Tag Archives: Ahmed Elgammal

True love with AI (artificial intelligence): The Nature of Things explores emotional and creative AI (long read)

The Canadian Broadcasting Corporation’s (CBC) science television series,The Nature of Things, which has been broadcast since November 1960, explored the world of emotional, empathic and creative artificial intelligence (AI) in a Friday, November 19, 2021 telecast titled, The Machine That Feels,

The Machine That Feels explores how artificial intelligence (AI) is catching up to us in ways once thought to be uniquely human: empathy, emotional intelligence and creativity.

As AI moves closer to replicating humans, it has the potential to reshape every aspect of our world – but most of us are unaware of what looms on the horizon.

Scientists see AI technology as an opportunity to address inequities and make a better, more connected world. But it also has the capacity to do the opposite: to stoke division and inequality and disconnect us from fellow humans. The Machine That Feels, from The Nature of Things, shows viewers what they need to know about a field that is advancing at a dizzying pace, often away from the public eye.

What does it mean when AI makes art? Can AI interpret and understand human emotions? How is it possible that AI creates sophisticated neural networks that mimic the human brain? The Machine That Feels investigates these questions, and more.

In Vienna, composer Walter Werzowa has — with the help of AI — completed Beethoven’s previously unfinished 10th symphony. By feeding data about Beethoven, his music, his style and the original scribbles on the 10th symphony into an algorithm, AI has created an entirely new piece of art.

In Atlanta, Dr. Ayanna Howard and her robotics lab at Georgia Tech are teaching robots how to interpret human emotions. Where others see problems, Howard sees opportunity: how AI can help fill gaps in education and health care systems. She believes we need a fundamental shift in how we perceive robots: let’s get humans and robots to work together to help others.

At Tufts University in Boston, a new type of biological robot has been created: the xenobot. The size of a grain of sand, xenobots are grown from frog heart and skin cells, and combined with the “mind” of a computer. Programmed with a specific task, they can move together to complete it. In the future, they could be used for environmental cleanup, digesting microplastics and targeted drug delivery (like releasing chemotherapy compounds directly into tumours).

The film includes interviews with global leaders, commentators and innovators from the AI field, including Geoff Hinton, Yoshua Bengio, Ray Kurzweil and Douglas Coupland, who highlight some of the innovative and cutting-edge AI technologies that are changing our world.

The Machine That Feels focuses on one central question: in the flourishing age of artificial intelligence, what does it mean to be human?

I’ll get back to that last bit, “… what does it mean to be human?” later.

There’s a lot to appreciate in this 44 min. programme. As you’d expect, there was a significant chunk of time devoted to research being done in the US but Poland and Japan also featured and Canadian content was substantive. A number of tricky topics were covered and transitions from one topic to the next were smooth.

In the end credits, I counted over 40 source materials from Getty Images, Google Canada, Gatebox, amongst others. It would have been interesting to find out which segments were produced by CBC.

David Suzuki’s (programme host) script was well written and his narration was enjoyable, engaging, and non-intrusive. That last quality is not always true of CBC hosts who can fall into the trap of overdramatizing the text.

Drilling down

I have followed artificial intelligence stories in a passive way (i.e., I don’t seek them out) for many years. Even so, there was a lot of material in the programme that was new to me.

For example, there was this love story (from the ‘I love her and see her as a real woman.’ Meet a man who ‘married’ an artificial intelligence hologram webpage on the CBC),

In the The Machine That Feels, a documentary from The Nature of Things, we meet Kondo Akihiko, a Tokyo resident who “married” a hologram of virtual pop singer Hatsune Miku using a certificate issued by Gatebox (the marriage isn’t recognized by the state, and Gatebox acknowledges the union goes “beyond dimensions”).

I found Akihiko to be quite moving when he described his relationship, which is not unique. It seems some 4,000 men have ‘wed’ their digital companions, you can read about that and more on the ‘I love her and see her as a real woman.’ Meet a man who ‘married’ an artificial intelligence hologram webpage.

What does it mean to be human?

Overall, this Nature of Things episode embraces certainty, which means the question of what it means to human is referenced rather than seriously discussed. An unanswerable philosophical question, the programme is ill-equipped to address it, especially since none of the commentators are philosophers or seem inclined to philosophize.

The programme presents AI as a juggernaut. Briefly mentioned is the notion that we need to make some decisions about how our juggernaut is developed and utilized. No one discusses how we go about making changes to systems that are already making critical decisions for us. (For more about AI and decision-making, see my February 28, 2017 posting and scroll down to the ‘Algorithms and big data’ subhead for Cathy O’Neil’s description of how important decisions that affect us are being made by AI systems. She is the author of the 2016 book, ‘Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy’; still a timely read.)

In fact, the programme’s tone is mostly one of breathless excitement. A few misgivings are expressed, e.g,, one woman who has an artificial ‘texting friend’ (Replika; a chatbot app) noted that it can ‘get into your head’ when she had a chat where her ‘friend’ told her that all of a woman’s worth is based on her body; she pushed back but intimated that someone more vulnerable could find that messaging difficult to deal with.

The sequence featuring Akihiko and his hologram ‘wife’ is followed by one suggesting that people might become more isolated and emotionally stunted as they interact with artificial friends. It should be noted, Akihiko’s wife is described as ‘perfect’. I gather perfection means that you are always understanding and have no needs of your own. She also seems to be about 18″ high.

Akihiko has obviously been asked about his ‘wife’ before as his answers are ready. They boil down to “there are many types of relationships” and there’s nothing wrong with that. It’s an intriguing thought which is not explored.

Also unexplored, these relationships could be said to resemble slavery. After all, you pay for these friends over which you have control. But perhaps that’s alright since AI friends don’t have consciousness. Or do they? In addition to not being able to answer the question, “what is it to be human?” we still can’t answer the question, “what is consciousness?”

AI and creativity

The Nature of Things team works fast. ‘Beethoven X – The AI Project’ had its first performance on October 9, 2021. (See my October 1, 2021 post ‘Finishing Beethoven’s unfinished 10th Symphony’ for more information from Ahmed Elgammal’s (Director of the Art & AI Lab at Rutgers University) technical perspective on the project.

Briefly, Beethoven died before completing his 10th symphony and a number of computer scientists, musicologists, AI, and musicians collaborated to finish the symphony.)

The one listener (Felix Mayer, music professor at the Technical University Munich) in the hall during a performance doesn’t consider the work to be a piece of music. He does have a point. Beethoven left some notes but this ’10th’ is at least partly mathematical guesswork. A set of probabilities where an algorithm chooses which note comes next based on probability.

There was another artist also represented in the programme. Puzzlingly, it was the still living Douglas Coupland. In my opinion, he’s better known as a visual artist than a writer (his Wikipedia entry lists him as a novelist first) but he has succeeded greatly in both fields.

What makes his inclusion in the Nature of Things ‘The Machine That Feels’ programme puzzling, is that it’s not clear how he worked with artificial intelligence in a collaborative fashion. Here’s a description of Coupland’s ‘AI’ project from a June 29, 2021 posting by Chris Henry on the Google Outreach blog (Note: Links have been removed),

… when the opportunity presented itself to explore how artificial intelligence (AI) inspires artistic expression — with the help of internationally renowned Canadian artist Douglas Coupland — the Google Research team jumped on it. This collaboration, with the support of Google Arts & Culture, culminated in a project called Slogans for the Class of 2030, which spotlights the experiences of the first generation of young people whose lives are fully intertwined with the existence of AI. 

This collaboration was brought to life by first introducing Coupland’s written work to a machine learning language model. Machine learning is a form of AI that provides computer systems the ability to automatically learn from data. In this case, Google research scientists tuned a machine learning algorithm with Coupland’s 30-year body of written work — more than a million words — so it would familiarize itself with the author’s unique style of writing. From there, curated general-public social media posts on selected topics were added to teach the algorithm how to craft short-form, topical statements. [emphases mine]

Once the algorithm was trained, the next step was to process and reassemble suggestions of text for Coupland to use as inspiration to create twenty-five Slogans for the Class of 2030. [emphasis mine]

I would comb through ‘data dumps’ where characters from one novel were speaking with those in other novels in ways that they might actually do. It felt like I was encountering a parallel universe Doug,” Coupland says. “And from these outputs, the statements you see here in this project appeared like gems. Did I write them? Yes. No. Could they have existed without me? No.” [emphases mine]

So, the algorithms crunched through Coupland’s word and social media texts to produce slogans, which Coupland then ‘combed through’ to pick out 25 slogans for the ‘Slogans For The Class of 2030’ project. (Note: In the programme, he says that he started a sentence and then the AI system completed that sentence with material gleaned from his own writings, which brings to Exquisite Corpse, a collaborative game for writers originated by the Surrealists, possibly as early as 1918.)

The ‘slogans’ project also reminds me of William S. Burroughs and the cut-up technique used in his work. From the William S. Burroughs Cut-up technique webpage on the Language is a Virus website (Thank you to Lake Rain Vajra for a very interesting website),

The cutup is a mechanical method of juxtaposition in which Burroughs literally cuts up passages of prose by himself and other writers and then pastes them back together at random. This literary version of the collage technique is also supplemented by literary use of other media. Burroughs transcribes taped cutups (several tapes spliced into each other), film cutups (montage), and mixed media experiments (results of combining tapes with television, movies, or actual events). Thus Burroughs’s use of cutups develops his juxtaposition technique to its logical conclusion as an experimental prose method, and he also makes use of all contemporary media, expanding his use of popular culture.

[Burroughs says] “All writing is in fact cut-ups. A collage of words read heard overheard. What else? Use of scissors renders the process explicit and subject to extension and variation. Clear classical prose can be composed entirely of rearranged cut-ups. Cutting and rearranging a page of written words introduces a new dimension into writing enabling the writer to turn images in cinematic variation. Images shift sense under the scissors smell images to sound sight to sound to kinesthetic. This is where Rimbaud was going with his color of vowels. And his “systematic derangement of the senses.” The place of mescaline hallucination: seeing colors tasting sounds smelling forms.

“The cut-ups can be applied to other fields than writing. Dr Neumann [emphasis mine] in his Theory of Games and Economic behavior introduces the cut-up method of random action into game and military strategy: assume that the worst has happened and act accordingly. … The cut-up method could be used to advantage in processing scientific data. [emphasis mine] How many discoveries have been made by accident? We cannot produce accidents to order. The cut-ups could add new dimension to films. Cut gambling scene in with a thousand gambling scenes all times and places. Cut back. Cut streets of the world. Cut and rearrange the word and image in films. There is no reason to accept a second-rate product when you can have the best. And the best is there for all. Poetry is for everyone . . .”

First, John von Neumann (1902 – 57) is a very important figure in the history of computing. From a February 25, 2017 John von Neumann and Modern Computer Architecture essay on the ncLab website, “… he invented the computer architecture that we use today.”

Here’s Burroughs on the history of writers and cutups (thank you to QUEDEAR for posting this clip),

You can hear Burroughs talk about the technique and how he started using it in 1959.

There is no explanation from Coupland as to how his project differs substantively from Burroughs’ cut-ups or a session of Exquisite Corpse. The use of a computer programme to crunch through data and give output doesn’t seem all that exciting. *(More about computers and chatbots at end of posting).* It’s hard to know if this was an interview situation where he wasn’t asked the question or if the editors decided against including it.

Kazuo Ishiguro?

Given that Ishiguro’s 2021 book (Klara and the Sun) is focused on an artificial friend and raises the question of ‘what does it mean to be human’, as well as the related question, ‘what is the nature of consciousness’, it would have been interesting to hear from him. He spent a fair amount of time looking into research on machine learning in preparation for his book. Maybe he was too busy?

AI and emotions

The work being done by Georgia Tech’s Dr. Ayanna Howard and her robotics lab is fascinating. They are teaching robots how to interpret human emotions. The segment which features researchers teaching and interacting with robots, Pepper and Salt, also touches on AI and bias.

Watching two African American researchers talk about the ways in which AI is unable to read emotions on ‘black’ faces as accurately as ‘white’ faces is quite compelling. It also reinforces the uneasiness you might feel after the ‘Replika’ segment where an artificial friend informs a woman that her only worth is her body.

(Interestingly, Pepper and Salt are produced by Softbank Robotics, part of Softbank, a multinational Japanese conglomerate, [see a June 28, 2021 article by Ian Carlos Campbell for The Verge] whose entire management team is male according to their About page.)

While Howard is very hopeful about the possibilities of a machine that can read emotions, she doesn’t explore (on camera) any means for pushing back against bias other than training AI by using more black faces to help them learn. Perhaps more representative management and coding teams in technology companies?

While the programme largely focused on AI as an algorithm on a computer, robots can be enabled by AI (as can be seen in the segment with Dr. Howard).

My February 14, 2019 posting features research with a completely different approach to emotions and machines,

“I’ve always felt that robots shouldn’t just be modeled after humans [emphasis mine] or be copies of humans,” he [Guy Hoffman, assistant professor at Cornell University)] said. “We have a lot of interesting relationships with other species. Robots could be thought of as one of those ‘other species,’ not trying to copy what we do but interacting with us with their own language, tapping into our own instincts.”

[from a July 16, 2018 Cornell University news release on EurekAlert]

This brings the question back to, what is consciousness?

What scientists aren’t taught

Dr. Howard notes that scientists are not taught to consider the implications of their work. Her comment reminded me of a question I was asked many years ago after a presentation, it concerned whether or not science had any morality. (I said, no.)

My reply angered an audience member (a visual artist who was working with scientists at the time) as she took it personally and started defending scientists as good people who care and have morals and values. She failed to understand that the way in which we teach science conforms to a notion that somewhere there are scientific facts which are neutral and objective. Society and its values are irrelevant in the face of the larger ‘scientific truth’ and, as a consequence, you don’t need to teach or discuss how your values or morals affect that truth or what the social implications of your work might be.

Science is practiced without much if any thought to values. By contrast, there is the medical injunction, “Do no harm,” which suggests to me that someone recognized competing values. E.g., If your important and worthwhile research is harming people, you should ‘do no harm’.

The experts, the connections, and the Canadian content

It’s been a while since I’ve seen Ray Kurzweil mentioned but he seems to be getting more attention these days. (See this November 16, 2021 posting by Jonny Thomson titled, “The Singularity: When will we all become super-humans? Are we really only a moment away from “The Singularity,” a technological epoch that will usher in a new era in human evolution?” on The Big Think for more). Note: I will have a little more about evolution later in this post.

Interestingly, Kurzweil is employed by Google these days (see his Wikipedia entry, the column to the right). So is Geoffrey Hinton, another one of the experts in the programme (see Hinton’s Wikipedia entry, the column to the right, under Institutions).

I’m not sure about Yoshu Bengio’s relationship with Google but he’s a professor at the Université de Montréal, and he’s the Scientific Director for Mila ((Quebec’s Artificial Intelligence research institute)) & IVADO (Institut de valorisation des données), Note: IVADO is not particularly relevant to what’s being discussed in this post.

As for Mila, the Canada Google blog in a November 21, 2016 posting notes a $4.5M grant to the institution,

Google invests $4.5 Million in Montreal AI Research

A new grant from Google for the Montreal Institute for Learning Algorithms (MILA) will fund seven faculty across a number of Montreal institutions and will help tackle some of the biggest challenges in machine learning and AI, including applications in the realm of systems that can understand and generate natural language. In other words, better understand a fan’s enthusiasm for Les Canadien [sic].

Google is expanding its academic support of deep learning at MILA, renewing Yoshua Bengio’s Focused Research Award and offering Focused Research Awards to MILA faculty at University of Montreal and McGill University:

Google reaffirmed their commitment to Mila in 2020 with a grant worth almost $4M (from a November 13, 2020 posting on the Mila website, Note: A link has been removed),

Google Canada announced today [November 13, 2020] that it will be renewing its funding of Mila – Quebec Artificial Intelligence Institute, with a generous pledge of nearly $4M over a three-year period. Google previously invested $4.5M US in 2016, enabling Mila to grow from 25 to 519 researchers.

In a piece written for Google’s Official Canada Blog, Yoshua Bengio, Mila Scientific Director, says that this year marked a “watershed moment for the Canadian AI community,” as the COVID-19 pandemic created unprecedented challenges that demanded rapid innovation and increased interdisciplinary collaboration between researchers in Canada and around the world.

COVID-19 has changed the world forever and many industries, from healthcare to retail, will need to adapt to thrive in our ‘new normal.’ As we look to the future and how priorities will shift, it is clear that AI is no longer an emerging technology but a useful tool that can serve to solve world problems. Google Canada recognizes not only this opportunity but the important task at hand and I’m thrilled they have reconfirmed their support of Mila with an additional $3,95 million funding grant until 22.

– Yoshua Bengio, for Google’s Official Canada Blog

Interesting, eh? Of course, Douglas Coupland is working with Google, presumably for money, and that would connect over 50% of the Canadian content (Douglas Coupland, Yoshua Bengio, and Geoffrey Hinton; Kurzweil is an American) in the programme to Google.

My hat’s off to Google’s marketing communications and public relations teams.

Anthony Morgan of Science Everywhere also provided some Canadian content. His LinkedIn profile indicates that he’s working on a PhD in molecular science, which is described this way, “My work explores the characteristics of learning environments, that support critical thinking and the relationship between critical thinking and wisdom.”

Morgan is also the founder and creative director of Science Everywhere, from his LinkedIn profile, “An events & media company supporting knowledge mobilization, community engagement, entrepreneurship and critical thinking. We build social tools for better thinking.”

There is this from his LinkedIn profile,

I develop, create and host engaging live experiences & media to foster critical thinking.

I’ve spent my 15+ years studying and working in psychology and science communication, thinking deeply about the most common individual and societal barriers to critical thinking. As an entrepreneur, I lead a team to create, develop and deploy cultural tools designed to address those barriers. As a researcher I study what we can do to reduce polarization around science.

There’s a lot more to Morgan (do look him up; he has connections to the CBC and other media outlets). The difficulty is: why was he chosen to talk about artificial intelligence and emotions and creativity when he doesn’t seem to know much about the topic? He does mention GPT-3, an AI programming language. He seems to be acting as an advocate for AI although he offers this bit of almost cautionary wisdom, “… algorithms are sets of instructions.” (You can can find out more about it in my April 27, 2021 posting. There’s also this November 26, 2021 posting [The Inherent Limitations of GPT-3] by Andrey Kurenkov, a PhD student with the Stanford [University] Vision and Learning Lab.)

Most of the cautionary commentary comes from Luke Stark, assistant professor at Western [Ontario] University’s Faculty of Information and Media Studies. He’s the one who mentions stunted emotional growth.

Before moving on, there is another set of connections through the Pan-Canadian Artificial Intelligence Strategy, a Canadian government science funding initiative announced in the 2017 federal budget. The funds allocated to the strategy are administered by the Canadian Institute for Advanced Research (CIFAR). Yoshua Bengio through Mila is associated with the strategy and CIFAR, as is Geoffrey Hinton through his position as Chief Scientific Advisor for the Vector Institute.

Evolution

Getting back to “The Singularity: When will we all become super-humans? Are we really only a moment away from “The Singularity,” a technological epoch that will usher in a new era in human evolution?” Xenobots point in a disconcerting (for some of us) evolutionary direction.

I featured the work, which is being done at Tufts University in the US, in my June 21, 2021 posting, which includes an embedded video,

From a March 31, 2021 news item on ScienceDaily,

Last year, a team of biologists and computer scientists from Tufts University and the University of Vermont (UVM) created novel, tiny self-healing biological machines from frog cells called “Xenobots” that could move around, push a payload, and even exhibit collective behavior in the presence of a swarm of other Xenobots.

Get ready for Xenobots 2.0.

Also from an excerpt in the posting, the team has “created life forms that self-assemble a body from single cells, do not require muscle cells to move, and even demonstrate the capability of recordable memory.”

Memory is key to intelligence and this work introduces the notion of ‘living’ robots which leads to questioning what constitutes life. ‘The Machine That Feels’ is already grappling with far too many questions to address this development but introducing the research here might have laid the groundwork for the next episode, The New Human, telecast on November 26, 2021,

While no one can be certain what will happen, evolutionary biologists and statisticians are observing trends that could mean our future feet only have four toes (so long, pinky toe) or our faces may have new combinations of features. The new humans might be much taller than their parents or grandparents, or have darker hair and eyes.

And while evolution takes a lot of time, we might not have to wait too long for a new version of ourselves.

Technology is redesigning the way we look and function — at a much faster pace than evolution. We are merging with technology more than ever before: our bodies may now have implanted chips, smart limbs, exoskeletons and 3D-printed organs. A revolutionary gene editing technique has given us the power to take evolution into our own hands and alter our own DNA. How long will it be before we are designing our children?

As the story about the xenobots doesn’t say, we could also take the evolution of another species into our hands.

David Suzuki, where are you?

Our programme host, David Suzuki surprised me. I thought that as an environmentalist he’d point out that the huge amounts of computing power needed for artificial intelligence as mentioned in the programme, constitutes an environmental issue. I also would have expected a geneticist like Suzuki might have some concerns with regard to xenobots but perhaps that’s being saved for the next episode (The New Human) of the Nature of Things.

Artificial stupidity

Thanks to Will Knight for introducing me to the term ‘artificial stupidity’. Knight, a senior writer covers artificial intelligence for WIRED magazine. According to its Wikipedia entry,

Artificial stupidity is commonly used as a humorous opposite of the term artificial intelligence (AI), often as a derogatory reference to the inability of AI technology to adequately perform its tasks.[1] However, within the field of computer science, artificial stupidity is also used to refer to a technique of “dumbing down” computer programs in order to deliberately introduce errors in their responses.

Knight was using the term in its humorous, derogatory form.

Finally

The episode certainly got me thinking if not quite in the way producers might have hoped. ‘The Machine That Feels’ is a glossy, pretty well researched piece of infotainment.

To be blunt, I like and have no problems with infotainment but it can be seductive. I found it easier to remember the artificial friends, wife, xenobots, and symphony than the critiques and concerns.

Hopefully, ‘The Machine That Feels’ stimulates more interest in some very important topics. If you missed the telecast, you can catch the episode here.

For anyone curious about predictive policing, which was mentioned in the Ayanna Howard segment, see my November 23, 2017 posting about Vancouver’s plunge into AI and car theft.

*ETA December 6, 2021: One of the first ‘chatterbots’ was ELIZA, a computer programme developed from1964 to 1966. The most famous ELIZA script was DOCTOR, where the programme simulated a therapist. Many early users believed ELIZA understood and could respond as a human would despite Joseph Weizenbaum’s (creator of the programme) insistence otherwise.

Finishing Beethoven’s unfinished 10th Symphony

Throughout the project, Beethoven’s genius loomed. Circe Denyer

This is an artificial intelligence (AI) story set to music. Professor Ahmed Elgammal (Director of the Art & AI Lab at Rutgers University located in New Jersey, US) has a September 24, 2021 essay posted on The Conversation (and, then, in the Smithsonian Magazine online) describing the AI project and upcoming album release and performance (Note: A link has been removed),

When Ludwig van Beethoven died in 1827, he was three years removed from the completion of his Ninth Symphony, a work heralded by many as his magnum opus. He had started work on his 10th Symphony but, due to deteriorating health, wasn’t able to make much headway: All he left behind were some musical sketches.

A full recording of Beethoven’s 10th Symphony is set to be released on Oct. 9, 2021, the same day as the world premiere performance scheduled to take place in Bonn, Germany – the culmination of a two-year-plus effort.

These excerpts from the Elgammal’s September 24, 2021 essay on the The Conversation provide a summarized view of events. By the way, this isn’t the first time an attempt has been made to finish Beethoven’s 10th Symphony (Note: Links have been removed),

Around 1817, the Royal Philharmonic Society in London commissioned Beethoven to write his Ninth and 10th symphonies. Written for an orchestra, symphonies often contain four movements: the first is performed at a fast tempo, the second at a slower one, the third at a medium or fast tempo, and the last at a fast tempo.

Beethoven completed his Ninth Symphony in 1824, which concludes with the timeless “Ode to Joy.”

But when it came to the 10th Symphony, Beethoven didn’t leave much behind, other than some musical notes and a handful of ideas he had jotted down.

There have been some past attempts to reconstruct parts of Beethoven’s 10th Symphony. Most famously, in 1988, musicologist Barry Cooper ventured to complete the first and second movements. He wove together 250 bars of music from the sketches to create what was, in his view, a production of the first movement that was faithful to Beethoven’s vision.

Yet the sparseness of Beethoven’s sketches made it impossible for symphony experts to go beyond that first movement.

In early 2019, Dr. Matthias Röder, the director of the Karajan Institute, an organization in Salzburg, Austria, that promotes music technology, contacted me. He explained that he was putting together a team to complete Beethoven’s 10th Symphony in celebration of the composer’s 250th birthday. Aware of my work on AI-generated art, he wanted to know if AI would be able to help fill in the blanks left by Beethoven.

Röder then compiled a team that included Austrian composer Walter Werzowa. Famous for writing Intel’s signature bong jingle, Werzowa was tasked with putting together a new kind of composition that would integrate what Beethoven left behind with what the AI would generate. Mark Gotham, a computational music expert, led the effort to transcribe Beethoven’s sketches and process his entire body of work so the AI could be properly trained.

The team also included Robert Levin, a musicologist at Harvard University who also happens to be an incredible pianist. Levin had previously finished a number of incomplete 18th-century works by Mozart and Johann Sebastian Bach.

… We didn’t have a machine that we could feed sketches to, push a button and have it spit out a symphony. Most AI available at the time couldn’t continue an uncompleted piece of music beyond a few additional seconds.

We would need to push the boundaries of what creative AI could do by teaching the machine Beethoven’s creative process – how he would take a few bars of music and painstakingly develop them into stirring symphonies, quartets and sonatas.

Here’s Elgammal’s description of the difficulties from an AI perspective, from the September 24, 2021 essay (Note: Links have been removed),

First, and most fundamentally, we needed to figure out how to take a short phrase, or even just a motif, and use it to develop a longer, more complicated musical structure, just as Beethoven would have done. For example, the machine had to learn how Beethoven constructed the Fifth Symphony out of a basic four-note motif.

Next, because the continuation of a phrase also needs to follow a certain musical form, whether it’s a scherzo, trio or fugue, the AI needed to learn Beethoven’s process for developing these forms.

The to-do list grew: We had to teach the AI how to take a melodic line and harmonize it. The AI needed to learn how to bridge two sections of music together. And we realized the AI had to be able to compose a coda, which is a segment that brings a section of a piece of music to its conclusion.

Finally, once we had a full composition, the AI was going to have to figure out how to orchestrate it, which involves assigning different instruments for different parts.

And it had to pull off these tasks in the way Beethoven might do so.

The team tested its work, from the September 24, 2021 essay, Note: A link has been removed,

In November 2019, the team met in person again – this time, in Bonn, at the Beethoven House Museum, where the composer was born and raised.

This meeting was the litmus test for determining whether AI could complete this project. We printed musical scores that had been developed by AI and built off the sketches from Beethoven’s 10th. A pianist performed in a small concert hall in the museum before a group of journalists, music scholars and Beethoven experts.

We challenged the audience to determine where Beethoven’s phrases ended and where the AI extrapolation began. They couldn’t.

A few days later, one of these AI-generated scores was played by a string quartet in a news conference. Only those who intimately knew Beethoven’s sketches for the 10th Symphony could determine when the AI-generated parts came in.

The success of these tests told us we were on the right track. But these were just a couple of minutes of music. There was still much more work to do.

There is a preview of the finished 10th symphony,

Beethoven X: The AI Project: III Scherzo. Allegro – Trio (Official Video) | Beethoven Orchestra Bonn

Modern Recordings / BMG present as a foretaste of the album “Beethoven X – The AI Project” (release: 8.10.) the edit of the 3rd movement “Scherzo. Allegro – Trio” as a classical music video. Listen now: https://lnk.to/BeethovenX-Scherzo

Album pre-order link: https://lnk.to/BeethovenX

The Beethoven Orchestra Bonn performing with Dirk Kaftan and Walter Werzowa a great recording of world-premiere Beethoven pieces. Developed by AI and music scientists as well as composers, Beethoven’s once unfinished 10th symphony now surprises with beautiful Beethoven-like harmonics and dynamics.

For anyone who’d like to hear the October 9, 2021 performance, Sharon Kelly included some details in her August 16, 2021 article for DiscoverMusic,

The world premiere of Beethoven’s 10th Symphony on 9 October 2021 at the Telekom Forum in Bonn, performed by the Beethoven Orchestra Bonn conducted by Dirk Kaftan, will be broadcast live and free of charge on MagentaMusik 360.

Sadly, the time is not listed but MagentaMusik 360 is fairly easy to find online.

You can find out more about Professor Elgammal on his Rutgers University profile page. Elgammal has graced this blog before in an August 16, 2019 posting “AI (artificial intelligence) artist got a show at a New York City art gallery“. He’s mentioned in an excerpt about 20% of the way down the page,

Ahmed Elgammal thinks AI art can be much more than that. A Rutgers University professor of computer science, Elgammal runs an art-and-artificial-intelligence lab, where he and his colleagues develop technologies that try to understand and generate new “art” (the scare quotes are Elgammal’s) with AI—not just credible copies of existing work, like GANs do. “That’s not art, that’s just repainting,” Elgammal says of GAN-made images. “It’s what a bad artist would do.”

Elgammal calls his approach a “creative adversarial network,” or CAN. It swaps a GAN’s discerner—the part that ensures similarity—for one that introduces novelty instead. The system amounts to a theory of how art evolves: through small alterations to a known style that produce a new one. That’s a convenient take, given that any machine-learning technique has to base its work on a specific training set.

Finally, thank you to @winsontang whose tweet led me to this story.

AI (artificial intelligence) artist got a show at a New York City art gallery

AI artists first hit my radar in August 2018 when Christie’s Auction House advertised an art auction of a ‘painting’ by an algorithm (artificial intelligence). There’s more in my August 31, 2018 posting but, briefly, a French art collective, Obvious, submitted a painting, “Portrait of Edmond de Belamy,” that was created by an artificial intelligence agent to be sold for an estimated to $7000 – $10,000. They weren’t even close. According to Ian Bogost’s March 6, 2019 article for The Atlantic, the painting sold for $432,500 In October 2018.

It has also, Bogost notes in his article, occasioned an art show (Note: Links have been removed),

… part of “Faceless Portraits Transcending Time,” an exhibition of prints recently shown [Februay 13 – March 5, 2019] at the HG Contemporary gallery in Chelsea, the epicenter of New York’s contemporary-art world. All of them were created by a computer.

The catalog calls the show a “collaboration between an artificial intelligence named AICAN and its creator, Dr. Ahmed Elgammal,” a move meant to spotlight, and anthropomorphize, the machine-learning algorithm that did most of the work. According to HG Contemporary, it’s the first solo gallery exhibit devoted to an AI artist.

If they hadn’t found each other in the New York art scene, the players involved could have met on a Spike Jonze film set: a computer scientist commanding five-figure print sales from software that generates inkjet-printed images; a former hotel-chain financial analyst turned Chelsea techno-gallerist with apparent ties to fine-arts nobility; a venture capitalist with two doctoral degrees in biomedical informatics; and an art consultant who put the whole thing together, A-Team–style, after a chance encounter at a blockchain conference. Together, they hope to reinvent visual art, or at least to cash in on machine-learning hype along the way.

The show in New York City, “Faceless Portraits …,” exhibited work by an artificially intelligent artist-agent (I’m creating a new term to suit my purposes) that’s different than the one used by Obvious to create “Portrait of Edmond de Belamy,” As noted earlier, it sold for a lot of money (Note: Links have been removed),

Bystanders in and out of the art world were shocked. The print had never been shown in galleries or exhibitions before coming to market at auction, a channel usually reserved for established work. The winning bid was made anonymously by telephone, raising some eyebrows; art auctions can invite price manipulation. It was created by a computer program that generates new images based on patterns in a body of existing work, whose features the AI “learns.” What’s more, the artists who trained and generated the work, the French collective Obvious, hadn’t even written the algorithm or the training set. They just downloaded them, made some tweaks, and sent the results to market.

“We are the people who decided to do this,” the Obvious member Pierre Fautrel said in response to the criticism, “who decided to print it on canvas, sign it as a mathematical formula, put it in a gold frame.” A century after Marcel Duchamp made a urinal into art [emphasis mine] by putting it in a gallery, not much has changed, with or without computers. As Andy Warhol famously said, “Art is what you can get away with.”

A bit of a segue here, there is a controversy as to whether or not that ‘urinal art’, also known as, The Fountain, should be attributed to Duchamp as noted in my January 23, 2019 posting titled ‘Baroness Elsa von Freytag-Loringhoven, Marcel Duchamp, and the Fountain’.

Getting back to the main action, Bogost goes on to describe the technologies underlying the two different AI artist-agents (Note: Links have been removed),

… Using a computer is hardly enough anymore; today’s machines offer all kinds of ways to generate images that can be output, framed, displayed, and sold—from digital photography to artificial intelligence. Recently, the fashionable choice has become generative adversarial networks, or GANs, the technology that created Portrait of Edmond de Belamy. Like other machine-learning methods, GANs use a sample set—in this case, art, or at least images of it—to deduce patterns, and then they use that knowledge to create new pieces. A typical Renaissance portrait, for example, might be composed as a bust or three-quarter view of a subject. The computer may have no idea what a bust is, but if it sees enough of them, it might learn the pattern and try to replicate it in an image.

GANs use two neural nets (a way of processing information modeled after the human brain) to produce images: a “generator” and a “discerner.” The generator produces new outputs—images, in the case of visual art—and the discerner tests them against the training set to make sure they comply with whatever patterns the computer has gleaned from that data. The quality or usefulness of the results depends largely on having a well-trained system, which is difficult.

That’s why folks in the know were upset by the Edmond de Belamy auction. The image was created by an algorithm the artists didn’t write, trained on an “Old Masters” image set they also didn’t create. The art world is no stranger to trend and bluster driving attention, but the brave new world of AI painting appeared to be just more found art, the machine-learning equivalent of a urinal on a plinth.

Ahmed Elgammal thinks AI art can be much more than that. A Rutgers University professor of computer science, Elgammal runs an art-and-artificial-intelligence lab, where he and his colleagues develop technologies that try to understand and generate new “art” (the scare quotes are Elgammal’s) with AI—not just credible copies of existing work, like GANs do. “That’s not art, that’s just repainting,” Elgammal says of GAN-made images. “It’s what a bad artist would do.”

Elgammal calls his approach a “creative adversarial network,” or CAN. It swaps a GAN’s discerner—the part that ensures similarity—for one that introduces novelty instead. The system amounts to a theory of how art evolves: through small alterations to a known style that produce a new one. That’s a convenient take, given that any machine-learning technique has to base its work on a specific training set.

The results are striking and strange, although calling them a new artistic style might be a stretch. They’re more like credible takes on visual abstraction. The images in the show, which were produced based on training sets of Renaissance portraits and skulls, are more figurative, and fairly disturbing. Their gallery placards name them dukes, earls, queens, and the like, although they depict no actual people—instead, human-like figures, their features smeared and contorted yet still legible as portraiture. Faceless Portrait of a Merchant, for example, depicts a torso that might also read as the front legs and rear haunches of a hound. Atop it, a fleshy orb comes across as a head. The whole scene is rippled by the machine-learning algorithm, in the way of so many computer-generated artworks.

Faceless Portrait of a Merchant, one of the AI portraits produced by Ahmed Elgammal and AICAN. (Artrendex Inc.) [downloaded from https://www.theatlantic.com/technology/archive/2019/03/ai-created-art-invades-chelsea-gallery-scene/584134/]

Bogost consults an expert on portraiture for a discussion about the particularities of portraiture and the shortcomings one might expect of an AI artist-agent (Note: A link has been removed),

“You can’t really pick a form of painting that’s more charged with cultural meaning than portraiture,” John Sharp, an art historian trained in 15th-century Italian painting and the director of the M.F.A. program in design and technology at Parsons School of Design, told me. The portrait isn’t just a style, it’s also a host for symbolism. “For example, men might be shown with an open book to show how they are in dialogue with that material; or a writing implement, to suggest authority; or a weapon, to evince power.” Take Portrait of a Youth Holding an Arrow, an early-16th-century Boltraffio portrait that helped train the AICAN database for the show. The painting depicts a young man, believed to be the Bolognese poet Girolamo Casio, holding an arrow at an angle in his fingers and across his chest. It doubles as both weapon and quill, a potent symbol of poetry and aristocracy alike. Along with the arrow, the laurels in Casio’s hair are emblems of Apollo, the god of both poetry and archery.

A neural net couldn’t infer anything about the particular symbolic trappings of the Renaissance or antiquity—unless it was taught to, and that wouldn’t happen just by showing it lots of portraits. For Sharp and other critics of computer-generated art, the result betrays an unforgivable ignorance about the supposed influence of the source material.

But for the purposes of the show, the appeal to the Renaissance might be mostly a foil, a way to yoke a hip, new technology to traditional painting in order to imbue it with the gravity of history: not only a Chelsea gallery show, but also an homage to the portraiture found at the Met. To reinforce a connection to the cradle of European art, some of the images are presented in elaborate frames, a decision the gallerist, Philippe Hoerle-Guggenheim (yes, that Guggenheim; he says the relation is “distant”) [the Guggenheim is strongly associated with the visual arts by way the two Guggeheim museums, one in New York City and the other in Bilbao, Portugal], told me he insisted upon. Meanwhile, the technical method makes its way onto the gallery placards in an official-sounding way—“Creative Adversarial Network print.” But both sets of inspirations, machine-learning and Renaissance portraiture, get limited billing and zero explanation at the show. That was deliberate, Hoerle-Guggenheim said. He’s betting that the simple existence of a visually arresting AI painting will be enough to draw interest—and buyers. It would turn out to be a good bet.

The art market is just that: a market. Some of the most renowned names in art today, from Damien Hirst to Banksy, trade in the trade of art as much as—and perhaps even more than—in the production of images, objects, and aesthetics. No artist today can avoid entering that fray, Elgammal included. “Is he an artist?” Hoerle-Guggenheim asked himself of the computer scientist. “Now that he’s in this context, he must be.” But is that enough? In Sharp’s estimation, “Faceless Portraits Transcending Time” is a tech demo more than a deliberate oeuvre, even compared to the machine-learning-driven work of his design-and-technology M.F.A. students, who self-identify as artists first.

Judged as Banksy or Hirst might be, Elgammal’s most art-worthy work might be the Artrendex start-up itself, not the pigment-print portraits that its technology has output. Elgammal doesn’t treat his commercial venture like a secret, but he also doesn’t surface it as a beneficiary of his supposedly earnest solo gallery show. He’s argued that AI-made images constitute a kind of conceptual art, but conceptualists tend to privilege process over product or to make the process as visible as the product.

Hoerle-Guggenheim worked as a financial analyst for Hyatt before getting into the art business via some kind of consulting deal (he responded cryptically when I pressed him for details). …

This is a fascinating article and I have one last excerpt, which poses this question, is an AI artist-agent a collaborator or a medium? There ‘s also speculation about how AI artist-agents might impact the business of art (Note: Links have been removed),

… it’s odd to list AICAN as a collaborator—painters credit pigment as a medium, not as a partner. Even the most committed digital artists don’t present the tools of their own inventions that way; when they do, it’s only after years, or even decades, of ongoing use and refinement.

But Elgammal insists that the move is justified because the machine produces unexpected results. “A camera is a tool—a mechanical device—but it’s not creative,” he said. “Using a tool is an unfair term for AICAN. It’s the first time in history that a tool has had some kind of creativity, that it can surprise you.” Casey Reas, a digital artist who co-designed the popular visual-arts-oriented coding platform Processing, which he uses to create some of his fine art, isn’t convinced. “The artist should claim responsibility over the work rather than to cede that agency to the tool or the system they create,” he told me.

Elgammal’s financial interest in AICAN might explain his insistence on foregrounding its role. Unlike a specialized print-making technique or even the Processing coding environment, AICAN isn’t just a device that Elgammal created. It’s also a commercial enterprise.

Elgammal has already spun off a company, Artrendex, that provides “artificial-intelligence innovations for the art market.” One of them offers provenance authentication for artworks; another can suggest works a viewer or collector might appreciate based on an existing collection; another, a system for cataloging images by visual properties and not just by metadata, has been licensed by the Barnes Foundation to drive its collection-browsing website.

The company’s plans are more ambitious than recommendations and fancy online catalogs. When presenting on a panel about the uses of blockchain for managing art sales and provenance, Elgammal caught the attention of Jessica Davidson, an art consultant who advises artists and galleries in building collections and exhibits. Davidson had been looking for business-development partnerships, and she became intrigued by AICAN as a marketable product. “I was interested in how we can harness it in a compelling way,” she says.

The art market is just that: a market. Some of the most renowned names in art today, from Damien Hirst to Banksy, trade in the trade of art as much as—and perhaps even more than—in the production of images, objects, and aesthetics. No artist today can avoid entering that fray, Elgammal included. “Is he an artist?” Hoerle-Guggenheim asked himself of the computer scientist. “Now that he’s in this context, he must be.” But is that enough? In Sharp’s estimation, “Faceless Portraits Transcending Time” is a tech demo more than a deliberate oeuvre, even compared to the machine-learning-driven work of his design-and-technology M.F.A. students, who self-identify as artists first.

Judged as Banksy or Hirst might be, Elgammal’s most art-worthy work might be the Artrendex start-up itself, not the pigment-print portraits that its technology has output. Elgammal doesn’t treat his commercial venture like a secret, but he also doesn’t surface it as a beneficiary of his supposedly earnest solo gallery show. He’s argued that AI-made images constitute a kind of conceptual art, but conceptualists tend to privilege process over product or to make the process as visible as the product.

Hoerle-Guggenheim worked as a financial analyst[emphasis mine] for Hyatt before getting into the art business via some kind of consulting deal (he responded cryptically when I pressed him for details). …

If you have the time, I recommend reading Bogost’s March 6, 2019 article for The Atlantic in its entirety/ these excerpts don’t do it enough justice.

Portraiture: what does it mean these days?

After reading the article I have a few questions. What exactly do Bogost and the arty types in the article mean by the word ‘portrait’? “Portrait of Edmond de Belamy” is an image of someone who doesn’t and never has existed and the exhibit “Faceless Portraits Transcending Time,” features images that don’t bear much or, in some cases, any resemblance to human beings. Maybe this is considered a dull question by people in the know but I’m an outsider and I found the paradox: portraits of nonexistent people or nonpeople kind of interesting.

BTW, I double-checked my assumption about portraits and found this definition in the Portrait Wikipedia entry (Note: Links have been removed),

A portrait is a painting, photograph, sculpture, or other artistic representation of a person [emphasis mine], in which the face and its expression is predominant. The intent is to display the likeness, personality, and even the mood of the person. For this reason, in photography a portrait is generally not a snapshot, but a composed image of a person in a still position. A portrait often shows a person looking directly at the painter or photographer, in order to most successfully engage the subject with the viewer.

So, portraits that aren’t portraits give rise to some philosophical questions but Bogost either didn’t want to jump into that rabbit hole (segue into yet another topic) or, as I hinted earlier, may have assumed his audience had previous experience of those kinds of discussions.

Vancouver (Canada) and a ‘portraiture’ exhibit at the Rennie Museum

By one of life’s coincidences, Vancouver’s Rennie Museum had an exhibit (February 16 – June 15, 2019) that illuminates questions about art collecting and portraiture, From a February 7, 2019 Rennie Museum news release,

‘downloaded from https://renniemuseum.org/press-release-spring-2019-collected-works/] Courtesy: Rennie Museum

February 7, 2019

Press Release | Spring 2019: Collected Works
By rennie museum

rennie museum is pleased to present Spring 2019: Collected Works, a group exhibition encompassing the mediums of photography, painting and film. A portraiture of the collecting spirit [emphasis mine], the works exhibited invite exploration of what collected objects, and both the considered and unintentional ways they are displayed, inform us. Featuring the works of four artists—Andrew Grassie, William E. Jones, Louise Lawler and Catherine Opie—the exhibition runs from February 16 to June 15, 2019.

Four exquisite paintings by Scottish painter Andrew Grassie detailing the home and private storage space of a major art collector provide a peek at how the passionately devoted integrates and accommodates the physical embodiments of such commitment into daily life. Grassie’s carefully constructed, hyper-realistic images also pose the question, “What happens to art once it’s sold?” In the transition from pristine gallery setting to idiosyncratic private space, how does the new context infuse our reading of the art and how does the art shift our perception of the individual?

Furthering the inquiry into the symbiotic exchange between possessor and possession, a selection of images by American photographer Louise Lawler depicting art installed in various private and public settings question how the bilateral relationship permeates our interpretation when the collector and the collected are no longer immediately connected. What does de-acquisitioning an object inform us and how does provenance affect our consideration of the art?

The question of legacy became an unexpected facet of 700 Nimes Road (2010-2011), American photographer Catherine Opie’s portrait of legendary actress Elizabeth Taylor. Opie did not directly photograph Taylor for any of the fifty images in the expansive portfolio. Instead, she focused on Taylor’s home and the objects within, inviting viewers to see—then see beyond—the façade of fame and consider how both treasures and trinkets act as vignettes to the stories of a life. Glamorous images of jewels and trophies juxtapose with mundane shots of a printer and the remote-control user manual. Groupings of major artworks on the wall are as illuminating of the home’s mistress as clusters of personal photos. Taylor passed away part way through Opie’s project. The subsequent photos include Taylor’s mementos heading off to auction, raising the question, “Once the collections that help to define someone are disbursed, will our image of that person lose focus?”

In a similar fashion, the twenty-two photographs in Villa Iolas (1982/2017), by American artist and filmmaker William E. Jones, depict the Athens home of iconic art dealer and collector Alexander Iolas. Taken in 1982 by Jones during his first travels abroad, the photographs of art, furniture and antiquities tell a story of privilege that contrast sharply with the images Jones captures on a return visit in 2016. Nearly three decades after Iolas’s 1989 death, his home sits in dilapidation, looted and vandalized. Iolas played an extraordinary role in the evolution of modern art, building the careers of Max Ernst, Yves Klein and Giorgio de Chirico. He gave Andy Warhol his first solo exhibition and was a key advisor to famed collectors John and Dominique de Menil. Yet in the years since his death, his intention of turning his home into a modern art museum as a gift to Greece, along with his reputation, crumbled into ruins. The photographs taken by Jones during his visits in two different eras are incorporated into the film Fall into Ruin (2017), along with shots of contemporary Athens and antiquities on display at the National Archaeological Museum.

“I ask a lot of questions about how portraiture functionswhat is there to describe the person or time we live in or a certain set of politics…”
 – Catherine Opie, The Guardian, Feb 9, 2016

We tend to think of the act of collecting as a formal activity yet it can happen casually on a daily basis, often in trivial ways. While we readily acknowledge a collector consciously assembling with deliberate thought, we give lesser consideration to the arbitrary accumulations that each of us accrue. Be it master artworks, incidental baubles or random curios, the objects we acquire and surround ourselves with tell stories of who we are.

Andrew Grassie (Scotland, b. 1966) is a painter known for his small scale, hyper-realist works. He has been the subject of solo exhibitions at the Tate Britain; Talbot Rice Gallery, Edinburgh; institut supérieur des arts de Toulouse; and rennie museum, Vancouver, Canada. He lives and works in London, England.

William E. Jones (USA, b. 1962) is an artist, experimental film-essayist and writer. Jones’s work has been the subject of retrospectives at Tate Modern, London; Anthology Film Archives, New York; Austrian Film Museum, Vienna; and, Oberhausen Short Film Festival. He is a recipient of the John Simon Guggenheim Memorial Fellowship and the Creative Capital/Andy Warhol Foundation Arts Writers Grant. He lives and works in Los Angeles, USA.

Louise Lawler (USA, b. 1947) is a photographer and one of the foremost members of the Pictures Generation. Lawler was the subject of a major retrospective at the Museum of Modern Art, New York in 2017. She has held exhibitions at the Whitney Museum of American Art, New York; Stedelijk Museum, Amsterdam; National Museum of Art, Oslo; and Musée d’Art Moderne de La Ville de Paris. She lives and works in New York.

Catherine Opie (USA, b. 1961) is a photographer and educator. Her work has been exhibited at Wexner Center for the Arts, Ohio; Henie Onstad Art Center, Oslo; Los the Angeles County Museum of Art; Portland Art Museum; and the Guggenheim Museum, New York. She is the recipient of United States Artist Fellowship, Julius Shulman’s Excellence in Photography Award, and the Smithsonian’s Archive of American Art Medal.  She lives and works in Los Angeles.

rennie museum opened in October 2009 in historic Wing Sang, the oldest structure in Vancouver’s Chinatown, to feature dynamic exhibitions comprising only of art drawn from rennie collection. Showcasing works by emerging and established international artists, the exhibits, accompanied by supporting catalogues, are open free to the public through engaging guided tours. The museum’s commitment to providing access to arts and culture is also expressed through its education program, which offers free age-appropriate tours and customized workshops to children of all ages.

rennie collection is a globally recognized collection of contemporary art that focuses on works that tackle issues related to identity, social commentary and injustice, appropriation, and the nature of painting, photography, sculpture and film. Currently the collection includes works by over 370 emerging and established artists, with over fifty collected in depth. The Vancouver based collection engages actively with numerous museums globally through a robust, artist-centric, lending policy.

So despite the Wikipedia definition, it seems that portraits don’t always feature people. While Bogost didn’t jump into that particular rabbit hole, he did touch on the business side of art.

What about intellectual property?

Bogost doesn’t explicitly discuss this particular issue. It’s a big topic so I’m touching on it only lightly, if an artist works* with an AI, the question as to ownership of the artwork could prove thorny. Is the copyright owner the computer scientist or the artist or both? Or does the AI artist-agent itself own the copyright? That last question may not be all that farfetched. Sophia, a social humanoid robot, has occasioned thought about ‘personhood.’ (Note: The robots mentioned in this posting have artificial intelligence.) From the Sophia (robot) Wikipedia entry (Note: Links have been removed),

Sophia has been interviewed in the same manner as a human, striking up conversations with hosts. Some replies have been nonsensical, while others have impressed interviewers such as 60 Minutes’ Charlie Rose.[12] In a piece for CNBC, when the interviewer expressed concerns about robot behavior, Sophia joked that he had “been reading too much Elon Musk. And watching too many Hollywood movies”.[27] Musk tweeted that Sophia should watch The Godfather and asked “what’s the worst that could happen?”[28][29] Business Insider’s chief UK editor Jim Edwards interviewed Sophia, and while the answers were “not altogether terrible”, he predicted it was a step towards “conversational artificial intelligence”.[30] At the 2018 Consumer Electronics Show, a BBC News reporter described talking with Sophia as “a slightly awkward experience”.[31]

On October 11, 2017, Sophia was introduced to the United Nations with a brief conversation with the United Nations Deputy Secretary-General, Amina J. Mohammed.[32] On October 25, at the Future Investment Summit in Riyadh, the robot was granted Saudi Arabian citizenship [emphasis mine], becoming the first robot ever to have a nationality.[29][33] This attracted controversy as some commentators wondered if this implied that Sophia could vote or marry, or whether a deliberate system shutdown could be considered murder. Social media users used Sophia’s citizenship to criticize Saudi Arabia’s human rights record. In December 2017, Sophia’s creator David Hanson said in an interview that Sophia would use her citizenship to advocate for women’s rights in her new country of citizenship; Newsweek criticized that “What [Hanson] means, exactly, is unclear”.[34] On November 27, 2018 Sophia was given a visa by Azerbaijan while attending Global Influencer Day Congress held in Baku. December 15, 2018 Sophia was appointed a Belt and Road Innovative Technology Ambassador by China'[35]

As for an AI artist-agent’s intellectual property rights , I have a July 10, 2017 posting featuring that question in more detail. Whether you read that piece or not, it seems obvious that artists might hesitate to call an AI agent, a partner rather than a medium of expression. After all, a partner (and/or the computer scientist who developed the programme) might expect to share in property rights and profits but paint, marble, plastic, and other media used by artists don’t have those expectations.

Moving slightly off topic , in my July 10, 2017 posting I mentioned a competition (literary and performing arts rather than visual arts) called, ‘Dartmouth College and its Neukom Institute Prizes in Computational Arts’. It was started in 2016 and, as of 2018, was still operational under this name: Creative Turing Tests. Assuming there’ll be contests for prizes in 2019, there’s (from the contest site) [1] PoetiX, competition in computer-generated sonnet writing; [2] Musical Style, composition algorithms in various styles, and human-machine improvisation …; and [3] DigiLit, algorithms able to produce “human-level” short story writing that is indistinguishable from an “average” human effort. You can find the contest site here.

*’worsk’ corrected to ‘works’ on June 9, 2022