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.
Her Incredible Sense of Smell Led Scientists to Develop the First Parkinson's Test
Thirty-seven years ago, Joy Milne, a nurse from Perth, Scotland, noticed a musky odor coming from her husband, Les.
To her surprise, at a local support group meeting, she caught the familiar scent once again, hanging over the group like a cloud.
At first, Milne thought the smell was a result of bad hygiene and badgered her husband to take longer showers. But when the smell persisted, Milne learned to live with it, not wanting to hurt her husband's feelings.
Twelve years after she first noticed the "woodsy" smell, Les was diagnosed at the age of 44 with Parkinson's Disease, a neurodegenerative condition characterized by lack of dopamine production and loss of movement. Parkinson's Disease currently affects more than 10 million people worldwide.
Milne spent the next several years believing the strange smell was exclusive to her husband. But to her surprise, at a local support group meeting in 2012, she caught the familiar scent once again, hanging over the group like a cloud. Stunned, Milne started to wonder if the smell was the result of Parkinson's Disease itself.
Milne's discovery led her to Dr. Tilo Kunath, a neurobiologist at the Centre for Regenerative Medicine at the University of Edinburgh. Together, Milne, Kunath, and a host of other scientists would use Milne's unusual sense of smell to develop a new diagnostic test, now in development and poised to revolutionize the treatment of Parkinson's Disease.
"Joy was in the audience during a talk I was giving on my work, which has to do with Parkinson's and stem cell biology," Kunath says. "During the patient engagement portion of the talk, she asked me if Parkinson's had a smell to it." Confused, Kunath said he had never heard of this – but for months after his talk he continued to turn the question over in his mind.
Kunath knew from his research that the skin's microbiome changes during different disease processes, releasing metabolites that can give off odors. In the medical literature, diseases like melanoma and Type 2 diabetes have been known to carry a specific scent – but no such connection had been made with Parkinson's. If people could smell Parkinson's, he thought, then it stood to reason that those metabolites could be isolated, identified, and used to potentially diagnose Parkinson's by their presence alone.
First, Kunath and his colleagues decided to test Milne's sense of smell. "I got in touch with Joy again and we designed a protocol to test her sense of smell without her having to be around patients," says Kunath, which could have affected the validity of the test. In his spare time, Kunath collected t-shirt samples from people diagnosed with Parkinson's and from others without the diagnosis and gave them to Milne to smell. In 100 percent of the samples, Milne was able to detect whether a person had Parkinson's based on smell alone. Amazingly, Milne was even able to detect the "Parkinson's scent" in a shirt from the control group – someone who did not have a Parkinson's diagnosis, but would go on to be diagnosed nine months later.
From the initial study, the team discovered that Parkinson's did have a smell, that Milne – inexplicably – could detect it, and that she could detect it long before diagnosis like she had with her husband, Les. But the experiments revealed other things that the team hadn't been expecting.
"One surprising thing we learned from that experiment was that the odor was always located in the back of the shirt – never in the armpit, where we expected the smell to be," Kunath says. "I had a chance meeting with a dermatologist and he said the smell was due to the patient's sebum, which are greasy secretions that are really dense on your upper back. We have sweat glands, instead of sebum, in our armpits." Patients with Parkinson's are also known to have increased sebum production.
With the knowledge that a patient's sebum was the source of the unusual smell, researchers could go on to investigate exactly what metabolites were in the sebum and in what amounts. Kunath, along with his associate, Dr. Perdita Barran, collected and analyzed sebum samples from 64 participants across the United Kingdom. Once the samples were collected, Barran and others analyzed it using a method called gas chromatography mass spectrometry, or GS-MC, which separated, weighed and helped identify the individual compounds present in each sebum sample.
Barran's team can now correctly identify Parkinson's in nine out of 10 patients – a much quicker and more accurate way to diagnose than what clinicians do now.
"The compounds we've identified in the sebum are not unique to people with Parkinson's, but they are differently expressed," says Barran, a professor of mass spectrometry at the University of Manchester. "So this test we're developing now is not a black-and-white, do-you-have-something kind of test, but rather how much of these compounds do you have compared to other people and other compounds." The team identified over a dozen compounds that were present in the sebum of Parkinson's patients in much larger amounts than the control group.
Using only the GC-MS and a sebum swab test, Barran's team can now correctly identify Parkinson's in nine out of 10 patients – a much quicker and more accurate way to diagnose than what clinicians do now.
"At the moment, a clinical diagnosis is based on the patient's physical symptoms," Barran says, and determining whether a patient has Parkinson's is often a long and drawn-out process of elimination. "Doctors might say that a group of symptoms looks like Parkinson's, but there are other reasons people might have those symptoms, and it might take another year before they're certain," Barran says. "Some of those symptoms are just signs of aging, and other symptoms like tremor are present in recovering alcoholics or people with other kinds of dementia." People under the age of 40 with Parkinson's symptoms, who present with stiff arms, are often misdiagnosed with carpal tunnel syndrome, she adds.
Additionally, by the time physical symptoms are present, Parkinson's patients have already lost a substantial amount of dopamine receptors – about sixty percent -- in the brain's basal ganglia. Getting a diagnosis before physical symptoms appear would mean earlier interventions that could prevent dopamine loss and preserve regular movement, Barran says.
"Early diagnosis is good if it means there's a chance of early intervention," says Barran. "It stops the process of dopamine loss, which means that motor symptoms potentially will not happen, or the onset of symptoms will be substantially delayed." Barran's team is in the processing of streamlining the sebum test so that definitive results will be ready in just two minutes.
"What we're doing right now will be a very inexpensive test, a rapid-screen test, and that will encourage people to self-sample and test at home," says Barran. In addition to diagnosing Parkinson's, she says, this test could also be potentially useful to determine if medications were at a therapeutic dose in people who have the disease, since the odor is strongest in people whose symptoms are least controlled by medication.
"When symptoms are under control, the odor is lower," Barran says. "Potentially this would allow patients and clinicians to see whether their symptoms are being managed properly with medication, or perhaps if they're being overmedicated." Hypothetically, patients could also use the test to determine if interventions like diet and exercise are effective at keeping Parkinson's controlled.
"We hope within the next two to five years we will have a test available."
Barran is now running another clinical trial – one that determines whether they can diagnose at an earlier stage and whether they can identify a difference in sebum samples between different forms of Parkinson's or diseases that have Parkinson's-like symptoms, such as Lewy Body Dementia.
"Within the next one to two years, we hope to be running a trial in the Manchester area for those people who do not have motor symptoms but are at risk for developing dementia due to symptoms like loss of smell and sleep difficulty," Barran says. "If we can establish that, we can roll out a test that determines if you have Parkinson's or not with those first pre-motor symptoms, and then at what stage. We hope within the next two to five years we will have a test available."
But a definitive Parkinson's test, however revolutionary, would likely not be made available to the general population – at least, not for a while.
"We would likely first give this test to people who are at risk due to a genetic predisposition, or who are at risk based on prodomal symptoms, like people who suffer from a REM sleep disorder who have a 50 to 70 percent chance of developing Parkinson's within a ten year period," Barran says. "Those would be people who would benefit from early therapeutic intervention. For the normal population, it isn't beneficial at the moment to know until we have therapeutic interventions that can be useful."
Milne's husband, Les, passed away from complications of Parkinson's Disease in 2015. But thanks to him and the dedication of his wife, Joy, science may have found a way to someday prolong the lives of others with this devastating disease.
[Ed. Note: This hit article from our archives originally ran on September 3, 2019.]
A Team of Israeli Students Just Created Honey Without Bees
Can you make honey without honeybees? According to 12 Israeli students who took home a gold medal in the iGEM (International Genetically Engineered Machine) competition with their synthetic honey project, the answer is yes, you can.
The honey industry faces serious environmental challenges, like the mysterious Colony Collapse Disorder.
For the past year, the team from Technion-Israel Institute of Technology has been working on creating sustainable, artificial honey—no bees required. Why? As the team explains in a video on the project's website, "Studies have shown the amazing nutritional values of honey. However, the honey industry harms the environment, and particularly the bees. That's why vegans don't use honey and why our honey will be a great replacement."
Indeed, honey has long been a controversial product in the vegan community. Some say it's stealing an animal's food source (though bees make more honey than they can possibly use). Some avoid eating honey because it is an animal product and bees' natural habitats are disturbed by humans harvesting it. Others feel that because bees aren't directly killed or harmed in the production of honey, it's not actually unethical to eat.
However, there's no doubt that the honey industry faces some serious environmental challenges. Colony Collapse Disorder, a mysterious phenomenon in which worker bees in colonies disappear in large numbers without any real explanation, came to international attention in 2006. Several explanations from poisonous pesticides to immune-suppressing stress to new or emerging diseases have been posited, but no definitive cause has been found.
There's also the problem of human-managed honey farms having a negative impact on the natural honeybee population.
So how can honey be made without honeybees? It's all about bacteria and enzymes.
The way bees make honey is by collecting nectar from flowers, transporting it in their "honey stomach" (which is separate from their food stomach), and bringing it back to the hive, where it gets transferred from bee mouth to bee mouth. That transferal process reduces the moisture content from about 70 percent to 20 percent, and honey is formed.
The product is still currently under development.
The Technion students created a model of a synthetic honey stomach metabolic pathway, in which the bacterium Bacillus subtilis "learns" to produce honey. "The bacteria can independently control the production of enzymes, eventually achieving a product with the same sugar profile as real honey, and the same health benefits," the team explains. Bacillus subtilis, which is found in soil, vegetation, and our own gastrointestinal tracts, has a natural ability to produce catalase, one of the enzymes needed for honey production. The product is still currently under development.
Whether this project results in a real-world jar of honey we'll be able to buy at the grocery store remains to be seen, but imagine how happy the bees—and vegans—would be if it did.