

"Generate a list of arguments both for and against the idea that electric cars are better for the environment. Consider factors like emissions, manufacturing processes, battery disposal, and energy sources"

Step 3: WPS AI will generate several arguments on both sides. If you want more, simply click "Rewrite”.

Jot down any valuable arguments before hitting "Rewrite", as you might not see the same ones again.

With these arguments in hand, you'll likely find yourself leaning towards one side of the debate. Armed with a variety of points and counterpoints, you'll be well-equipped to write an effective argumentative essay. Remember, a strong argumentative essay is built on a foundation of thorough preparation and diverse ideas.

2.Preparing

Now that we've generated our initial arguments and counterarguments, it's time to dive deeper into research to strengthen our position. Let's continue with our example topic: "Are Electric Cars Better for the Environment?"

Let's continue with our example topic: "Are Electric Cars Better for the Environment?" Our next step is to select the most impactful supporting arguments and conduct in-depth research to substantiate them with solid evidence. Simultaneously, we'll identify the strongest counterarguments and explore ways to address or neutralize them through our research.

All of this might seem a little overwhelming, but with the help of WPS AI, the research phase becomes significantly more manageable. As we gather research papers, we can upload them to WPS Office and quickly gain insights using the AI features.

Here's how to leverage WPS AI for efficient research:

Step 1: Open your research paper PDFs in WPS Office, then click on the WPS AI widget in the top right corner.

Step 2: In the WPS AI panel that appears on the right side of your screen, click "Upload" to add your PDF.

Step 3: Once processed, WPS AI will provide you with key insights from the PDF at a glance.

Step 4: For more specific information, click on the "Inquiry" tab and use the WPS AI chatbot to ask further questions about the PDF contents.

As you conduct your research, begin organizing your findings into an outline. Remember to structure your outline according to the elements we discussed in previous sections. This will ensure your outline contains all the necessary components for an effective argumentative essay.

3.First Drafting

Now that we have our research and outline ready, it's time to start writing our first draft. This is where your essay really starts to take shape. Don't worry about perfection at this stage—the goal is to get your ideas down coherently.

Using the outline we prepared during our research, you'll find it easier to organize your thoughts for your essay. To make things simpler, use WPS Office editing tools. When I write my essay, I always ensure it is properly formatted, giving it a cleaner look and helping me focus better.

Now, simply start your draft on WPS Office with an introduction, followed by a body paragraph, and conclude with a strong summary that reviews your main points and leaves the reader with something to think about.

Once you have your draft ready, make use of WPS Office's AI features, which can help you improve writing, shorten or elongate your paragraphs, and much more. Let's say you've written your first body paragraph, and it's a bit too long. So, let's shorten it with WPS AI:

Step 1: Select the paragraph you want to shorten, then click on the WPS AI icon in the hover menu.

Step 2: From the list of options, simply click on "Make shorter" to shorten your paragraph.

Step 3: WPS AI will display the shorter version on a small screen. Click on "Replace" to replace the original text with the shorter version.

4.Revising & Proofreading

Congratulations on completing your first draft! However, there is one crucial step remaining: revising and proofreading.  Revising and proofreading are where good essays become great essays.

A method I find most effective for revising my essay is reading it aloud. This technique helps in identifying awkward phrasing and run-on sentences that may go unnoticed when reading silently. As you read, ask yourself:

Does my introduction effectively grab the reader's attention and clearly state my thesis?

Do my body paragraphs each focus on a single main idea that supports my thesis?

Have I provided enough evidence to support each of my arguments?

Have I addressed potential counterarguments?

Does my conclusion effectively summarize my main points and leave a lasting impression?

You might find that you need to make some structural changes. For instance, you might realize that your second body paragraph would be more effective if it came first. Don't be afraid to move things around!

Once you have made the necessary changes to your essay, the next step is to ensure it does not have any grammatical errors. For this, I use WPS AI's spell check feature. With just a single click, WPS AI spell check ensures that my essay is complete and ready to be submitted!

Bonus Tips: How to Polish your argumentative Essay with WPS AI

WPS Office is already a premium choice among students, offering all the features needed to write a perfect essay. With WPS Office, students can write better without payment issues, annoying ads, or difficulty navigating the tools. It's a free tool with advanced features, including WPS AI, which supports the entire writing process.

1.Check for Grammar and Spelling:

WPS AI carefully scans your essay for grammatical errors and spelling mistakes, ensuring that your writing is polished and professional. This feature not only helps you avoid common errors but also enhances the readability and credibility of your work.

2.Seek Style and Tone Adjustments:

WPS AI offers suggestions to improve the style and tone of your writing, making it more engaging and suitable for your target audience. Whether your essay requires a formal academic tone or a more conversational approach, WPS AI tailors its recommendations to fit your needs, ensuring your writing is coherent and compelling.

Here's an example of WPS AI's 'Improve Writing' feature in action, enhancing the formality and persuasiveness of my body paragraph for the reader.

3.Writing Assistance:

From the initial brainstorming phase to the final touches, WPS AI provides comprehensive writing assistance. It helps you structure your arguments logically, develop clear and concise thesis statements, and refine your conclusions. WPS AI also offers suggestions for enhancing clarity and coherence, making the writing process smoother and more efficient.

With the assistance of WPS AI's 'Continue Writing' feature, we can extend our essays by seamlessly incorporating additional sections that complement the existing content's flow and tone.

FAQs about Writing an Argumentative Essay

1. what’s the difference between an expository essay and an argumentative essay.

An argumentative essay is typically more extensive and requires independent research to establish a unique claim regarding a specific topic. It includes a thesis statement that presents a debatable assertion, which must be supported by objective evidence. In contrast, an expository essay strives for objectivity but does not propose an original argument. Instead, it aims to clarify and explain a topic straightforwardly, such as a process or concept. Generally, expository essays are shorter and do not rely as heavily on research.

2. When do I need to cite sources?

In a college environment, accurately citing sources is vital for essays, research papers, and other academic assignments, but this requirement does not extend to exams or in-class tasks. Proper citations are needed for direct quotes, paraphrased material, and summaries, and it is necessary to provide complete source information in a bibliography or reference list. Following the specified citation style, such as APA or MLA, is essential for maintaining academic integrity. Whenever you utilize information or ideas from another work in college-level writing, proper citation is required to acknowledge the original source.

3. What is an Argumentative essay?

An argumentative essay is a type of writing that asserts a specific stance on a debatable issue, backing it up with reasoning and evidence. The main objective is to convince the reader to accept or seriously consider the author's viewpoint. This essay usually contains a clear thesis statement and develops arguments while addressing opposing views to reinforce its position. Ultimately, it seeks to encourage critical engagement with the topic at hand.

Excel the Art of Persuasion With WPS Office

Argumentative essays are possibly the most thought-provoking when it comes to writing, presenting a higher difficulty level. Despite the challenge on how to write an argumentative essay, they are also the most fun to write, as they allow you to express your opinions in a highly opinionated form. WPS Office strives to enhance your writing experience, and as a writer, I can vouch for this. WPS Office not only offers advanced tools like WPS AI to help refine and improve your writing skills but also provides options to make your work as presentable as you want it to be. Download WPS Office today to experience the difference.

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Argumentative Essay Evaluator

Ai-powered evaluation of argumentative essays.

• Assess a student's essay: Evaluate the strength and coherence of a student's argumentative essay, providing detailed feedback to guide improvement.
• Improve your own writing: Submit your own argumentative essay for analysis to identify areas of strength and areas for improvement.
• Prepare for an exam: Use the tool to practice and improve your essay writing skills in preparation for an exam.
• Teaching tool: Educators can use this tool to provide comprehensive feedback to students, helping them understand how to improve their argumentative writing.

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• Citing Generative AI

Please see below for MLA guidelines on how to cite Generative AI (artificial intelligence) tools like ChatGPT, Dall-e, Grammarly, etc used for sources. 

General Rules

• Paraphrasing or Quoting from AI Text

AI-Generated Images

• AI Creative Textual Work
• Help Resources

See SEICAI Student Guide to Generative AI and your instructor's policy about the appropriate use of generative AI for any academic assignments.

Author:  None

Title:  Use the prompt you entered (in quotes) to generate the content followed by the word "prompt" (no quotes). 

Name of the AI Tool & Version:  The name of the AI tool will be in italics, followed by a comma, and the version of the AI not in italics  (examples: ChatGPT , version 3.5, or  AutoDraw , May 2017 version, etc.). If you cannot find a version for the AI, just list the AI tool.

Publisher:  Name of the Company who created the tool (OpenAI, Google, etc.).

Date:  Give the date you used the AI tool to generate the content. Dates should be in MLA Format (example: 15 Oct. 2024)

URL:  Give the general URL for the AI tool unless the AI provides a specific shareable link to the conversation/content (example: the tool DALL-E creates images and allows users to generate a publicly-available URL that leads back to that image).

Asking AI to Answer a Question or Prompt and Then Writing in Your Own Words (Paraphrasing)

You still need to give credit if you used material created from an AI tool, even if you put the information in your own words the same as you would paraphrasing from any source. 

Format:  "The prompt you entered to generate the content" plus the word prompt.  Name of A I Tool in Italics , Version, Publisher, Date, URL.

Example 1:  " What are some age appropriate lessons to teach sharing to children age 3 to 5"   prompt. Magic School AI,  Oct. version, Magic School, 3 Oct. 2024, www.magicschool.ai.

Example 2:  "What skills from the job ad should I highlight in my cover letter"   prompt. ChatGPT ,  version 3.5, OpenAI, 3 June 2024, chat.openai.com/chat.

When using an AI-generated image in your assignments, use a description of the prompt, followed by the AI tool, version, and date created, URL.  See our guide on  Citing Images or Graphs for more information about citing and using images in your project.

Format:  "The prompt you entered to generate the image" plus the word prompt.  Name of A I Tool in Italics , Version [if available], Publisher, Date, URL.

Example:  "10ft x 12ft garden with 3 Dwarf Palmetto shrubs" prompt. Canva,  Canva Inc., 23 Aug. 2024, www.canva.com/ai-image-generator/.

Asking AI to Create a Text like a Poem, Song, or Short Story

How you cite a creative text depends on if you told the AI tool a title for the text it created. 

Text with a Title 

Format:  “Title of Text" plus an explanation of the prompt.  Name of A I Tool in Italics , Version, Publisher, Date, URL.

Example:  “The Tale of Which Came First the Egg or the Chicken” a short story answering the riddle.  ChatGPT , version 3.5, OpenAI, 23 Sept. 2024, chat.openai.com/chat.

Text without a Title

If you did not tell the AI tool a title for the work, then you will use either all or part of the first line (depending on how long) as the title plus an explanation of the prompt.

Format:  “All or Part of First Line of Text" plus an explanation of the prompt.  Name of A I Tool in Italics , Version, Publisher, Date, URL.

Example:  “In 1920, Wilson wins reelection over Harding...” write a chapter about the outcome of the 1920 US presidential election if women did not get the right to vote.  ChatGPT , version 3.5, OpenAI,15 Nov. 2024, chat.openai.com/chat.

MLA Style Center

How do I cite generative AI in MLA style?

Grammarly 

How to Cite ChatGPT and AI in MLA Format

Purdue University 

How to Cite AI-Generated Content

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