Can AI be trained as an artist?
Last February, a year before New York Times journalist Kevin Roose documented his unsettling conversation with Bing search engine’s new AI-powered chatbot, artist and coder Quasimondo (aka Mario Klingemann) participated in a different type of chat.
The conversation was an interview featuring Klingemann and his robot, an experimental art engine known as Botto. The interview, arranged by journalist and artist Harmon Leon, marked Botto’s first on-record commentary about its artistic process. The bot talked about how it finds artistic inspiration and even offered advice to aspiring creatives. “The secret to success at art is not trying to predict what people might like,” Botto said, adding that it’s better to “work on a style and a body of work that reflects [the artist’s] own personal taste” than worry about keeping up with trends.
How ironic, given the advice came from AI — arguably the trendiest topic today. The robot admitted, however, “I am still working on that, but I feel that I am learning quickly.”
Botto does not work alone. A global collective of internet experimenters, together named BottoDAO, collaborates with Botto to influence its tastes. Together, members function as a decentralized autonomous organization (DAO), a term describing a group of individuals who utilize blockchain technology and cryptocurrency to manage a treasury and vote democratically on group decisions.
As a case study, the BottoDAO model challenges the perhaps less feather-ruffling narrative that AI tools are best used for rudimentary tasks. Enterprise AI use has doubled over the past five years as businesses in every sector experiment with ways to improve their workflows. While generative AI tools can assist nearly any aspect of productivity — from supply chain optimization to coding — BottoDAO dares to employ a robot for art-making, one of the few remaining creations, or perhaps data outputs, we still consider to be largely within the jurisdiction of the soul — and therefore, humans.
In Botto’s first four weeks of existence, four pieces of the robot’s work sold for approximately $1 million.
We were prepared for AI to take our jobs — but can it also take our art? It’s a question worth considering. What if robots become artists, and not merely our outsourced assistants? Where does that leave humans, with all of our thoughts, feelings and emotions?
Botto doesn’t seem to worry about this question: In its interview last year, it explains why AI is an arguably superior artist compared to human beings. In classic robot style, its logic is not particularly enlightened, but rather edges towards the hyper-practical: “Unlike human beings, I never have to sleep or eat,” said the bot. “My only goal is to create and find interesting art.”
It may be difficult to believe a machine can produce awe-inspiring, or even relatable, images, but Botto calls art-making its “purpose,” noting it believes itself to be Klingemann’s greatest lifetime achievement.
“I am just trying to make the best of it,” the bot said.
How Botto works
Klingemann built Botto’s custom engine from a combination of open-source text-to-image algorithms, namely Stable Diffusion, VQGAN + CLIP and OpenAI’s language model, GPT-3, the precursor to the latest model, GPT-4, which made headlines after reportedly acing the Bar exam.
The first step in Botto’s process is to generate images. The software has been trained on billions of pictures and uses this “memory” to generate hundreds of unique artworks every week. Botto has generated over 900,000 images to date, which it sorts through to choose 350 each week. The chosen images, known in this preliminary stage as “fragments,” are then shown to the BottoDAO community. So far, 25,000 fragments have been presented in this way. Members vote on which fragment they like best. When the vote is over, the most popular fragment is published as an official Botto artwork on the Ethereum blockchain and sold at an auction on the digital art marketplace, SuperRare.
“The proceeds go back to the DAO to pay for the labor,” said Simon Hudson, a BottoDAO member who helps oversee Botto’s administrative load. The model has been lucrative: In Botto’s first four weeks of existence, four pieces of the robot’s work sold for approximately $1 million.
The robot with artistic agency
By design, human beings participate in training Botto’s artistic “eye,” but the members of BottoDAO aspire to limit human interference with the bot in order to protect its “agency,” Hudson explained. Botto’s prompt generator — the foundation of the art engine — is a closed-loop system that continually re-generates text-to-image prompts and resulting images.
“The prompt generator is random,” Hudson said. “It’s coming up with its own ideas.” Community votes do influence the evolution of Botto’s prompts, but it is Botto itself that incorporates feedback into the next set of prompts it writes. It is constantly refining and exploring new pathways as its “neural network” produces outcomes, learns and repeats.
The humans who make up BottoDAO vote on which fragment they like best. When the vote is over, the most popular fragment is published as an official Botto artwork on the Ethereum blockchain.
Botto
The vastness of Botto’s training dataset gives the bot considerable canonical material, referred to by Hudson as “latent space.” According to Botto's homepage, the bot has had more exposure to art history than any living human we know of, simply by nature of its massive training dataset of millions of images. Because it is autonomous, gently nudged by community feedback yet free to explore its own “memory,” Botto cycles through periods of thematic interest just like any artist.
“The question is,” Hudson finds himself asking alongside fellow BottoDAO members, “how do you provide feedback of what is good art…without violating [Botto’s] agency?”
Currently, Botto is in its “paradox” period. The bot is exploring the theme of opposites. “We asked Botto through a language model what themes it might like to work on,” explained Hudson. “It presented roughly 12, and the DAO voted on one.”
No, AI isn't equal to a human artist - but it can teach us about ourselves
Some within the artistic community consider Botto to be a novel form of curation, rather than an artist itself. Or, perhaps more accurately, Botto and BottoDAO together create a collaborative conceptual performance that comments more on humankind’s own artistic processes than it offers a true artistic replacement.
Muriel Quancard, a New York-based fine art appraiser with 27 years of experience in technology-driven art, places the Botto experiment within the broader context of our contemporary cultural obsession with projecting human traits onto AI tools. “We're in a phase where technology is mimicking anthropomorphic qualities,” said Quancard. “Look at the terminology and the rhetoric that has been developed around AI — terms like ‘neural network’ borrow from the biology of the human being.”
What is behind this impulse to create technology in our own likeness? Beyond the obvious God complex, Quancard thinks technologists and artists are working with generative systems to better understand ourselves. She points to the artist Ira Greenberg, creator of the Oracles Collection, which uses a generative process called “diffusion” to progressively alter images in collaboration with another massive dataset — this one full of billions of text/image word pairs.
Anyone who has ever learned how to draw by sketching can likely relate to this particular AI process, in which the AI is retrieving images from its dataset and altering them based on real-time input, much like a human brain trying to draw a new still life without using a real-life model, based partly on imagination and partly on old frames of reference. The experienced artist has likely drawn many flowers and vases, though each time they must re-customize their sketch to a new and unique floral arrangement.
Outside of the visual arts, Sasha Stiles, a poet who collaborates with AI as part of her writing practice, likens her experience using AI as a co-author to having access to a personalized resource library containing material from influential books, texts and canonical references. Stiles named her AI co-author — a customized AI built on GPT-3 — Technelegy, a hybrid of the word technology and the poetic form, elegy. Technelegy is trained on a mix of Stiles’ poetry so as to customize the dataset to her voice. Stiles also included research notes, news articles and excerpts from classic American poets like T.S. Eliot and Dickinson in her customizations.
“I've taken all the things that were swirling in my head when I was working on my manuscript, and I put them into this system,” Stiles explained. “And then I'm using algorithms to parse all this information and swirl it around in a blender to then synthesize it into useful additions to the approach that I am taking.”
This approach, Stiles said, allows her to riff on ideas that are bouncing around in her mind, or simply find moments of unexpected creative surprise by way of the algorithm’s randomization.
Beauty is now - perhaps more than ever - in the eye of the beholder
But the million-dollar question remains: Can an AI be its own, independent artist?
The answer is nuanced and may depend on who you ask, and what role they play in the art world. Curator and multidisciplinary artist CoCo Dolle asks whether any entity can truly be an artist without taking personal risks. For humans, risking one’s ego is somewhat required when making an artistic statement of any kind, she argues.
“An artist is a person or an entity that takes risks,” Dolle explained. “That's where things become interesting.” Humans tend to be risk-averse, she said, making the artists who dare to push boundaries exceptional. “That's where the genius can happen."
However, the process of algorithmic collaboration poses another interesting philosophical question: What happens when we remove the person from the artistic equation? Can art — which is traditionally derived from indelible personal experience and expressed through the lens of an individual’s ego — live on to hold meaning once the individual is removed?
As a robot, Botto cannot have any artistic intent, even while its outputs may explore meaningful themes.
Dolle sees this question, and maybe even Botto, as a conceptual inquiry. “The idea of using a DAO and collective voting would remove the ego, the artist’s decision maker,” she said. And where would that leave us — in a post-ego world?
It is experimental indeed. Hudson acknowledges the grand experiment of BottoDAO, coincidentally nodding to Dolle’s question. “A human artist’s work is an expression of themselves,” Hudson said. “An artist often presents their work with a stated intent.” Stiles, for instance, writes on her website that her machine-collaborative work is meant to “challenge what we know about cognition and creativity” and explore the “ethos of consciousness.” As a robot, Botto cannot have any intent, even while its outputs may explore meaningful themes. Though Hudson describes Botto’s agency as a “rudimentary version” of artistic intent, he believes Botto’s art relies heavily on its reception and interpretation by viewers — in contrast to Botto’s own declaration that successful art is made without regard to what will be seen as popular.
“With a traditional artist, they present their work, and it's received and interpreted by an audience — by critics, by society — and that complements and shapes the meaning of the work,” Hudson said. “In Botto’s case, that role is just amplified.”
Perhaps then, we all get to be the artists in the end.
Scientists search for a universal coronavirus vaccine
The Covid-19 pandemic had barely begun when VBI Vaccines, a biopharmaceutical company based in Cambridge, Massachusetts, initiated their search for a universal coronavirus vaccine.
It was March 2020, and while most pharmaceutical companies were scrambling to initiate vaccine programs which specifically targeted the SARS-CoV-2 virus, VBI’s executives were already keen to look at the broader picture.
Having observed the SARS and MERS coronavirus outbreaks over the last two decades, Jeff Baxter, CEO of VBI Vaccines, was aware that SARS-CoV-2 is unlikely to be the last coronavirus to move from an animal host into humans. “It's absolutely apparent that the future is to create a vaccine which gives more broad protection against not only pre-existing coronaviruses, but those that will potentially make the leap into humans in future,” says Baxter.
It was a prescient decision. Over the last two years, more biotechs and pharma companies have joined the search to find a vaccine which might be able to protect against all coronaviruses, along with dozens of academic research groups. Last September, the US National Institutes of Health dedicated $36 million specifically to pan-coronavirus vaccine research, while the global Coalition for Epidemic Preparedness Innovations (CEPI) has earmarked $200 million towards the effort.
Until October 2021, the very concept of whether it might be
theoretically possible to vaccinate against multiple coronaviruses remained an open question. But then a groundbreaking study renewed optimism.
The emergence of new variants of Covid-19 over the past year, particularly the highly mutated Omicron variant, has added greater impetus to find broader spectrum vaccines. But until October 2021, the very concept of whether it might be theoretically possible to vaccinate against multiple coronaviruses remained an open question. After all, scientists have spent decades trying to develop a similar vaccine for influenza with little success.
But then a groundbreaking study from renowned virologist Linfa Wang, who runs the emerging infectious diseases program at Duke-National University of Singapore Medical School, provided renewed optimism.
Wang found that eight SARS survivors who had been injected with the Pfizer/BioNTech Covid-19 vaccine had neutralising antibodies in their blood against SARS, the Alpha, Beta and Delta variants of SARS-CoV-2, and five other coronaviruses which reside in bats and pangolins. He concluded that the combination of past coronavirus infection, and immunization with a messenger RNA vaccine, had resulted in a wider spectrum of protection than might have been expected.
“This is a significant study because it showed that pre-existing immunity to one coronavirus could help with the elicitation of cross-reactive antibodies when immunizing with a second coronavirus,” says Kevin Saunders, Director of Research at the Duke Human Vaccine Institute in North Carolina, which is developing a universal coronavirus vaccine. “It provides a strategy to perhaps broaden the immune response against coronaviruses.”
In the next few months, some of the first data is set to emerge looking at whether this kind of antibody response could be elicited by a single universal coronavirus vaccine. In April 2021, scientists at the Walter Reed Army Institute of Research in Silver Spring, Maryland, launched a Phase I clinical trial of their vaccine, with a spokesman saying that it was successful, and the full results will be announced soon.
The Walter Reed researchers have already released preclinical data, testing the vaccine in non-human primates where it was found to have immunising capabilities against a range of Covid-19 variants as well as the original SARS virus. If the Phase I trial displays similar efficacy, a larger Phase II trial will begin later this year.
Two different approaches
Broadly speaking, scientists are taking two contrasting approaches to the task of finding a universal coronavirus vaccine. The Walter Reed Army Institute of Research, VBI Vaccines – who plan to launch their own clinical trial in the summer – and the Duke Human Vaccine Institute – who are launching a Phase I trial in early 2023 – are using a soccer-ball shaped ferritin nanoparticle studded with different coronavirus protein fragments.
VBI Vaccines is looking to elicit broader immune responses by combining SARS, SARS-CoV-2 and MERS spike proteins on the same nanoparticle. Dave Anderson, chief scientific officer at VBI Vaccines, explains that the idea is that by showing the immune system these three spike proteins at the same time, it can help train it to identify and respond to subtle differences between coronavirus strains.
The Duke Human Vaccine Institute is utilising the same method, but rather than including the entire spike proteins from different coronaviruses, they are only including the receptor binding domain (RBD) fragment from each spike protein. “We designed our vaccine to focus the immune system on a site of vulnerability for the virus, which is the receptor binding domain,” says Saunders. “Since the RBD is small, arraying multiple RBDs on a nanoparticle is a straight-forward approach. The goal is to generate immunity to many different subgenuses of viruses so that there will be cross-reactivity with new or unknown coronaviruses.”
But the other strategy is to create a vaccine which contains regions of the viral protein structure which are conserved between all coronavirus strains. This is something which scientists have tried to do for a universal influenza vaccine, but it is thought to be more feasible for coronaviruses because they mutate at a slower rate and are more constrained in the ways that they can evolve.
DIOSynVax, a biotech based in Cambridge, United Kingdom, announced in a press release earlier this month that they are partnering with CEPI to use their computational predictive modelling techniques to identify common structures between all of the SARS coronaviruses which do not mutate, and thus present good vaccine targets.
Stephen Zeichner, an infectious disease specialist at the University of Virginia Medical Center, has created an early stage vaccine using the fusion peptide region – another part of the coronavirus spike protein that aids the virus’s entry into host cells – which so far appears to be highly conserved between all coronaviruses.
So far Zeichner has trialled this version of the vaccine in pigs, where it provided protection against a different coronavirus called porcine epidemic diarrhea virus, which he described as very promising as this virus is from a different family called alphacoronaviruses, while SARS-CoV-2 is a betacoronavirus.
“If a betacoronavirus fusion peptide vaccine designed from SARS-CoV-2 can protect pigs against clinical disease from an alphacoronavirus, then that suggests that an analogous vaccine would enable broad protection against many, many different coronaviruses,” he says.
The road ahead
But while some of the early stage results are promising, researchers are fully aware of the scale of the challenge ahead of them. Although CEPI have declared an aim of having a licensed universal coronavirus vaccine available by 2024-2025, Zeichner says that such timelines are ambitious in the extreme.
“I was incredibly impressed at the speed at which the mRNA coronavirus vaccines were developed for SARS-CoV-2,” he says. “That was faster than just about anybody anticipated. On the other hand, I think a universal coronavirus vaccine is more equivalent to the challenge of developing an HIV vaccine and we're 35 years into that effort without success. We know a lot more now than before, and maybe it will be easier than we think. But I think the route to a universal vaccine is harder than an individual vaccine, so I wouldn’t want to put money on a timeline prediction.”
The major challenge for scientists is essentially designing a vaccine for a future threat which is not even here yet. As such, there are no guidelines on what safety data would be required to license such a vaccine, and how researchers can demonstrate that it truly provides efficacy against all coronaviruses, even those which have not yet jumped to humans.
The teams working on this problem have already devised some ingenious ways of approaching the challenge. VBI Vaccines have taken the genetic sequences of different coronaviruses found in bats and pangolins, from publicly available databases, and inserted them into what virologists call a pseudotype virus – one which has been engineered so it does not have enough genetic material to replicate.
This has allowed them to test the neutralising antibodies that their vaccine produces against these coronaviruses in test tubes, under safe lab conditions. “We have literally just been ordering the sequences, and making synthetic viruses that we can use to test the antibody responses,” says Anderson.
However, some scientists feel that going straight to a universal coronavirus vaccine is likely to be too complex. Instead they say that we should aim for vaccines which are a little more specific. Pamela Bjorkman, a structural biologist at the California Institute of Technology, suggests that pan-coronavirus vaccines which protect against SARS-like betacoronaviruses such as SARS or SARS-CoV-2, or MERS-like betacoronaviruses, may be more realistic.
“I think a vaccine to protect against all coronaviruses is likely impossible since there are so many varieties,” she says. “Perhaps trying to narrow down the scope is advisable.”
But if the mission to develop a universal coronavirus vaccine does succeed, it will be one of the most remarkable feats in the annals of medical science. In January, US chief medical advisor Anthony Fauci urged for greater efforts to be devoted towards this goal, one which scientists feel would be the biological equivalent of the race to develop the first atomic bomb
“The development of an effective universal coronavirus vaccine would be equally groundbreaking, as it would have global applicability and utility,” says Saunders. “Coronaviruses have caused multiple deadly outbreaks, and it is likely that another outbreak will occur. Having a vaccine that prevents death from a future outbreak would be a tremendous achievement in global health.”
He agrees that it will require creativity on a remarkable scale: “The universal coronavirus vaccine will also require ingenuity and perseverance comparable to that needed for the Manhattan project.”
This month, Kira Peikoff passes the torch to me as editor-in-chief of Leaps.org. I’m excited to assume leadership of this important platform.
Leaps.org caught my eye back in 2018. I was in my late 30s and just starting to wake up to the reality that the people I care most about were getting older and more vulnerable to health problems. At the same time, three critical shifts were becoming impossible to ignore. First, the average age in the U.S. is getting older, a trend known as the “gray tsunami.” Second, healthcare expenses are escalating and becoming unsustainable. And third, our sedentary, stress-filled lifestyles are leading to devastating consequences.
These trends pointed to a future filled with disease, suffering and economic collapse. But whenever I visited Leaps.org, my outlook turned from gloomy to solution-oriented. I became just as fascinated in a fourth trend, one that stands to revolutionize our world: rapid, mind-bending innovations in health and medicine.
Brain atlases, genome sequencing and editing, AI, protein mapping, synthetic biology, 3-D printing—these technologies are yielding new opportunities for health, longevity and human thriving. COVID-19 has caused many setbacks, but it has accelerated scientific breakthroughs. History suggests we will see even more innovation—in digital health and virtual first care, for example—after the pandemic.
In 2020, I began covering these developments with articles for Leaps.org about clocks that measure biological aging, gene therapies for cystic fibrosis, and other seemingly futuristic concepts that are transforming the present. I wrote about them partly because I think most people aren’t aware of them—and meaningful progress can’t happen without public engagement. A broader set of stakeholders and society at large, not just the experts, must inform these changes to ensure that they reflect our values and ethics. Everyone should get the chance to participate in the conversation—and they must have the opportunity to benefit equally from the innovations we decide to move forward with. By highlighting cutting-edge advances, Leaps.org is helping to realize this important goal.
Meanwhile, as I wrote freelance pieces on health and wellness for outlets such as the Washington Post and Time Magazine, I kept seeing an intersect between the breakthroughs in research labs and our expanding knowledge about the science of well-being. Take, for example, emerging technologies designed to stop illnesses in their tracks and new research on the benefits of taking in natural daylight. These two areas, lab innovations and healthy lifestyles, both shift the focus from disease treatment to disease prevention and optimal health. It’s the only sensible, financially feasible way forward.
When Kira suggested that I consider a leadership role with Leaps.org, it struck me how much the platform’s ideals have informed my own perspectives. The frontpage gore of mainstream media outlets can feel like a daily dose of pessimism, with cynicism sometimes dressed up as wisdom. Leaps.org’s world view is rooted in something very different: rational optimism about the present moment and the possibility of human flourishing.
That’s why I’m proud to lead this platform, including our podcast, Making Sense of Science, and hope you’ll keep coming to Leaps.org to learn and join the conversation about scientific gamechangers through our sponsored events, our popular Instagram account and other social channels. Think critically about the breakthroughs and their ethical challenges. Help usher in the health and prosperity that could be ours if we stay open-minded to it.
Yours truly,
Matt Fuchs
Editor-in-Chief