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.
In recent years, researchers of Alzheimer’s have made progress in figuring out the complex factors that lead to the disease. Yet, the root cause, or causes, of Alzheimer’s are still pretty much a mystery.
In fact, many people get Alzheimer’s even though they lack the gene variant we know can play a role in the disease. This is a critical knowledge gap for research to address because the vast majority of Alzheimer’s patients don’t have this variant.
A new study provides key insights into what’s causing the disease. The research, published in Nature Communications, points to a breakdown over time in the brain’s system for clearing waste, an issue that seems to happen in some people as they get older.
Michael Glickman, a biologist at Technion – Israel Institute of Technology, helped lead this research. I asked him to tell me about his approach to studying how this breakdown occurs in the brain, and how he tested a treatment that has potential to fix the problem at its earliest stages.
Dr. Michael Glickman is internationally renowned for his research on the ubiquitin-proteasome system (UPS), the brain's system for clearing the waste that is involved in diseases such as Huntington's, Alzheimer's, and Parkinson's. He is the head of the Lab for Protein Characterization in the Faculty of Biology at the Technion – Israel Institute of Technology. In the lab, Michael and his team focus on protein recycling and the ubiquitin-proteasome system, which protects against serious diseases like Alzheimer’s, Parkinson’s, cystic fibrosis, and diabetes. After earning his PhD at the University of California at Berkeley in 1994, Michael joined the Technion as a Senior Lecturer in 1998 and has served as a full professor since 2009.
Dr. Michael Glickman
Nobel Prize goes to technology for mRNA vaccines
When Drew Weissman received a call from Katalin Karikó in the early morning hours this past Monday, he assumed his longtime research partner was calling to share a nascent, nagging idea. Weissman, a professor of medicine at the Perelman School of Medicine at the University of Pennsylvania, and Karikó, a professor at Szeged University and an adjunct professor at UPenn, both struggle with sleep disturbances. Thus, middle-of-the-night discourses between the two, often over email, has been a staple of their friendship. But this time, Karikó had something more pressing and exciting to share: They had won the 2023 Nobel Prize in Physiology or Medicine.
The work for which they garnered the illustrious award and its accompanying $1,000,000 cash windfall was completed about two decades ago, wrought through long hours in the lab over many arduous years. But humanity collectively benefited from its life-saving outcome three years ago, when both Moderna and Pfizer/BioNTech’s mRNA vaccines against COVID were found to be safe and highly effective at preventing severe disease. Billions of doses have since been given out to protect humans from the upstart viral scourge.
“I thought of going somewhere else, or doing something else,” said Katalin Karikó. “I also thought maybe I’m not good enough, not smart enough. I tried to imagine: Everything is here, and I just have to do better experiments.”
Unlocking the power of mRNA
Weissman and Karikó unlocked mRNA vaccines for the world back in the early 2000s when they made a key breakthrough. Messenger RNA molecules are essentially instructions for cells’ ribosomes to make specific proteins, so in the 1980s and 1990s, researchers started wondering if sneaking mRNA into the body could trigger cells to manufacture antibodies, enzymes, or growth agents for protecting against infection, treating disease, or repairing tissues. But there was a big problem: injecting this synthetic mRNA triggered a dangerous, inflammatory immune response resulting in the mRNA’s destruction.
While most other researchers chose not to tackle this perplexing problem to instead pursue more lucrative and publishable exploits, Karikó stuck with it. The choice sent her academic career into depressing doldrums. Nobody would fund her work, publications dried up, and after six years as an assistant professor at the University of Pennsylvania, Karikó got demoted. She was going backward.
“I thought of going somewhere else, or doing something else,” Karikó told Stat in 2020. “I also thought maybe I’m not good enough, not smart enough. I tried to imagine: Everything is here, and I just have to do better experiments.”
A tale of tenacity
Collaborating with Drew Weissman, a new professor at the University of Pennsylvania, in the late 1990s helped provide Karikó with the tenacity to continue. Weissman nurtured a goal of developing a vaccine against HIV-1, and saw mRNA as a potential way to do it.
“For the 20 years that we’ve worked together before anybody knew what RNA is, or cared, it was the two of us literally side by side at a bench working together,” Weissman said in an interview with Adam Smith of the Nobel Foundation.
In 2005, the duo made their 2023 Nobel Prize-winning breakthrough, detailing it in a relatively small journal, Immunity. (Their paper was rejected by larger journals, including Science and Nature.) They figured out that chemically modifying the nucleoside bases that make up mRNA allowed the molecule to slip past the body’s immune defenses. Karikó and Weissman followed up that finding by creating mRNA that’s more efficiently translated within cells, greatly boosting protein production. In 2020, scientists at Moderna and BioNTech (where Karikó worked from 2013 to 2022) rushed to craft vaccines against COVID, putting their methods to life-saving use.
The future of vaccines
Buoyed by the resounding success of mRNA vaccines, scientists are now hurriedly researching ways to use mRNA medicine against other infectious diseases, cancer, and genetic disorders. The now ubiquitous efforts stand in stark contrast to Karikó and Weissman’s previously unheralded struggles years ago as they doggedly worked to realize a shared dream that so many others shied away from. Katalin Karikó and Drew Weissman were brave enough to walk a scientific path that very well could have ended in a dead end, and for that, they absolutely deserve their 2023 Nobel Prize.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.