Tag Archives: Yann LeCun

Non-human authors (ChatGPT or others) of scientific and medical studies and the latest AI panic!!!

It’s fascinating to see all the current excitement (distressed and/or enthusiastic) around the act of writing and artificial intelligence. Easy to forget that it’s not new. First, the ‘non-human authors’ and then the panic(s). *What follows the ‘nonhuman authors’ is essentially a survey of situation/panic.*

How to handle non-human authors (ChatGPT and other AI agents)—the medical edition

The first time I wrote about the incursion of robots or artificial intelligence into the field of writing was in a July 16, 2014 posting titled “Writing and AI or is a robot writing this blog?” ChatGPT (then known as GPT-2) first made its way onto this blog in a February 18, 2019 posting titled “AI (artificial intelligence) text generator, too dangerous to release?

The folks at the Journal of the American Medical Association (JAMA) have recently adopted a pragmatic approach to the possibility of nonhuman authors of scientific and medical papers, from a January 31, 2022 JAMA editorial,

Artificial intelligence (AI) technologies to help authors improve the preparation and quality of their manuscripts and published articles are rapidly increasing in number and sophistication. These include tools to assist with writing, grammar, language, references, statistical analysis, and reporting standards. Editors and publishers also use AI-assisted tools for myriad purposes, including to screen submissions for problems (eg, plagiarism, image manipulation, ethical issues), triage submissions, validate references, edit, and code content for publication in different media and to facilitate postpublication search and discoverability..1

In November 2022, OpenAI released a new open source, natural language processing tool called ChatGPT.2,3 ChatGPT is an evolution of a chatbot that is designed to simulate human conversation in response to prompts or questions (GPT stands for “generative pretrained transformer”). The release has prompted immediate excitement about its many potential uses4 but also trepidation about potential misuse, such as concerns about using the language model to cheat on homework assignments, write student essays, and take examinations, including medical licensing examinations.5 In January 2023, Nature reported on 2 preprints and 2 articles published in the science and health fields that included ChatGPT as a bylined author.6 Each of these includes an affiliation for ChatGPT, and 1 of the articles includes an email address for the nonhuman “author.” According to Nature, that article’s inclusion of ChatGPT in the author byline was an “error that will soon be corrected.”6 However, these articles and their nonhuman “authors” have already been indexed in PubMed and Google Scholar.

Nature has since defined a policy to guide the use of large-scale language models in scientific publication, which prohibits naming of such tools as a “credited author on a research paper” because “attribution of authorship carries with it accountability for the work, and AI tools cannot take such responsibility.”7 The policy also advises researchers who use these tools to document this use in the Methods or Acknowledgment sections of manuscripts.7 Other journals8,9 and organizations10 are swiftly developing policies that ban inclusion of these nonhuman technologies as “authors” and that range from prohibiting the inclusion of AI-generated text in submitted work8 to requiring full transparency, responsibility, and accountability for how such tools are used and reported in scholarly publication.9,10 The International Conference on Machine Learning, which issues calls for papers to be reviewed and discussed at its conferences, has also announced a new policy: “Papers that include text generated from a large-scale language model (LLM) such as ChatGPT are prohibited unless the produced text is presented as a part of the paper’s experimental analysis.”11 The society notes that this policy has generated a flurry of questions and that it plans “to investigate and discuss the impact, both positive and negative, of LLMs on reviewing and publishing in the field of machine learning and AI” and will revisit the policy in the future.11

This is a link to and a citation for the JAMA editorial,

Nonhuman “Authors” and Implications for the Integrity of Scientific Publication and Medical Knowledge by Annette Flanagin, Kirsten Bibbins-Domingo, Michael Berkwits, Stacy L. Christiansen. JAMA. 2023;329(8):637-639. doi:10.1001/jama.2023.1344

The editorial appears to be open access.

ChatGPT in the field of education

Dr. Andrew Maynard (scientist, author, and professor of Advanced Technology Transitions in the Arizona State University [ASU] School for the Future if Innovation in Society and founder of the ASU Future of Being Human initiative and Director of the ASU Risk Innovation Nexus) also takes a pragmatic approach in a March 14, 2023 posting on his eponymous blog,

Like many of my colleagues, I’ve been grappling with how ChatGPT and other Large Language Models (LLMs) are impacting teaching and education — especially at the undergraduate level.

We’re already seeing signs of the challenges here as a growing divide emerges between LLM-savvy students who are experimenting with novel ways of using (and abusing) tools like ChatGPT, and educators who are desperately trying to catch up. As a result, educators are increasingly finding themselves unprepared and poorly equipped to navigate near-real-time innovations in how students are using these tools. And this is only exacerbated where their knowledge of what is emerging is several steps behind that of their students.

To help address this immediate need, a number of colleagues and I compiled a practical set of Frequently Asked Questions on ChatGPT in the classroom. These covers the basics of what ChatGPT is, possible concerns over use by students, potential creative ways of using the tool to enhance learning, and suggestions for class-specific guidelines.

Dr. Maynard goes on to offer the FAQ/practical guide here. Prior to issuing the ‘guide’, he wrote a December 8, 2022 essay on Medium titled “I asked Open AI’s ChatGPT about responsible innovation. This is what I got.”

Crawford Kilian, a longtime educator, author, and contributing editor to The Tyee, expresses measured enthusiasm for the new technology (as does Dr. Maynard), in a December 13, 2022 article for thetyee.ca, Note: Links have been removed,

ChatGPT, its makers tell us, is still in beta form. Like a million other new users, I’ve been teaching it (tuition-free) so its answers will improve. It’s pretty easy to run a tutorial: once you’ve created an account, you’re invited to ask a question or give a command. Then you watch the reply, popping up on the screen at the speed of a fast and very accurate typist.

Early responses to ChatGPT have been largely Luddite: critics have warned that its arrival means the end of high school English, the demise of the college essay and so on. But remember that the Luddites were highly skilled weavers who commanded high prices for their products; they could see that newfangled mechanized looms would produce cheap fabrics that would push good weavers out of the market. ChatGPT, with sufficient tweaks, could do just that to educators and other knowledge workers.

Having spent 40 years trying to teach my students how to write, I have mixed feelings about this prospect. But it wouldn’t be the first time that a technological advancement has resulted in the atrophy of a human mental skill.

Writing arguably reduced our ability to memorize — and to speak with memorable and persuasive coherence. …

Writing and other technological “advances” have made us what we are today — powerful, but also powerfully dangerous to ourselves and our world. If we can just think through the implications of ChatGPT, we may create companions and mentors that are not so much demonic as the angels of our better nature.

More than writing: emergent behaviour

The ChatGPT story extends further than writing and chatting. From a March 6, 2023 article by Stephen Ornes for Quanta Magazine, Note: Links have been removed,

What movie do these emojis describe?

That prompt was one of 204 tasks chosen last year to test the ability of various large language models (LLMs) — the computational engines behind AI chatbots such as ChatGPT. The simplest LLMs produced surreal responses. “The movie is a movie about a man who is a man who is a man,” one began. Medium-complexity models came closer, guessing The Emoji Movie. But the most complex model nailed it in one guess: Finding Nemo.

“Despite trying to expect surprises, I’m surprised at the things these models can do,” said Ethan Dyer, a computer scientist at Google Research who helped organize the test. It’s surprising because these models supposedly have one directive: to accept a string of text as input and predict what comes next, over and over, based purely on statistics. Computer scientists anticipated that scaling up would boost performance on known tasks, but they didn’t expect the models to suddenly handle so many new, unpredictable ones.

“That language models can do these sort of things was never discussed in any literature that I’m aware of,” said Rishi Bommasani, a computer scientist at Stanford University. Last year, he helped compile a list of dozens of emergent behaviors [emphasis mine], including several identified in Dyer’s project. That list continues to grow.

Now, researchers are racing not only to identify additional emergent abilities but also to figure out why and how they occur at all — in essence, to try to predict unpredictability. Understanding emergence could reveal answers to deep questions around AI and machine learning in general, like whether complex models are truly doing something new or just getting really good at statistics. It could also help researchers harness potential benefits and curtail emergent risks.

Biologists, physicists, ecologists and other scientists use the term “emergent” to describe self-organizing, collective behaviors that appear when a large collection of things acts as one. Combinations of lifeless atoms give rise to living cells; water molecules create waves; murmurations of starlings swoop through the sky in changing but identifiable patterns; cells make muscles move and hearts beat. Critically, emergent abilities show up in systems that involve lots of individual parts. But researchers have only recently been able to document these abilities in LLMs as those models have grown to enormous sizes.

But the debut of LLMs also brought something truly unexpected. Lots of somethings. With the advent of models like GPT-3, which has 175 billion parameters — or Google’s PaLM, which can be scaled up to 540 billion — users began describing more and more emergent behaviors. One DeepMind engineer even reported being able to convince ChatGPT that it was a Linux terminal and getting it to run some simple mathematical code to compute the first 10 prime numbers. Remarkably, it could finish the task faster than the same code running on a real Linux machine.

As with the movie emoji task, researchers had no reason to think that a language model built to predict text would convincingly imitate a computer terminal. Many of these emergent behaviors illustrate “zero-shot” or “few-shot” learning, which describes an LLM’s ability to solve problems it has never — or rarely — seen before. This has been a long-time goal in artificial intelligence research, Ganguli [Deep Ganguli, a computer scientist at the AI startup Anthropic] said. Showing that GPT-3 could solve problems without any explicit training data in a zero-shot setting, he said, “led me to drop what I was doing and get more involved.”

There is an obvious problem with asking these models to explain themselves: They are notorious liars. [emphasis mine] “We’re increasingly relying on these models to do basic work,” Ganguli said, “but I do not just trust these. I check their work.” As one of many amusing examples, in February [2023] Google introduced its AI chatbot, Bard. The blog post announcing the new tool shows Bard making a factual error.

If you have time, I recommend reading Omes’s March 6, 2023 article.

The panic

Perhaps not entirely unrelated to current developments, there was this announcement in a May 1, 2023 article by Hannah Alberga for CTV (Canadian Television Network) news, Note: Links have been removed,

Toronto’s pioneer of artificial intelligence quits Google to openly discuss dangers of AI

Geoffrey Hinton, professor at the University of Toronto and the “godfather” of deep learning – a field of artificial intelligence that mimics the human brain – announced his departure from the company on Monday [May 1, 2023] citing the desire to freely discuss the implications of deep learning and artificial intelligence, and the possible consequences if it were utilized by “bad actors.”

Hinton, a British-Canadian computer scientist, is best-known for a series of deep neural network breakthroughs that won him, Yann LeCun and Yoshua Bengio the 2018 Turing Award, known as the Nobel Prize of computing. 

Hinton has been invested in the now-hot topic of artificial intelligence since its early stages. In 1970, he got a Bachelor of Arts in experimental psychology from Cambridge, followed by his Ph.D. in artificial intelligence in Edinburgh, U.K. in 1978.

He joined Google after spearheading a major breakthrough with two of his graduate students at the University of Toronto in 2012, in which the team uncovered and built a new method of artificial intelligence: neural networks. The team’s first neural network was  incorporated and sold to Google for $44 million.

Neural networks are a method of deep learning that effectively teaches computers how to learn the way humans do by analyzing data, paving the way for machines to classify objects and understand speech recognition.

There’s a bit more from Hinton in a May 3, 2023 article by Sheena Goodyear for the Canadian Broadcasting Corporation’s (CBC) radio programme, As It Happens (the 10 minute radio interview is embedded in the article), Note: A link has been removed,

There was a time when Geoffrey Hinton thought artificial intelligence would never surpass human intelligence — at least not within our lifetimes.

Nowadays, he’s not so sure.

“I think that it’s conceivable that this kind of advanced intelligence could just take over from us,” the renowned British-Canadian computer scientist told As It Happens host Nil Köksal. “It would mean the end of people.”

For the last decade, he [Geoffrey Hinton] divided his career between teaching at the University of Toronto and working for Google’s deep-learning artificial intelligence team. But this week, he announced his resignation from Google in an interview with the New York Times.

Now Hinton is speaking out about what he fears are the greatest dangers posed by his life’s work, including governments using AI to manipulate elections or create “robot soldiers.”

But other experts in the field of AI caution against his visions of a hypothetical dystopian future, saying they generate unnecessary fear, distract from the very real and immediate problems currently posed by AI, and allow bad actors to shirk responsibility when they wield AI for nefarious purposes. 

Ivana Bartoletti, founder of the Women Leading in AI Network, says dwelling on dystopian visions of an AI-led future can do us more harm than good. 

“It’s important that people understand that, to an extent, we are at a crossroads,” said Bartoletti, chief privacy officer at the IT firm Wipro.

“My concern about these warnings, however, is that we focus on the sort of apocalyptic scenario, and that takes us away from the risks that we face here and now, and opportunities to get it right here and now.”

Ziv Epstein, a PhD candidate at the Massachusetts Institute of Technology who studies the impacts of technology on society, says the problems posed by AI are very real, and he’s glad Hinton is “raising the alarm bells about this thing.”

“That being said, I do think that some of these ideas that … AI supercomputers are going to ‘wake up’ and take over, I personally believe that these stories are speculative at best and kind of represent sci-fi fantasy that can monger fear” and distract from more pressing issues, he said.

He especially cautions against language that anthropomorphizes — or, in other words, humanizes — AI.

“It’s absolutely possible I’m wrong. We’re in a period of huge uncertainty where we really don’t know what’s going to happen,” he [Hinton] said.

Don Pittis in his May 4, 2022 business analysis for CBC news online offers a somewhat jaundiced view of Hinton’s concern regarding AI, Note: Links have been removed,

As if we needed one more thing to terrify us, the latest warning from a University of Toronto scientist considered by many to be the founding intellect of artificial intelligence, adds a new layer of dread.

Others who have warned in the past that thinking machines are a threat to human existence seem a little miffed with the rock-star-like media coverage Geoffrey Hinton, billed at a conference this week as the Godfather of AI, is getting for what seems like a last minute conversion. Others say Hinton’s authoritative voice makes a difference.

Not only did Hinton tell an audience of experts at Wednesday’s [May 3, 2023] EmTech Digital conference that humans will soon be supplanted by AI — “I think it’s serious and fairly close.” — he said that due to national and business competition, there is no obvious way to prevent it.

“What we want is some way of making sure that even if they’re smarter than us, they’re going to do things that are beneficial,” said Hinton on Wednesday [May 3, 2023] as he explained his change of heart in detailed technical terms. 

“But we need to try and do that in a world where there’s bad actors who want to build robot soldiers that kill people and it seems very hard to me.”

“I wish I had a nice and simple solution I could push, but I don’t,” he said. “It’s not clear there is a solution.”

So when is all this happening?

“In a few years time they may be significantly more intelligent than people,” he told Nil Köksal on CBC Radio’s As It Happens on Wednesday [May 3, 2023].

While he may be late to the party, Hinton’s voice adds new clout to growing anxiety that artificial general intelligence, or AGI, has now joined climate change and nuclear Armageddon as ways for humans to extinguish themselves.

But long before that final day, he worries that the new technology will soon begin to strip away jobs and lead to a destabilizing societal gap between rich and poor that current politics will be unable to solve.

The EmTech Digital conference is a who’s who of AI business and academia, fields which often overlap. Most other participants at the event were not there to warn about AI like Hinton, but to celebrate the explosive growth of AI research and business.

As one expert I spoke to pointed out, the growth in AI is exponential and has been for a long time. But even knowing that, the increase in the dollar value of AI to business caught the sector by surprise.

Eight years ago when I wrote about the expected increase in AI business, I quoted the market intelligence group Tractica that AI spending would “be worth more than $40 billion in the coming decade,” which sounded like a lot at the time. It appears that was an underestimate.

“The global artificial intelligence market size was valued at $428 billion U.S. in 2022,” said an updated report from Fortune Business Insights. “The market is projected to grow from $515.31 billion U.S. in 2023.”  The estimate for 2030 is more than $2 trillion. 

This week the new Toronto AI company Cohere, where Hinton has a stake of his own, announced it was “in advanced talks” to raise $250 million. The Canadian media company Thomson Reuters said it was planning “a deeper investment in artificial intelligence.” IBM is expected to “pause hiring for roles that could be replaced with AI.” The founders of Google DeepMind and LinkedIn have launched a ChatGPT competitor called Pi.

And that was just this week.

“My one hope is that, because if we allow it to take over it will be bad for all of us, we could get the U.S. and China to agree, like we did with nuclear weapons,” said Hinton. “We’re all the in same boat with respect to existential threats, so we all ought to be able to co-operate on trying to stop it.”

Interviewer and moderator Will Douglas Heaven, an editor at MIT Technology Review finished Hinton’s sentence for him: “As long as we can make some money on the way.”

Hinton has attracted some criticism himself. Wilfred Chan writing for Fast Company has two articles, “‘I didn’t see him show up’: Ex-Googlers blast ‘AI godfather’ Geoffrey Hinton’s silence on fired AI experts” on May 5, 2023, Note: Links have been removed,

Geoffrey Hinton, the 75-year-old computer scientist known as the “Godfather of AI,” made headlines this week after resigning from Google to sound the alarm about the technology he helped create. In a series of high-profile interviews, the machine learning pioneer has speculated that AI will surpass humans in intelligence and could even learn to manipulate or kill people on its own accord.

But women who for years have been speaking out about AI’s problems—even at the expense of their jobs—say Hinton’s alarmism isn’t just opportunistic but also overshadows specific warnings about AI’s actual impacts on marginalized people.

“It’s disappointing to see this autumn-years redemption tour [emphasis mine] from someone who didn’t really show up” for other Google dissenters, says Meredith Whittaker, president of the Signal Foundation and an AI researcher who says she was pushed out of Google in 2019 in part over her activism against the company’s contract to build machine vision technology for U.S. military drones. (Google has maintained that Whittaker chose to resign.)

Another prominent ex-Googler, Margaret Mitchell, who co-led the company’s ethical AI team, criticized Hinton for not denouncing Google’s 2020 firing of her coleader Timnit Gebru, a leading researcher who had spoken up about AI’s risks for women and people of color.

“This would’ve been a moment for Dr. Hinton to denormalize the firing of [Gebru],” Mitchell tweeted on Monday. “He did not. This is how systemic discrimination works.”

Gebru, who is Black, was sacked in 2020 after refusing to scrap a research paper she coauthored about the risks of large language models to multiply discrimination against marginalized people. …

… An open letter in support of Gebru was signed by nearly 2,700 Googlers in 2020, but Hinton wasn’t one of them. 

Instead, Hinton has used the spotlight to downplay Gebru’s voice. In an appearance on CNN Tuesday [May 2, 2023], for example, he dismissed a question from Jake Tapper about whether he should have stood up for Gebru, saying her ideas “aren’t as existentially serious as the idea of these things getting more intelligent than us and taking over.” [emphasis mine]

Gebru has been mentioned here a few times. She’s mentioned in passing in a June 23, 2022 posting “Racist and sexist robots have flawed AI” and in a little more detail in an August 30, 2022 posting “Should AI algorithms get patents for their inventions and is anyone talking about copyright for texts written by AI algorithms?” scroll down to the ‘Consciousness and ethical AI’ subhead

Chan has another Fast Company article investigating AI issues also published on May 5, 2023, “Researcher Meredith Whittaker says AI’s biggest risk isn’t ‘consciousness’—it’s the corporations that control them.”

The last two existential AI panics

The term “autumn-years redemption tour”is striking and while the reference to age could be viewed as problematic, it also hints at the money, honours, and acknowledgement that Hinton has enjoyed as an eminent scientist. I’ve covered two previous panics set off by eminent scientists. “Existential risk” is the title of my November 26, 2012 posting which highlights Martin Rees’ efforts to found the Centre for Existential Risk at the University of Cambridge.

Rees is a big deal. From his Wikipedia entry, Note: Links have been removed,

Martin John Rees, Baron Rees of Ludlow OM FRS FREng FMedSci FRAS HonFInstP[10][2] (born 23 June 1942) is a British cosmologist and astrophysicist.[11] He is the fifteenth Astronomer Royal, appointed in 1995,[12][13][14] and was Master of Trinity College, Cambridge, from 2004 to 2012 and President of the Royal Society between 2005 and 2010.[15][16][17][18][19][20]

The Centre for Existential Risk can be found here online (it is located at the University of Cambridge). Interestingly, Hinton who was born in December 1947 will be giving a lecture “Digital versus biological intelligence: Reasons for concern about AI” in Cambridge on May 25, 2023.

The next panic was set off by Stephen Hawking (1942 – 2018; also at the University of Cambridge, Wikipedia entry) a few years before he died. (Note: Rees, Hinton, and Hawking were all born within five years of each other and all have/had ties to the University of Cambridge. Interesting coincidence, eh?) From a January 9, 2015 article by Emily Chung for CBC news online,

Machines turning on their creators has been a popular theme in books and movies for decades, but very serious people are starting to take the subject very seriously. Physicist Stephen Hawking says, “the development of full artificial intelligence could spell the end of the human race.” Tesla Motors and SpaceX founder Elon Musk suggests that AI is probably “our biggest existential threat.”

Artificial intelligence experts say there are good reasons to pay attention to the fears expressed by big minds like Hawking and Musk — and to do something about it while there is still time.

Hawking made his most recent comments at the beginning of December [2014], in response to a question about an upgrade to the technology he uses to communicate, He relies on the device because he has amyotrophic lateral sclerosis, a degenerative disease that affects his ability to move and speak.

Popular works of science fiction – from the latest Terminator trailer, to the Matrix trilogy, to Star Trek’s borg – envision that beyond that irreversible historic event, machines will destroy, enslave or assimilate us, says Canadian science fiction writer Robert J. Sawyer.

Sawyer has written about a different vision of life beyond singularity [when machines surpass humans in general intelligence,] — one in which machines and humans work together for their mutual benefit. But he also sits on a couple of committees at the Lifeboat Foundation, a non-profit group that looks at future threats to the existence of humanity, including those posed by the “possible misuse of powerful technologies” such as AI. He said Hawking and Musk have good reason to be concerned.

To sum up, the first panic was in 2012, the next in 2014/15, and the latest one began earlier this year (2023) with a letter. A March 29, 2023 Thompson Reuters news item on CBC news online provides information on the contents,

Elon Musk and a group of artificial intelligence experts and industry executives are calling for a six-month pause in developing systems more powerful than OpenAI’s newly launched GPT-4, in an open letter citing potential risks to society and humanity.

Earlier this month, Microsoft-backed OpenAI unveiled the fourth iteration of its GPT (Generative Pre-trained Transformer) AI program, which has wowed users with its vast range of applications, from engaging users in human-like conversation to composing songs and summarizing lengthy documents.

The letter, issued by the non-profit Future of Life Institute and signed by more than 1,000 people including Musk, called for a pause on advanced AI development until shared safety protocols for such designs were developed, implemented and audited by independent experts.

Co-signatories included Stability AI CEO Emad Mostaque, researchers at Alphabet-owned DeepMind, and AI heavyweights Yoshua Bengio, often referred to as one of the “godfathers of AI,” and Stuart Russell, a pioneer of research in the field.

According to the European Union’s transparency register, the Future of Life Institute is primarily funded by the Musk Foundation, as well as London-based effective altruism group Founders Pledge, and Silicon Valley Community Foundation.

The concerns come as EU police force Europol on Monday {March 27, 2023] joined a chorus of ethical and legal concerns over advanced AI like ChatGPT, warning about the potential misuse of the system in phishing attempts, disinformation and cybercrime.

Meanwhile, the U.K. government unveiled proposals for an “adaptable” regulatory framework around AI.

The government’s approach, outlined in a policy paper published on Wednesday [March 29, 2023], would split responsibility for governing artificial intelligence (AI) between its regulators for human rights, health and safety, and competition, rather than create a new body dedicated to the technology.

The engineers have chimed in, from an April 7, 2023 article by Margo Anderson for the IEEE (institute of Electrical and Electronics Engineers) Spectrum magazine, Note: Links have been removed,

The open letter [published March 29, 2023], titled “Pause Giant AI Experiments,” was organized by the nonprofit Future of Life Institute and signed by more than 27,565 people (as of 8 May). It calls for cessation of research on “all AI systems more powerful than GPT-4.”

It’s the latest of a host of recent “AI pause” proposals including a suggestion by Google’s François Chollet of a six-month “moratorium on people overreacting to LLMs” in either direction.

In the news media, the open letter has inspired straight reportage, critical accounts for not going far enough (“shut it all down,” Eliezer Yudkowsky wrote in Time magazine), as well as critical accounts for being both a mess and an alarmist distraction that overlooks the real AI challenges ahead.

IEEE members have expressed a similar diversity of opinions.

There was an earlier open letter in January 2015 according to Wikipedia’s “Open Letter on Artificial Intelligence” entry, Note: Links have been removed,

In January 2015, Stephen Hawking, Elon Musk, and dozens of artificial intelligence experts[1] signed an open letter on artificial intelligence calling for research on the societal impacts of AI. The letter affirmed that society can reap great potential benefits from artificial intelligence, but called for concrete research on how to prevent certain potential “pitfalls”: artificial intelligence has the potential to eradicate disease and poverty, but researchers must not create something which is unsafe or uncontrollable.[1] The four-paragraph letter, titled “Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter”, lays out detailed research priorities in an accompanying twelve-page document.

As for ‘Mr. ChatGPT’ or Sam Altman, CEO of OpenAI, while he didn’t sign the March 29, 2023 letter, he appeared before US Congress suggesting AI needs to be regulated according to May 16, 2023 news article by Mohar Chatterjee for Politico.

You’ll notice I’ve arbitrarily designated three AI panics by assigning their origins to eminent scientists. In reality, these concerns rise and fall in ways that don’t allow for such a tidy analysis. As Chung notes, science fiction regularly addresses this issue. For example, there’s my October 16, 2013 posting, “Wizards & Robots: a comic book encourages study in the sciences and maths and discussions about existential risk.” By the way, will.i.am (of the Black Eyed Peas band was involved in the comic book project and he us a longtime supporter of STEM (science, technology, engineering, and mathematics) initiatives.

Finally (but not quite)

Puzzling, isn’t it? I’m not sure we’re asking the right questions but it’s encouraging to see that at least some are being asked.

Dr. Andrew Maynard in a May 12, 2023 essay for The Conversation (h/t May 12, 2023 item on phys.org) notes that ‘Luddites’ questioned technology’s inevitable progress and were vilified for doing so, Note: Links have been removed,

The term “Luddite” emerged in early 1800s England. At the time there was a thriving textile industry that depended on manual knitting frames and a skilled workforce to create cloth and garments out of cotton and wool. But as the Industrial Revolution gathered momentum, steam-powered mills threatened the livelihood of thousands of artisanal textile workers.

Faced with an industrialized future that threatened their jobs and their professional identity, a growing number of textile workers turned to direct action. Galvanized by their leader, Ned Ludd, they began to smash the machines that they saw as robbing them of their source of income.

It’s not clear whether Ned Ludd was a real person, or simply a figment of folklore invented during a period of upheaval. But his name became synonymous with rejecting disruptive new technologies – an association that lasts to this day.

Questioning doesn’t mean rejecting

Contrary to popular belief, the original Luddites were not anti-technology, nor were they technologically incompetent. Rather, they were skilled adopters and users of the artisanal textile technologies of the time. Their argument was not with technology, per se, but with the ways that wealthy industrialists were robbing them of their way of life

In December 2015, Stephen Hawking, Elon Musk and Bill Gates were jointly nominated for a “Luddite Award.” Their sin? Raising concerns over the potential dangers of artificial intelligence.

The irony of three prominent scientists and entrepreneurs being labeled as Luddites underlines the disconnect between the term’s original meaning and its more modern use as an epithet for anyone who doesn’t wholeheartedly and unquestioningly embrace technological progress.

Yet technologists like Musk and Gates aren’t rejecting technology or innovation. Instead, they’re rejecting a worldview that all technological advances are ultimately good for society. This worldview optimistically assumes that the faster humans innovate, the better the future will be.

In an age of ChatGPT, gene editing and other transformative technologies, perhaps we all need to channel the spirit of Ned Ludd as we grapple with how to ensure that future technologies do more good than harm.

In fact, “Neo-Luddites” or “New Luddites” is a term that emerged at the end of the 20th century.

In 1990, the psychologist Chellis Glendinning published an essay titled “Notes toward a Neo-Luddite Manifesto.”

Then there are the Neo-Luddites who actively reject modern technologies, fearing that they are damaging to society. New York City’s Luddite Club falls into this camp. Formed by a group of tech-disillusioned Gen-Zers, the club advocates the use of flip phones, crafting, hanging out in parks and reading hardcover or paperback books. Screens are an anathema to the group, which sees them as a drain on mental health.

I’m not sure how many of today’s Neo-Luddites – whether they’re thoughtful technologists, technology-rejecting teens or simply people who are uneasy about technological disruption – have read Glendinning’s manifesto. And to be sure, parts of it are rather contentious. Yet there is a common thread here: the idea that technology can lead to personal and societal harm if it is not developed responsibly.

Getting back to where this started with nonhuman authors, Amelia Eqbal has written up an informal transcript of a March 16, 2023 CBC radio interview (radio segment is embedded) about ChatGPT-4 (the latest AI chatbot from OpenAI) between host Elamin Abdelmahmoud and tech journalist, Alyssa Bereznak.

I was hoping to add a little more Canadian content, so in March 2023 and again in April 2023, I sent a question about whether there were any policies regarding nonhuman or AI authors to Kim Barnhardt at the Canadian Medical Association Journal (CMAJ). To date, there has been no reply but should one arrive, I will place it here.

In the meantime, I have this from Canadian writer, Susan Baxter in her May 15, 2023 blog posting “Coming soon: Robot Overlords, Sentient AI and more,”

The current threat looming (Covid having been declared null and void by the WHO*) is Artificial Intelligence (AI) which, we are told, is becoming too smart for its own good and will soon outsmart humans. Then again, given some of the humans I’ve met along the way that wouldn’t be difficult.

All this talk of scary-boo AI seems to me to have become the worst kind of cliché, one that obscures how our lives have become more complicated and more frustrating as apps and bots and cyber-whatsits take over.

The trouble with clichés, as Alain de Botton wrote in How Proust Can Change Your Life, is not that they are wrong or contain false ideas but more that they are “superficial articulations of good ones”. Cliches are oversimplifications that become so commonplace we stop noticing the more serious subtext. (This is rife in medicine where metaphors such as talk of “replacing” organs through transplants makes people believe it’s akin to changing the oil filter in your car. Or whatever it is EV’s have these days that needs replacing.)

Should you live in Vancouver (Canada) and are attending a May 28, 2023 AI event, you may want to read Susan Baxter’s piece as a counterbalance to, “Discover the future of artificial intelligence at this unique AI event in Vancouver,” a May 19, 2023 sponsored content by Katy Brennan for the Daily Hive,

If you’re intrigued and eager to delve into the rapidly growing field of AI, you’re not going to want to miss this unique Vancouver event.

On Sunday, May 28 [2023], a Multiplatform AI event is coming to the Vancouver Playhouse — and it’s set to take you on a journey into the future of artificial intelligence.

The exciting conference promises a fusion of creativity, tech innovation, and thought–provoking insights, with talks from renowned AI leaders and concept artists, who will share their experiences and opinions.

Guests can look forward to intense discussions about AI’s pros and cons, hear real-world case studies, and learn about the ethical dimensions of AI, its potential threats to humanity, and the laws that govern its use.

Live Q&A sessions will also be held, where leading experts in the field will address all kinds of burning questions from attendees. There will also be a dynamic round table and several other opportunities to connect with industry leaders, pioneers, and like-minded enthusiasts. 

This conference is being held at The Playhouse, 600 Hamilton Street, from 11 am to 7:30 pm, ticket prices range from $299 to $349 to $499 (depending on when you make your purchase, From the Multiplatform AI Conference homepage,

Event Speakers

Max Sills
General Counsel at Midjourney

From Jan 2022 – present (Advisor – now General Counsel) – Midjourney – An independent research lab exploring new mediums of thought and expanding the imaginative powers of the human species (SF) Midjourney – a generative artificial intelligence program and service created and hosted by a San Francisco-based independent research lab Midjourney, Inc. Midjourney generates images from natural language descriptions, called “prompts”, similar to OpenAI’s DALL-E and Stable Diffusion. For now the company uses Discord Server as a source of service and, with huge 15M+ members, is the biggest Discord server in the world. In the two-things-at-once department, Max Sills also known as an owner of Open Advisory Services, firm which is set up to help small and medium tech companies with their legal needs (managing outside counsel, employment, carta, TOS, privacy). Their clients are enterprise level, medium companies and up, and they are here to help anyone on open source and IP strategy. Max is an ex-counsel at Block, ex-general manager of the Crypto Open Patent Alliance. Prior to that Max led Google’s open source legal group for 7 years.

So, the first speaker listed is a lawyer associated with Midjourney, a highly controversial generative artificial intelligence programme used to generate images. According to their entry on Wikipedia, the company is being sued, Note: Links have been removed,

On January 13, 2023, three artists – Sarah Andersen, Kelly McKernan, and Karla Ortiz – filed a copyright infringement lawsuit against Stability AI, Midjourney, and DeviantArt, claiming that these companies have infringed the rights of millions of artists, by training AI tools on five billion images scraped from the web, without the consent of the original artists.[32]

My October 24, 2022 posting highlights some of the issues with generative image programmes and Midjourney is mentioned throughout.

As I noted earlier, I’m glad to see more thought being put into the societal impact of AI and somewhat disconcerted by the hyperbole from the like of Geoffrey Hinton and the like of Vancouver’s Multiplatform AI conference organizers. Mike Masnick put it nicely in his May 24, 2023 posting on TechDirt (Note 1: I’ve taken a paragraph out of context, his larger issue is about proposals for legislation; Note 2: Links have been removed),

Honestly, this is partly why I’ve been pretty skeptical about the “AI Doomers” who keep telling fanciful stories about how AI is going to kill us all… unless we give more power to a few elite people who seem to think that it’s somehow possible to stop AI tech from advancing. As I noted last month, it is good that some in the AI space are at least conceptually grappling with the impact of what they’re building, but they seem to be doing so in superficial ways, focusing only on the sci-fi dystopian futures they envision, and not things that are legitimately happening today from screwed up algorithms.

For anyone interested in the Canadian government attempts to legislate AI, there’s my May 1, 2023 posting, “Canada, AI regulation, and the second reading of the Digital Charter Implementation Act, 2022 (Bill C-27).”

Addendum (June 1, 2023)

Another statement warning about runaway AI was issued on Tuesday, May 30, 2023. This was far briefer than the previous March 2023 warning, from the Center for AI Safety’s “Statement on AI Risk” webpage,

Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war [followed by a list of signatories] …

Vanessa Romo’s May 30, 2023 article (with contributions from Bobby Allyn) for NPR ([US] National Public Radio) offers an overview of both warnings. Rae Hodge’s May 31, 2023 article for Salon offers a more critical view, Note: Links have been removed,

The artificial intelligence world faced a swarm of stinging backlash Tuesday morning, after more than 350 tech executives and researchers released a public statement declaring that the risks of runaway AI could be on par with those of “nuclear war” and human “extinction.” Among the signatories were some who are actively pursuing the profitable development of the very products their statement warned about — including OpenAI CEO Sam Altman and Google DeepMind CEO Demis Hassabis.

“Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war,” the statement from the non-profit Center for AI Safety said.

But not everyone was shaking in their boots, especially not those who have been charting AI tech moguls’ escalating use of splashy language — and those moguls’ hopes for an elite global AI governance board.

TechCrunch’s Natasha Lomas, whose coverage has been steeped in AI, immediately unravelled the latest panic-push efforts with a detailed rundown of the current table stakes for companies positioning themselves at the front of the fast-emerging AI industry.

“Certainly it speaks volumes about existing AI power structures that tech execs at AI giants including OpenAI, DeepMind, Stability AI and Anthropic are so happy to band and chatter together when it comes to publicly amplifying talk of existential AI risk. And how much more reticent to get together to discuss harms their tools can be seen causing right now,” Lomas wrote.

“Instead of the statement calling for a development pause, which would risk freezing OpenAI’s lead in the generative AI field, it lobbies policymakers to focus on risk mitigation — doing so while OpenAI is simultaneously crowdfunding efforts to shape ‘democratic processes for steering AI,'” Lomas added.

The use of scary language and fear as a marketing tool has a long history in tech. And, as the LA Times’ Brian Merchant pointed out in an April column, OpenAI stands to profit significantly from a fear-driven gold rush of enterprise contracts.

“[OpenAI is] almost certainly betting its longer-term future on more partnerships like the one with Microsoft and enterprise deals serving large companies,” Merchant wrote. “That means convincing more corporations that if they want to survive the coming AI-led mass upheaval, they’d better climb aboard.”

Fear, after all, is a powerful sales tool.

Romo’s May 30, 2023 article for NPR offers a good overview and, if you have the time, I recommend reading Hodge’s May 31, 2023 article for Salon in its entirety.

*ETA June 8, 2023: This sentence “What follows the ‘nonhuman authors’ is essentially a survey of situation/panic.” was added to the introductory paragraph at the beginning of this post.

Kempner Institute for the Study of Natural and Artificial Intelligence launched at Harvard University and University of Manchester pushes the boundaries of smart robotics and AI

Before getting to the two news items, it might be a good idea to note that ‘artificial intelligence (AI)’ and ‘robot’ are not synonyms although they are often used that way, even by people who should know better. (sigh … I do it too)

A robot may or may not be animated with artificial intelligence while artificial intelligence algorithms may be installed on a variety of devices such as a phone or a computer or a thermostat or a … .

It’s something to bear in mind when reading about the two new institutions being launched. Now, on to Harvard University.

Kempner Institute for the Study of Natural and Artificial Intelligence

A September 23, 2022 Chan Zuckerberg Initiative (CZI) news release (also on EurekAlert) announces a symposium to launch a new institute close to Mark Zuckerberg’s heart,

On Thursday [September 22, 2022], leadership from the Chan Zuckerberg Initiative (CZI) and Harvard University celebrated the launch of the Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University with a symposium on Harvard’s campus. Speakers included CZI Head of Science Stephen Quake, President of Harvard University Lawrence Bacow, Provost of Harvard University Alan Garber, and Kempner Institute co-directors Bernardo Sabatini and Sham Kakade. The event also included remarks and panels from industry leaders in science, technology, and artificial intelligence, including Bill Gates, Eric Schmidt, Andy Jassy, Daniel Huttenlocher, Sam Altman, Joelle Pineau, Sangeeta Bhatia, and Yann LeCun, among many others.

The Kempner Institute will seek to better understand the basis of intelligence in natural and artificial systems. Its bold premise is that the two fields are intimately interconnected; the next generation of AI will require the same principles that our brains use for fast, flexible natural reasoning, and understanding how our brains compute and reason requires theories developed for AI. The Kempner Institute will study AI systems, including artificial neural networks, to develop both principled theories [emphasis mine] and a practical understanding of how these systems operate and learn. It will also focus on research topics such as learning and memory, perception and sensation, brain function, and metaplasticity. The Institute will recruit and train future generations of researchers from undergraduates and graduate students to post-docs and faculty — actively recruiting from underrepresented groups at every stage of the pipeline — to study intelligence from biological, cognitive, engineering, and computational perspectives.

CZI Co-Founder and Co-CEO Mark Zuckerberg [chairman and chief executive officer of Meta/Facebook] said: “The Kempner Institute will be a one-of-a-kind institute for studying intelligence and hopefully one that helps us discover what intelligent systems really are, how they work, how they break and how to repair them. There’s a lot of exciting implications because once you understand how something is supposed to work and how to repair it once it breaks, you can apply that to the broader mission the Chan Zuckerberg Initiative has to empower scientists to help cure, prevent or manage all diseases.”

CZI Co-Founder and Co-CEO Priscilla Chan said: “Just attending this school meant the world to me. But to stand on this stage and to be able to give something back is truly a dream come true … All of this progress starts with building one fundamental thing: a Kempner community that’s diverse, multi-disciplinary and multi-generational, because incredible ideas can come from anyone. If you bring together people from all different disciplines to look at a problem and give them permission to articulate their perspective, you might start seeing insights or solutions in a whole different light. And those new perspectives lead to new insights and discoveries and generate new questions that can lead an entire field to blossom. So often, that momentum is what breaks the dam and tears down old orthodoxies, unleashing new floods of new ideas that allow us to progress together as a society.”

CZI Head of Science Stephen Quake said: “It’s an honor to partner with Harvard in building this extraordinary new resource for students and science. This is a once-in-a-generation moment for life sciences and medicine. We are living in such an extraordinary and exciting time for science. Many breakthrough discoveries are going to happen not only broadly but right here on this campus and at this institute.”

CZI’s 10-year vision is to advance research and develop technologies to observe, measure, and analyze any biological process within the human body — across spatial scales and in real time. CZI’s goal is to accelerate scientific progress by funding scientific research to advance entire fields; working closely with scientists and engineers at partner institutions like the Chan Zuckerberg Biohub and Chan Zuckerberg Institute for Advanced Biological Imaging to do the research that can’t be done in conventional environments; and building and democratizing next-generation software and hardware tools to drive biological insights and generate more accurate and biologically important sources of data.

President of Harvard University Lawrence Bacow said: “Here we are with this incredible opportunity that Priscilla Chan and Mark Zuckerberg have given us to imagine taking what we know about the brain, neuroscience and how to model intelligence and putting them together in ways that can inform both, and can truly advance our understanding of intelligence from multiple perspectives.”

Kempner Institute Co-Director and Gordon McKay Professor of Computer Science and of Statistics at the Harvard John A. Paulson School of Engineering and Applied Sciences Sham Kakade said: “Now we begin assembling a world-leading research and educational program at Harvard that collectively tries to understand the fundamental mechanisms of intelligence and seeks to apply these new technologies for the benefit of humanity … We hope to create a vibrant environment for all of us to engage in broader research questions … We want to train the next generation of leaders because those leaders will go on to do the next set of great things.”

Kempner Institute Co-Director and the Alice and Rodman W. Moorhead III Professor of Neurobiology at Harvard Medical School Bernardo Sabatini said: “We’re blending research, education and computation to nurture, raise up and enable any scientist who is interested in unraveling the mysteries of the brain. This field is a nascent and interdisciplinary one, so we’re going to have to teach neuroscience to computational biologists, who are going to have to teach machine learning to cognitive scientists and math to biologists. We’re going to do whatever is necessary to help each individual thrive and push the field forward … Success means we develop mathematical theories that explain how our brains compute and learn, and these theories should be specific enough to be testable and useful enough to start to explain diseases like schizophrenia, dyslexia or autism.”

About the Chan Zuckerberg Initiative

The Chan Zuckerberg Initiative was founded in 2015 to help solve some of society’s toughest challenges — from eradicating disease and improving education, to addressing the needs of our communities. Through collaboration, providing resources and building technology, our mission is to help build a more inclusive, just and healthy future for everyone. For more information, please visit chanzuckerberg.com.

Principled theories, eh. I don’t see a single mention of ethicists or anyone in the social sciences or the humanities or the arts. How are scientists and engineers who have no training in or education in or, even, an introduction to ethics or social impacts or psychology going to manage this?

Mark Zuckerberg’s approach to these issues was something along the lines of “it’s easier to ask for forgiveness than to ask for permission.” I understand there have been changes but it took far too long to recognize the damage let alone attempt to address it.

If you want to gain a little more insight into the Kempner Institute, there’s a December 7, 2021 article by Alvin Powell announcing the institute for the Harvard Gazette,

The institute will be funded by a $500 million gift from Priscilla Chan and Mark Zuckerberg, which was announced Tuesday [December 7, 2021] by the Chan Zuckerberg Initiative. The gift will support 10 new faculty appointments, significant new computing infrastructure, and resources to allow students to flow between labs in pursuit of ideas and knowledge. The institute’s name honors Zuckerberg’s mother, Karen Kempner Zuckerberg, and her parents — Zuckerberg’s grandparents — Sidney and Gertrude Kempner. Chan and Zuckerberg have given generously to Harvard in the past, supporting students, faculty, and researchers in a range of areas, including around public service, literacy, and cures.

“The Kempner Institute at Harvard represents a remarkable opportunity to bring together approaches and expertise in biological and cognitive science with machine learning, statistics, and computer science to make real progress in understanding how the human brain works to improve how we address disease, create new therapies, and advance our understanding of the human body and the world more broadly,” said President Larry Bacow.

Q&A

Bernardo Sabatini and Sham Kakade [Institute co-directors]

GAZETTE: Tell me about the new institute. What is its main reason for being?

SABATINI: The institute is designed to take from two fields and bring them together, hopefully to create something that’s essentially new, though it’s been tried in a couple of places. Imagine that you have over here cognitive scientists and neurobiologists who study the human brain, including the basic biological mechanisms of intelligence and decision-making. And then over there, you have people from computer science, from mathematics and statistics, who study artificial intelligence systems. Those groups don’t talk to each other very much.

We want to recruit from both populations to fill in the middle and to create a new population, through education, through graduate programs, through funding programs — to grow from academic infancy — those equally versed in neuroscience and in AI systems, who can be leaders for the next generation.

Over the millions of years that vertebrates have been evolving, the human brain has developed specializations that are fundamental for learning and intelligence. We need to know what those are to understand their benefits and to ask whether they can make AI systems better. At the same time, as people who study AI and machine learning (ML) develop mathematical theories as to how those systems work and can say that a network of the following structure with the following properties learns by calculating the following function, then we can take those theories and ask, “Is that actually how the human brain works?”

KAKADE: There’s a question of why now? In the technological space, the advancements are remarkable even to me, as a researcher who knows how these things are being made. I think there’s a long way to go, but many of us feel that this is the right time to study intelligence more broadly. You might also ask: Why is this mission unique and why is this institute different from what’s being done in academia and in industry? Academia is good at putting out ideas. Industry is good at turning ideas into reality. We’re in a bit of a sweet spot. We have the scale to study approaches at a very different level: It’s not going to be just individual labs pursuing their own ideas. We may not be as big as the biggest companies, but we can work on the types of problems that they work on, such as having the compute resources to work on large language models. Industry has exciting research, but the spectrum of ideas produced is very different, because they have different objectives.

For the die-hards, there’s a September 23, 2022 article by Clea Simon in Harvard Gazette, which updates the 2021 story,

Next, Manchester, England.

Manchester Centre for Robotics and AI

Robotots take a break at a lab at The University of Manchester – picture courtesy of Marketing Manchester [downloaded from https://www.manchester.ac.uk/discover/news/manchester-ai-summit-aims-to-attract-experts-in-advanced-engineering-and-robotics/]

A November 22, 2022 University of Manchester press release (also on EurekAlert) announces both a meeting and a new centre, Note: Links to the Centre have been retained; all others have been removed,

How humans and super smart robots will live and work together in the future will be among the key issues being scrutinised by experts at a new centre of excellence for AI and autonomous machines based at The University of Manchester.

The Manchester Centre for Robotics and AI will be a new specialist multi-disciplinary centre to explore developments in smart robotics through the lens of artificial intelligence (AI) and autonomous machinery.

The University of Manchester has built a modern reputation of excellence in AI and robotics, partly based on the legacy of pioneering thought leadership begun in this field in Manchester by legendary codebreaker Alan Turing.

Manchester’s new multi-disciplinary centre is home to world-leading research from across the academic disciplines – and this group will hold its first conference on Wednesday, Nov 23, at the University’s new engineering and materials facilities.

A  highlight will be a joint talk by robotics expert Dr Andy Weightman and theologian Dr Scott Midson which is expected to put a spotlight on ‘posthumanism’, a future world where humans won’t be the only highly intelligent decision-makers.

Dr Weightman, who researches home-based rehabilitation robotics for people with neurological impairment, and Dr Midson, who researches theological and philosophical critiques of posthumanism, will discuss how interdisciplinary research can help with the special challenges of rehabilitation robotics – and, ultimately, what it means to be human “in the face of the promises and challenges of human enhancement through robotic and autonomous machines”.

Other topics that the centre will have a focus on will include applications of robotics in extreme environments.

For the past decade, a specialist Manchester team led by Professor Barry Lennox has designed robots to work safely in nuclear decommissioning sites in the UK. A ground-breaking robot called Lyra that has been developed by Professor Lennox’s team – and recently deployed at the Dounreay site in Scotland, the “world’s deepest nuclear clean up site” – has been listed in Time Magazine’s Top 200 innovations of 2022.

Angelo Cangelosi, Professor of Machine Learning and Robotics at Manchester, said the University offers a world-leading position in the field of autonomous systems – a technology that will be an integral part of our future world. 

Professor Cangelosi, co-Director of Manchester’s Centre for Robotics and AI, said: “We are delighted to host our inaugural conference which will provide a special showcase for our diverse academic expertise to design robotics for a variety of real world applications.

“Our research and innovation team are at the interface between robotics, autonomy and AI – and their knowledge is drawn from across the University’s disciplines, including biological and medical sciences – as well the humanities and even theology. [emphases mine]

“This rich diversity offers Manchester a distinctive approach to designing robots and autonomous systems for real world applications, especially when combined with our novel use of AI-based knowledge.”

Delegates will have a chance to observe a series of robots and autonomous machines being demoed at the new conference.

The University of Manchester’s Centre for Robotics and AI will aim to: 

  • design control systems with a focus on bio-inspired solutions to mechatronics, eg the use of biomimetic sensors, actuators and robot platforms; 
  • develop new software engineering and AI methodologies for verification in autonomous systems, with the aim to design trustworthy autonomous systems; 
  • research human-robot interaction, with a pioneering focus on the use of brain-inspired approaches [emphasis mine] to robot control, learning and interaction; and 
  • research the ethics and human-centred robotics issues, for the understanding of the impact of the use of robots and autonomous systems with individuals and society. 

In some ways, the Kempner Institute and the Manchester Centre for Robotics and AI have very similar interests, especially where the brain is concerned. What fascinates me is the Manchester Centre’s inclusion of theologian Dr Scott Midson and the discussion (at the meeting) of ‘posthumanism’. The difference is between actual engagement at the symposium (the centre) and mere mention in a news release (the institute).

I wish the best for both institutions.

Mad, bad, and dangerous to know? Artificial Intelligence at the Vancouver (Canada) Art Gallery (2 of 2): Meditations

Dear friend,

I thought it best to break this up a bit. There are a couple of ‘objects’ still to be discussed but this is mostly the commentary part of this letter to you. (Here’s a link for anyone who stumbled here but missed Part 1.)

Ethics, the natural world, social justice, eeek, and AI

Dorothy Woodend in her March 10, 2022 review for The Tyee) suggests some ethical issues in her critique of the ‘bee/AI collaboration’ and she’s not the only one with concerns. UNESCO (United Nations Educational, Scientific and Cultural Organization) has produced global recommendations for ethical AI (see my March 18, 2022 posting). More recently, there’s “Racist and sexist robots have flawed AI,” a June 23, 2022 posting, where researchers prepared a conference presentation and paper about deeply flawed AI still being used in robots.

Ultimately, the focus is always on humans and Woodend has extended the ethical AI conversation to include insects and the natural world. In short, something less human-centric.

My friend, this reference to the de Young exhibit may seem off topic but I promise it isn’t in more ways than one. The de Young Museum in San Francisco (February 22, 2020 – June 27, 2021) also held and AI and art show called, “Uncanny Valley: Being Human in the Age of AI”), from the exhibitions page,

In today’s AI-driven world, increasingly organized and shaped by algorithms that track, collect, and evaluate our data, the question of what it means to be human [emphasis mine] has shifted. Uncanny Valley is the first major exhibition to unpack this question through a lens of contemporary art and propose new ways of thinking about intelligence, nature, and artifice. [emphasis mine]

Courtesy: de Young Museum [downloaded from https://deyoung.famsf.org/exhibitions/uncanny-valley]

As you can see, it hinted (perhaps?) at an attempt to see beyond human-centric AI. (BTW, I featured this ‘Uncanny Valley’ show in my February 25, 2020 posting where I mentioned Stephanie Dinkins [featured below] and other artists.)

Social justice

While the VAG show doesn’t see much past humans and AI, it does touch on social justice. In particular there’s Pod 15 featuring the Algorithmic Justice League (AJL). The group “combine[s] art and research to illuminate the social implications and harms of AI” as per their website’s homepage.

In Pod 9, Stephanie Dinkins’ video work with a robot (Bina48), which was also part of the de Young Museum ‘Uncanny Valley’ show, addresses some of the same issues.

Still of Stephanie Dinkins, “Conversations with Bina48,” 2014–present. Courtesy of the artist [downloaded from https://deyoung.famsf.org/stephanie-dinkins-conversations-bina48-0]

From the the de Young Museum’s Stephanie Dinkins “Conversations with Bina48” April 23, 2020 article by Janna Keegan (Dinkins submitted the same work you see at the VAG show), Note: Links have been removed,

Transdisciplinary artist and educator Stephanie Dinkins is concerned with fostering AI literacy. The central thesis of her social practice is that AI, the internet, and other data-based technologies disproportionately impact people of color, LGBTQ+ people, women, and disabled and economically disadvantaged communities—groups rarely given a voice in tech’s creation. Dinkins strives to forge a more equitable techno-future by generating AI that includes the voices of multiple constituencies …

The artist’s ongoing Conversations with Bina48 takes the form of a series of interactions with the social robot Bina48 (Breakthrough Intelligence via Neural Architecture, 48 exaflops per second). The machine is the brainchild of Martine Rothblatt, an entrepreneur in the field of biopharmaceuticals who, with her wife, Bina, cofounded the Terasem Movement, an organization that seeks to extend human life through cybernetic means. In 2007 Martine commissioned Hanson Robotics to create a robot whose appearance and consciousness simulate Bina’s. The robot was released in 2010, and Dinkins began her work with it in 2014.

Part psychoanalytical discourse, part Turing test, Conversations with Bina48 also participates in a larger dialogue regarding bias and representation in technology. Although Bina Rothblatt is a Black woman, Bina48 was not programmed with an understanding of its Black female identity or with knowledge of Black history. Dinkins’s work situates this omission amid the larger tech industry’s lack of diversity, drawing attention to the problems that arise when a roughly homogenous population creates technologies deployed globally. When this occurs, writes art critic Tess Thackara, “the unconscious biases of white developers proliferate on the internet, mapping our social structures and behaviors onto code and repeating imbalances and injustices that exist in the real world.” One of the most appalling and public of these instances occurred when a Google Photos image-recognition algorithm mislabeled the faces of Black people as “gorillas.”

Eeek

You will find as you go through the ‘imitation game’ a pod with a screen showing your movements through the rooms in realtime on a screen. The installation is called “Creepers” (2021-22). The student team from Vancouver’s Centre for Digital Media (CDM) describes their project this way, from the CDM’s AI-driven Installation Piece for the Vancouver Art Gallery webpage,

Project Description

Kaleidoscope [team name] is designing an installation piece that harnesses AI to collect and visualize exhibit visitor behaviours, and interactions with art, in an impactful and thought-provoking way.

There’s no warning that you’re being tracked and you can see they’ve used facial recognition software to track your movements through the show. It’s claimed on the pod’s signage that they are deleting the data once you’ve left.

‘Creepers’ is an interesting approach to the ethics of AI. The name suggests that even the student designers were aware it was problematic.

For the curious, there’s a description of the other VAG ‘imitation game’ installations provided by CDM students on the ‘Master of Digital Media Students Develop Revolutionary Installations for Vancouver Art Gallery AI Exhibition‘ webpage.

In recovery from an existential crisis (meditations)

There’s something greatly ambitious about “The Imitation Game: Visual Culture in the Age of Artificial Intelligence” and walking up the VAG’s grand staircase affirms that ambition. Bravo to the two curators, Grenville and Entis for an exhibition.that presents a survey (or overview) of artificial intelligence, and its use in and impact on creative visual culture.

I’ve already enthused over the history (specifically Turing, Lovelace, Ovid), admitted to being mesmerized by Scott Eaton’s sculpture/AI videos, and confessed to a fascination (and mild repulsion) regarding Oxman’s honeycombs.

It’s hard to remember all of the ‘objects’ as the curators have offered a jumble of work, almost all of them on screens. Already noted, there’s Norbert Wiener’s The Moth (1949) and there are also a number of other computer-based artworks from the 1960s and 1970s. Plus, you’ll find works utilizing a GAN (generative adversarial network), an AI agent that is explained in the exhibit.

It’s worth going more than once to the show as there is so much to experience.

Why did they do that?

Dear friend, I’ve already commented on the poor flow through the show and It’s hard to tell if the curators intended the experience to be disorienting but this is to the point of chaos, especially when the exhibition is crowded.

I’ve seen Grenville’s shows before. In particular there was “MashUp: The Birth of Modern Culture, a massive survey documenting the emergence of a mode of creativity that materialized in the late 1800s and has grown to become the dominant model of cultural production in the 21st century” and there was “KRAZY! The Delirious World of Anime + Manga + Video Games + Art.” As you can see from the description, he pulls together disparate works and ideas into a show for you to ‘make sense’ of them.

One of the differences between those shows and the “imitation Game: …” is that most of us have some familiarity, whether we like it or not, with modern art/culture and anime/manga/etc. and can try to ‘make sense’ of it.

By contrast, artificial intelligence (which even experts have difficulty defining) occupies an entirely different set of categories; all of them associated with science/technology. This makes for a different kind of show so the curators cannot rely on the audience’s understanding of basics. It’s effectively an art/sci or art/tech show and, I believe, the first of its kind at the Vancouver Art Gallery. Unfortunately, the curators don’t seem to have changed their approach to accommodate that difference.

AI is also at the centre of a current panic over job loss, loss of personal agency, automated racism and sexism, etc. which makes the experience of viewing the show a little tense. In this context, their decision to commission and use ‘Creepers’ seems odd.

Where were Ai-Da and Dall-E-2 and the others?

Oh friend, I was hoping for a robot. Those roomba paintbots didn’t do much for me. All they did was lie there on the floor

To be blunt I wanted some fun and perhaps a bit of wonder and maybe a little vitality. I wasn’t necessarily expecting Ai-Da, an artisitic robot, but something three dimensional and fun in this very flat, screen-oriented show would have been nice.

This image has an empty alt attribute; its file name is image-asset.jpeg
Ai-Da was at the Glastonbury Festival in the U from 23-26th June 2022. Here’s Ai-Da and her Billie Eilish (one of the Glastonbury 2022 headliners) portrait. [downloaded from https://www.ai-darobot.com/exhibition]

Ai-Da was first featured here in a December 17, 2021 posting about performing poetry that she had written in honour of the 700th anniversary of poet Dante Alighieri’s death.

Named in honour of Ada Lovelace, Ai-Da visited the 2022 Venice Biennale as Leah Henrickson and Simone Natale describe in their May 12, 2022 article for Fast Company (Note: Links have been removed),

Ai-Da sits behind a desk, paintbrush in hand. She looks up at the person posing for her, and then back down as she dabs another blob of paint onto the canvas. A lifelike portrait is taking shape. If you didn’t know a robot produced it, this portrait could pass as the work of a human artist.

Ai-Da is touted as the “first robot to paint like an artist,” and an exhibition of her work, called Leaping into the Metaverse, opened at the Venice Biennale.

Ai-Da produces portraits of sitting subjects using a robotic hand attached to her lifelike feminine figure. She’s also able to talk, giving detailed answers to questions about her artistic process and attitudes toward technology. She even gave a TEDx talk about “The Intersection of Art and AI” in Oxford a few years ago. While the words she speaks are programmed, Ai-Da’s creators have also been experimenting with having her write and perform her own poetry.

She has her own website.

If not Ai-Da, what about Dall-E-2? Aaron Hertzmann’s June 20, 2022 commentary, “Give this AI a few words of description and it produces a stunning image – but is it art?” investigates for Salon (Note: Links have been removed),

DALL-E 2 is a new neural network [AI] algorithm that creates a picture from a short phrase or sentence that you provide. The program, which was announced by the artificial intelligence research laboratory OpenAI in April 2022, hasn’t been released to the public. But a small and growing number of people – myself included – have been given access to experiment with it.

As a researcher studying the nexus of technology and art, I was keen to see how well the program worked. After hours of experimentation, it’s clear that DALL-E – while not without shortcomings – is leaps and bounds ahead of existing image generation technology. It raises immediate questions about how these technologies will change how art is made and consumed. It also raises questions about what it means to be creative when DALL-E 2 seems to automate so much of the creative process itself.

A July 4, 2022 article “DALL-E, Make Me Another Picasso, Please” by Laura Lane for The New Yorker has a rebuttal to Ada Lovelace’s contention that creativity is uniquely human (Note: A link has been removed),

“There was this belief that creativity is this deeply special, only-human thing,” Sam Altman, OpenAI’s C.E.O., explained the other day. Maybe not so true anymore, he said. Altman, who wore a gray sweater and had tousled brown hair, was videoconferencing from the company’s headquarters, in San Francisco. DALL-E is still in a testing phase. So far, OpenAI has granted access to a select group of people—researchers, artists, developers—who have used it to produce a wide array of images: photorealistic animals, bizarre mashups, punny collages. Asked by a user to generate “a plate of various alien fruits from another planet photograph,” DALL-E returned something kind of like rambutans. “The rest of mona lisa” is, according to DALL-E, mostly just one big cliff. Altman described DALL-E as “an extension of your own creativity.”

There are other AI artists, in my August 16, 2019 posting, I had this,

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.

That posting also included AI artist, AICAN. Both artist-AI agents (Obvious and AICAN) are based on GANs (generative adversarial networks) for learning and eventual output. Both artist-AI agents work independently or with human collaborators on art works that are available for purchase.

As might be expected not everyone is excited about AI and visual art. Sonja Drimmer, Professor of Medieval Art, University of Massachusetts at Amherst, provides another perspective on AI, visual art, and, her specialty, art history in her November 1, 2021 essay for The Conversation (Note: Links have been removed),

Over the past year alone, I’ve come across articles highlighting how artificial intelligence recovered a “secret” painting of a “lost lover” of Italian painter Modigliani, “brought to life” a “hidden Picasso nude”, “resurrected” Austrian painter Gustav Klimt’s destroyed works and “restored” portions of Rembrandt’s 1642 painting “The Night Watch.” The list goes on.

As an art historian, I’ve become increasingly concerned about the coverage and circulation of these projects.

They have not, in actuality, revealed one secret or solved a single mystery.

What they have done is generate feel-good stories about AI.

Take the reports about the Modigliani and Picasso paintings.

These were projects executed by the same company, Oxia Palus, which was founded not by art historians but by doctoral students in machine learning.

In both cases, Oxia Palus relied upon traditional X-rays, X-ray fluorescence and infrared imaging that had already been carried out and published years prior – work that had revealed preliminary paintings beneath the visible layer on the artists’ canvases.

The company edited these X-rays and reconstituted them as new works of art by applying a technique called “neural style transfer.” This is a sophisticated-sounding term for a program that breaks works of art down into extremely small units, extrapolates a style from them and then promises to recreate images of other content in that same style.

As you can ‘see’ my friend, the topic of AI and visual art is a juicy one. In fact, I have another example in my June 27, 2022 posting, which is titled, “Art appraised by algorithm.” So, Grenville’s and Entis’ decision to focus on AI and its impact on visual culture is quite timely.

Visual culture: seeing into the future

The VAG Imitation Game webpage lists these categories of visual culture “animation, architecture, art, fashion, graphic design, urban design and video games …” as being represented in the show. Movies and visual art, not mentioned in the write up, are represented while theatre and other performing arts are not mentioned or represented. That’ s not a surprise.

In addition to an area of science/technology that’s not well understood even by experts, the curators took on the truly amorphous (and overwhelming) topic of visual culture. Given that even writing this commentary has been a challenge, I imagine pulling the show together was quite the task.

Grenville often grounds his shows in a history of the subject and, this time, it seems especially striking. You’re in a building that is effectively a 19th century construct and in galleries that reflect a 20th century ‘white cube’ aesthetic, while looking for clues into the 21st century future of visual culture employing technology that has its roots in the 19th century and, to some extent, began to flower in the mid-20th century.

Chung’s collaboration is one of the only ‘optimistic’ notes about the future and, as noted earlier, it bears a resemblance to Wiener’s 1949 ‘Moth’

Overall, it seems we are being cautioned about the future. For example, Oxman’s work seems bleak (bees with no flowers to pollinate and living in an eternal spring). Adding in ‘Creepers’ and surveillance along with issues of bias and social injustice reflects hesitation and concern about what we will see, who sees it, and how it will be represented visually.

Learning about robots, automatons, artificial intelligence, and more

I wish the Vancouver Art Gallery (and Vancouver’s other art galleries) would invest a little more in audience education. A couple of tours, by someone who may or may not know what they’re talking, about during the week do not suffice. The extra material about Stephanie Dinkins and her work (“Conversations with Bina48,” 2014–present) came from the de Young Museum’s website. In my July 26, 2021 commentary on North Vancouver’s Polygon Gallery 2021 show “Interior Infinite,” I found background information for artist Zanele Muholi on the Tate Modern’s website. There is nothing on the VAG website that helps you to gain some perspective on the artists’ works.

It seems to me that if the VAG wants to be considered world class, it should conduct itself accordingly and beefing up its website with background information about their current shows would be a good place to start.

Robots, automata, and artificial intelligence

Prior to 1921, robots were known exclusively as automatons. These days, the word ‘automaton’ (or ‘automata’ in the plural) seems to be used to describe purely mechanical representations of humans from over 100 years ago whereas the word ‘robot’ can be either ‘humanlike’ or purely machine, e.g. a mechanical arm that performs the same function over and over. I have a good February 24, 2017 essay on automatons by Miguel Barral for OpenMind BBVA*, which provides some insight into the matter,

The concept of robot is relatively recent. The idea was introduced in 1921 by the Czech writer Karel Capek in his work R.U.R to designate a machine that performs tasks in place of man. But their predecessors, the automatons (from the Greek automata, or “mechanical device that works by itself”), have been the object of desire and fascination since antiquity. Some of the greatest inventors in history, such as Leonardo Da Vinci, have contributed to our fascination with these fabulous creations:

The Al-Jazari automatons

The earliest examples of known automatons appeared in the Islamic world in the 12th and 13th centuries. In 1206, the Arab polymath Al-Jazari, whose creations were known for their sophistication, described some of his most notable automatons: an automatic wine dispenser, a soap and towels dispenser and an orchestra-automaton that operated by the force of water. This latter invention was meant to liven up parties and banquets with music while floating on a pond, lake or fountain.

As the water flowed, it started a rotating drum with pegs that, in turn, moved levers whose movement produced different sounds and movements. As the pegs responsible for the musical notes could be exchanged for different ones in order to interpret another melody, it is considered one of the first programmable machines in history.

If you’re curious about automata, my friend, I found this Sept. 26, 2016 ABC news radio news item about singer Roger Daltrey’s and his wife, Heather’s auction of their collection of 19th century French automata (there’s an embedded video showcasing these extraordinary works of art). For more about automata, robots, and androids, there’s an excellent May 4, 2022 article by James Vincent, ‘A visit to the human factory; How to build the world’s most realistic robot‘ for The Verge; Vincent’s article is about Engineered Arts, the UK-based company that built Ai-Da.

AI is often used interchangeably with ‘robot’ but they aren’t the same. Not all robots have AI integrated into their processes. At its simplest AI is an algorithm or set of algorithms, which may ‘live’ in a CPU and be effectively invisible or ‘live’ in or make use of some kind of machine and/or humanlike body. As the experts have noted, the concept of artificial intelligence is a slippery concept.

*OpenMind BBVA is a Spanish multinational financial services company, Banco Bilbao Vizcaya Argentaria (BBVA), which runs the non-profit project, OpenMind (About us page) to disseminate information on robotics and so much more.*

You can’t always get what you want

My friend,

I expect many of the show’s shortcomings (as perceived by me) are due to money and/or scheduling issues. For example, Ai-Da was at the Venice Biennale and if there was a choice between the VAG and Biennale, I know where I’d be.

Even with those caveats in mind, It is a bit surprising that there were no examples of wearable technology. For example, Toronto’s Tapestry Opera recently performed R.U.R. A Torrent of Light (based on the word ‘robot’ from Karel Čapek’s play, R.U.R., ‘Rossumovi Univerzální Roboti’), from my May 24, 2022 posting,

I have more about tickets prices, dates, and location later in this post but first, here’s more about the opera and the people who’ve created it from the Tapestry Opera’s ‘R.U.R. A Torrent of Light’ performance webpage,

“This stunning new opera combines dance, beautiful multimedia design, a chamber orchestra including 100 instruments creating a unique electronica-classical sound, and wearable technology [emphasis mine] created with OCAD University’s Social Body Lab, to create an immersive and unforgettable science-fiction experience.”

And, from later in my posting,

“Despite current stereotypes, opera was historically a launchpad for all kinds of applied design technologies. [emphasis mine] Having the opportunity to collaborate with OCAD U faculty is an invigorating way to reconnect to that tradition and foster connections between art, music and design, [emphasis mine]” comments the production’s Director Michael Hidetoshi Mori, who is also Tapestry Opera’s Artistic Director. 

That last quote brings me back to the my comment about theatre and performing arts not being part of the show. Of course, the curators couldn’t do it all but a website with my hoped for background and additional information could have helped to solve the problem.

The absence of the theatrical and performing arts in the VAG’s ‘Imitation Game’ is a bit surprising as the Council of Canadian Academies (CCA) in their third assessment, “Competing in a Global Innovation Economy: The Current State of R&D in Canada” released in 2018 noted this (from my April 12, 2018 posting),

Canada, relative to the world, specializes in subjects generally referred to as the
humanities and social sciences (plus health and the environment), and does
not specialize as much as others in areas traditionally referred to as the physical
sciences and engineering. Specifically, Canada has comparatively high levels
of research output in Psychology and Cognitive Sciences, Public Health and
Health Services, Philosophy and Theology, Earth and Environmental Sciences,
and Visual and Performing Arts. [emphasis mine] It accounts for more than 5% of world research in these fields. Conversely, Canada has lower research output than expected in Chemistry, Physics and Astronomy, Enabling and Strategic Technologies,
Engineering, and Mathematics and Statistics. The comparatively low research
output in core areas of the natural sciences and engineering is concerning,
and could impair the flexibility of Canada’s research base, preventing research
institutions and researchers from being able to pivot to tomorrow’s emerging
research areas. [p. xix Print; p. 21 PDF]

US-centric

My friend,

I was a little surprised that the show was so centered on work from the US given that Grenville has curated ate least one show where there was significant input from artists based in Asia. Both Japan and Korea are very active with regard to artificial intelligence and it’s hard to believe that their artists haven’t kept pace. (I’m not as familiar with China and its AI efforts, other than in the field of facial recognition, but it’s hard to believe their artists aren’t experimenting.)

The Americans, of course, are very important developers in the field of AI but they are not alone and it would have been nice to have seen something from Asia and/or Africa and/or something from one of the other Americas. In fact, anything which takes us out of the same old, same old. (Luba Elliott wrote this (2019/2020/2021?) essay, “Artificial Intelligence Art from Africa and Black Communities Worldwide” on Aya Data if you want to get a sense of some of the activity on the African continent. Elliott does seem to conflate Africa and Black Communities, for some clarity you may want to check out the Wikipedia entry on Africanfuturism, which contrasts with this August 12, 2020 essay by Donald Maloba, “What is Afrofuturism? A Beginner’s Guide.” Maloba also conflates the two.)

As it turns out, Luba Elliott presented at the 2019 Montréal Digital Spring event, which brings me to Canada’s artificial intelligence and arts scene.

I promise I haven’t turned into a flag waving zealot, my friend. It’s just odd there isn’t a bit more given that machine learning was pioneered at the University of Toronto. Here’s more about that (from Wikipedia entry for Geoffrey Hinston),

Geoffrey Everest HintonCCFRSFRSC[11] (born 6 December 1947) is a British-Canadian cognitive psychologist and computer scientist, most noted for his work on artificial neural networks.

Hinton received the 2018 Turing Award, together with Yoshua Bengio [Canadian scientist] and Yann LeCun, for their work on deep learning.[24] They are sometimes referred to as the “Godfathers of AI” and “Godfathers of Deep Learning“,[25][26] and have continued to give public talks together.[27][28]

Some of Hinton’s work was started in the US but since 1987, he has pursued his interests at the University of Toronto. He wasn’t proven right until 2012. Katrina Onstad’s February 29, 2018 article (Mr. Robot) for Toronto Life is a gripping read about Hinton and his work on neural networks. BTW, Yoshua Bengio (co-Godfather) is a Canadian scientist at the Université de Montréal and Yann LeCun (co-Godfather) is a French scientist at New York University.

Then, there’s another contribution, our government was the first in the world to develop a national artificial intelligence strategy. Adding those developments to the CCA ‘State of Science’ report findings about visual arts and performing arts, is there another word besides ‘odd’ to describe the lack of Canadian voices?

You’re going to point out the installation by Ben Bogart (a member of Simon Fraser University’s Metacreation Lab for Creative AI and instructor at the Emily Carr University of Art + Design (ECU)) but it’s based on the iconic US scifi film, 2001: A Space Odyssey. As for the other Canadian, Sougwen Chung, she left Canada pretty quickly to get her undergraduate degree in the US and has since moved to the UK. (You could describe hers as the quintessential success story, i.e., moving from Canada only to get noticed here after success elsewhere.)

Of course, there are the CDM student projects but the projects seem less like an exploration of visual culture than an exploration of technology and industry requirements, from the ‘Master of Digital Media Students Develop Revolutionary Installations for Vancouver Art Gallery AI Exhibition‘ webpage, Note: A link has been removed,

In 2019, Bruce Grenville, Senior Curator at Vancouver Art Gallery, approached [the] Centre for Digital Media to collaborate on several industry projects for the forthcoming exhibition. Four student teams tackled the project briefs over the course of the next two years and produced award-winning installations that are on display until October 23 [2022].

Basically, my friend, it would have been nice to see other voices or, at the least, an attempt at representing other voices and visual cultures informed by AI. As for Canadian contributions, maybe put something on the VAG website?

Playing well with others

it’s always a mystery to me why the Vancouver cultural scene seems comprised of a set of silos or closely guarded kingdoms. Reaching out to the public library and other institutions such as Science World might have cost time but could have enhanced the show

For example, one of the branches of the New York Public Library ran a programme called, “We are AI” in March 2022 (see my March 23, 2022 posting about the five-week course, which was run as a learning circle). The course materials are available for free (We are AI webpage) and I imagine that adding a ‘visual culture module’ wouldn’t be that difficult.

There is one (rare) example of some Vancouver cultural institutions getting together to offer an art/science programme and that was in 2017 when the Morris and Helen Belkin Gallery (at the University of British Columbia; UBC) hosted an exhibition of Santiago Ramon y Cajal’s work (see my Sept. 11, 2017 posting about the gallery show) along with that show was an ancillary event held by the folks at Café Scientifique at Science World and featuring a panel of professionals from UBC’s Faculty of Medicine and Dept. of Psychology, discussing Cajal’s work.

In fact, where were the science and technology communities for this show?

On a related note, the 2022 ACM SIGGRAPH conference (August 7 – 11, 2022) is being held in Vancouver. (ACM is the Association for Computing Machinery; SIGGRAPH is for Special Interest Group on Computer Graphics and Interactive Techniques.) SIGGRAPH has been holding conferences in Vancouver every few years since at least 2011.

At this year’s conference, they have at least two sessions that indicate interests similar to the VAG’s. First, there’s Immersive Visualization for Research, Science and Art which includes AI and machine learning along with other related topics. There’s also, Frontiers Talk: Art in the Age of AI: Can Computers Create Art?

This is both an international conference and an exhibition (of art) and the whole thing seems to have kicked off on July 25, 2022. If you’re interested, the programme can be found here and registration here.

Last time SIGGRAPH was here the organizers seemed interested in outreach and they offered some free events.

In the end

It was good to see the show. The curators brought together some exciting material. As is always the case, there were some missed opportunities and a few blind spots. But all is not lost.

July 27, 2022, the VAG held a virtual event with an artist,

Gwenyth Chao to learn more about what happened to the honeybees and hives in Oxman’s Synthetic Apiary project. As a transdisciplinary artist herself, Chao will also discuss the relationship between art, science, technology and design. She will then guide participants to create a space (of any scale, from insect to human) inspired by patterns found in nature.

Hopefully there will be more more events inspired by specific ‘objects’. Meanwhile, August 12, 2022, the VAG is hosting,

… in partnership with the Canadian Music Centre BC, New Music at the Gallery is a live concert series hosted by the Vancouver Art Gallery that features an array of musicians and composers who draw on contemporary art themes.

Highlighting a selection of twentieth- and twenty-first-century music compositions, this second concert, inspired by the exhibition The Imitation Game: Visual Culture in the Age of Artificial Intelligence, will spotlight The Iliac Suite (1957), the first piece ever written using only a computer, and Kaija Saariaho’s Terra Memoria (2006), which is in a large part dependent on a computer-generated musical process.

It would be lovely if they could include an Ada Lovelace Day event. This is an international celebration held on October 11, 2022.

Do go. Do enjoy, my friend.

World Science Festival May 29 – June 3, 2018 in New York City

I haven’t featured the festival since 2014 having forgotten all about it but I received (via email) an April 30, 2018 news release announcing the latest iteration,

ANNOUNCING WORLD SCIENCE FESTIVAL NEW YORK CITY

MAY 29 THROUGH JUNE 3, 2018

OVER 70 INSPIRING SCIENCE-THEMED EVENTS EXPLORE THE VERY EDGE OF
KNOWLEDGE

Over six extraordinary days in New York City, from May 29 through June
3, 2018; the world’s leading scientists will explore the very edge of
knowledge and share their insights with the public.  Festival goers of
all ages can experience vibrant discussions and debates, evocative
performances and films, world-changing research updates,
thought-provoking town hall gatherings and fireside chats, hands-on
experiments and interactive outdoor explorations.  It’s an action
adventure for your mind!

See the full list of programs here:
https://www.worldsciencefestival.com/festival/world-science-festival-2018/

This year will highlight some of the incredible achievements of Women in
Science, celebrating and exploring their impact on the history and
future of scientific discovery. Perennial favorites will also return in
full force, including WSF main stage Big Ideas programs, the Flame
Challenge, Cool Jobs, and FREE outdoor events.

The World Science Festival makes the esoteric understandable and the
familiar fascinating. It has drawn more than 2.5 million participants
since its launch in 2008, with millions more experiencing the programs
online.

THE 2018 WORLD SCIENCE FESTIVAL IS NOT TO BE MISSED, SO MARK YOUR
CALENDAR AND SAVE THE DATES!

Here are a few items from the 2018 Festival’s program page,

Thursday, May 31, 2018

6:00 pm – 9:00 pm

American Museum of Natural History

Host: Faith Salie

How deep is the ocean? Why do whales sing? How far is 20,000 leagues—and what is a league anyway? Raise a glass and take a deep dive into the foamy waters of oceanic arcana under the blue whale in the Museum’s Hall of Ocean Life. Comedian and journalist Faith Salie will regale you with a pub-style night of trivia questions, physical challenges, and hilarity to celebrate the Museum’s newest temporary exhibition, Unseen Oceans. Don’t worry. When the going gets tough, we won’t let you drown. Teams of top scientists—and even a surprise guest or two—will be standing by to assist you. Program includes one free drink and private access to the special exhibition Unseen Oceans. Special exhibition access is available to ticket holders beginning one hour before the program, from 6–7pm.

Learn More

Buy Tickets

Thursday, May 31, 2018

8:00 pm – 9:30 pm

Gerald W. Lynch Theater at John Jay College

Participants: Alvaro Pascual-Leone, Nim Tottenham, Carla Shatz, And Others

What if your brain at 77 were as plastic as it was at 7? What if you could learn Mandarin with the ease of a toddler or play Rachmaninoff without breaking a sweat? A growing understanding of neuroplasticity suggests these fantasies could one day become reality. Neuroplasticity may also be the key to solving diseases like Alzheimer’s, depression, and autism. This program will guide you through the intricate neural pathways inside our skulls, as leading neuroscientists discuss their most recent findings and both the tantalizing possibilities and pitfalls for our future cognitive selves.

The Big Ideas Series is supported in part by the John Templeton Foundation. 

Learn More

Buy Tickets

Friday, June 1, 2018

8:00 pm – 9:30 pm

NYU Skirball Center for the Performing Arts

Participants: Yann LeCun, Susan Schneider, Max Tegmark, And Others

“Success in creating effective A.I.,” said the late Stephen Hawking, “could be the biggest event in the history of our civilization. Or the worst. We just don’t know.” Elon Musk called A.I. “a fundamental risk to the existence of civilization.” Are we creating the instruments of our own destruction or exciting tools for our future survival? Once we teach a machine to learn on its own—as the programmers behind AlphaGo have done, to wondrous results—where do we draw moral and computational lines? Leading specialists in A.I, neuroscience, and philosophy will tackle the very questions that may define the future of humanity.

The Big Ideas Series is supported in part by the John Templeton Foundation. 

Learn More

Buy Tickets

Friday, June 1, 2018

8:00 pm – 9:30 pm

Gerald W. Lynch Theater at John Jay College

Participants Marcela Carena, Janet Conrad, Michael Doser, Hitoshi Murayama, Neil Turok

“If I had a world of my own,” said the Mad Hatter, “nothing would be what it is, because everything would be what it isn’t. And contrary wise, what is, it wouldn’t be.” Nonsensical as this may sound, it comes close to describing an interesting paradox: You exist. You shouldn’t. Stars and galaxies and planets exist. They shouldn’t. The nascent universe contained equal parts matter and antimatter that should have instantly obliterated each other, turning the Big Bang into the Big Fizzle. And yet, here we are: flesh, blood, stars, moons, sky. Why? Come join us as we dive deep down the rabbit hole of solving the mystery of the missing antimatter.

The Big Ideas Series is supported in part by the John Templeton Foundation.

Learn More

Buy Tickets

Saturday, June 2, 2018

10:00 am – 11:00 am

Museum of the City of New York

ParticipantsKubi Ackerman

What makes a city a city? How do you build buildings, plan streets, and design parks with humans and their needs in mind? Join architect and Future Lab Project Director, Kubi Ackerman, on an exploration in which you’ll venture outside to examine New York City anew, seeing it through the eyes of a visionary museum architect, and then head to the Future City Lab’s awesome interactive space where you will design your own park. This is a student-only program for kids currently enrolled in the 4th grade – 8th grade. Parents/Guardians should drop off their children for this event.

Supported by the Bezos Family Foundation.

Learn More

Buy Tickets

Saturday, June 2, 2018

11:00 am – 12:30 pm

NYU Global Center, Grand Hall

Kerouac called it “the only truth.” Shakespeare called it “the food of love.” Maya Angelou called it “my refuge.” And now scientists are finally discovering what these thinkers, musicians, or even any of us with a Spotify account and a set of headphones could have told you on instinct: music lights up multiple corners of the brain, strengthening our neural networks, firing up memory and emotion, and showing us what it means to be human. In fact, music is as essential to being human as language and may even predate it. Can music also repair broken networks, restore memory, and strengthen the brain? Join us as we speak with neuroscientists and other experts in the fields of music and the brain as we pluck the notes of these fascinating phenomenon.

The Big Ideas Series is supported in part by the John Templeton Foundation.

Learn More

Buy Tickets

Saturday, June 2, 2018

3:00 pm – 4:00 pm

NYU Skirball Center for the Performing Arts

Moderator“Science Bob” Pflugfelder

Participants William Clark, Matt Lanier, Michael Meacham, Casie Parish Fisher, Mike Ressler

Most people think of scientists as people who work in funny-smelling labs filled with strange equipment. But there are lots of scientists whose jobs often take them out of the lab, into the world, and beyond. Come join some of the coolest of them in Cool Jobs. You’ll get to meet a forensic scientist, a venomous snake-loving herpetologist, a NASA engineer who lands spacecrafts on Mars, and inventors who are changing the future of sports.

Learn More

Buy Tickets

Saturday, June 2, 2018

4:00 pm – 5:30 pm

NYU Global Center, Grand Hall

“We can rebuild him. We have the technology,” began the opening sequence of the hugely popular 70’s TV show, “The Six Million Dollar Man.” Forty-five years later, how close are we, in reality, to that sci-fi fantasy? More thornily, now that artificial intelligence may soon pass human intelligence, and the merging of human with machine is potentially on the table, what will it then mean to “be human”? Join us for an important discussion with scientists, technologists and ethicists about the path toward superhumanism and the quest for immortality.

The Big Ideas Series is supported in part by the John Templeton Foundation.

Learn More

Buy Tickets

Saturday, June 2, 2018

4:00 pm – 5:30 pm

Gerald W. Lynch Theater at John Jay College

Participants Brett Frischmann, Tim Hwang, Aviv Ovadya, Meredith Whittaker

“Move fast and break things,” went the Silicon Valley rallying cry, and for a long time we cheered along. Born in dorm rooms and garages, implemented by iconoclasts in hoodies, Big Tech, in its infancy, spouted noble goals of bringing us closer. But now, in its adolescence, it threatens to tear us apart. Some worry about an “Infocalypse”: a dystopian disruption so deep and dire we will no longer trust anything we see, hear, or read. Is this pessimistic vision of the future real or hyperbole? Is it time for tech to slow down, grow up, and stop breaking things? Big names in Big Tech will offer big thoughts on this massive societal shift, its terrifying pitfalls, and practical solutions both for ourselves and for future generations.

The Big Ideas Series is supported in part by the John Templeton Foundation.

Learn More

Buy Tickets

This looks like an exciting lineup and there’s a lot more for you to see on the 2018 Festival’s program page. You may also want to take a look at the list of participants which features some expected specialty speakers, an architect, a mathematician, a neuroscientist and some unexpected names such Kareem Abdul-Jabbar who I know as a basketball player and currently, a contestant on Dancing with the Stars. Bringing to mind that Walt Whitman quote, “I am large, I contain multitudes.” (from Whitman’s Song of Myself Wikipedia entry).

If you’re going, there are free events and note a few of the event are already sold out.

Deep learning and some history from the Swiss National Science Foundation (SNSF)

A June 27, 2016 news item on phys.org provides a measured analysis of deep learning and its current state of development (from a Swiss perspective),

In March 2016, the world Go champion Lee Sedol lost 1-4 against the artificial intelligence AlphaGo. For many, this was yet another defeat for humanity at the hands of the machines. Indeed, the success of the AlphaGo software was forged in an area of artificial intelligence that has seen huge progress over the last decade. Deep learning, as it’s called, uses artificial neural networks to process algorithmic calculations. This software architecture therefore mimics biological neural networks.

Much of the progress in deep learning is thanks to the work of Jürgen Schmidhuber, director of the IDSIA (Istituto Dalle Molle di Studi sull’Intelligenza Artificiale) which is located in the suburbs of Lugano. The IDSIA doctoral student Shane Legg and a group of former colleagues went on to found DeepMind, the startup acquired by Google in early 2014 for USD 500 million. The DeepMind algorithms eventually wound up in AlphaGo.

“Schmidhuber is one of the best at deep learning,” says Boi Faltings of the EPFL Artificial Intelligence Lab. “He never let go of the need to keep working at it.” According to Stéphane Marchand-Maillet of the University of Geneva computing department, “he’s been in the race since the very beginning.”

A June 27, 2016 SNSF news release (first published as a story in Horizons no. 109 June 2016) by Fabien Goubet, which originated the news item, goes on to provide a brief history,

The real strength of deep learning is structural recognition, and winning at Go is just an illustration of this, albeit a rather resounding one. Elsewhere, and for some years now, we have seen it applied to an entire spectrum of areas, such as visual and vocal recognition, online translation tools and smartphone personal assistants. One underlying principle of machine learning is that algorithms must first be trained using copious examples. Naturally, this has been helped by the deluge of user-generated content spawned by smartphones and web 2.0, stretching from Facebook photo comments to official translations published on the Internet. By feeding a machine thousands of accurately tagged images of cats, for example, it learns first to recognise those cats and later any image of a cat, including those it hasn’t been fed.

Deep learning isn’t new; it just needed modern computers to come of age. As far back as the early 1950s, biologists tried to lay out formal principles to explain the working of the brain’s cells. In 1956, the psychologist Frank Rosenblatt of the New York State Aeronautical Laboratory published a numerical model based on these concepts, thereby creating the very first artificial neural network. Once integrated into a calculator, it learned to recognise rudimentary images.

“This network only contained eight neurones organised in a single layer. It could only recognise simple characters”, says Claude Touzet of the Adaptive and Integrative Neuroscience Laboratory of Aix-Marseille University. “It wasn’t until 1985 that we saw the second generation of artificial neural networks featuring multiple layers and much greater performance”. This breakthrough was made simultaneously by three researchers: Yann LeCun in Paris, Geoffrey Hinton in Toronto and Terrence Sejnowski in Baltimore.

Byte-size learning

In multilayer networks, each layer learns to recognise the precise visual characteristics of a shape. The deeper the layer, the more abstract the characteristics. With cat photos, the first layer analyses pixel colour, and the following layer recognises the general form of the cat. This structural design can support calculations being made upon thousands of layers, and it was this aspect of the architecture that gave rise to the name ‘deep learning’.

Marchand-Maillet explains: “Each artificial neurone is assigned an input value, which it computes using a mathematical function, only firing if the output exceeds a pre-defined threshold”. In this way, it reproduces the behaviour of real neurones, which only fire and transmit information when the input signal (the potential difference across the entire neural circuit) reaches a certain level. In the artificial model, the results of a single layer are weighted, added up and then sent as the input signal to the following layer, which processes that input using different functions, and so on and so forth.

For example, if a system is trained with great quantities of photos of apples and watermelons, it will progressively learn to distinguish them on the basis of diameter, says Marchand-Maillet. If it cannot decide (e.g., when processing a picture of a tiny watermelon), the subsequent layers take over by analysing the colours or textures of the fruit in the photo, and so on. In this way, every step in the process further refines the assessment.

Video games to the rescue

For decades, the frontier of computing held back more complex applications, even at the cutting edge. Industry walked away, and deep learning only survived thanks to the video games sector, which eventually began producing graphics chips, or GPUs, with an unprecedented power at accessible prices: up to 6 teraflops (i.e., 6 trillion calculations per second) for a few hundred dollars. “There’s no doubt that it was this calculating power that laid the ground for the quantum leap in deep learning”, says Touzet. GPUs are also very good at parallel calculations, a useful function for executing the innumerable simultaneous operations required by neural networks.
Although image analysis is getting great results, things are more complicated for sequential data objects such as natural spoken language and video footage. This has formed part of Schmidhuber’s work since 1989, and his response has been to develop recurrent neural networks in which neurones communicate with each other in loops, feeding processed data back into the initial layers.

Such sequential data analysis is highly dependent on context and precursory data. In Lugano, networks have been instructed to memorise the order of a chain of events. Long Short Term Memory (LSTM) networks can distinguish ‘boat’ from ‘float’ by recalling the sound that preceded ‘oat’ (i.e., either ‘b’ or ‘fl’). “Recurrent neural networks are more powerful than other approaches such as the Hidden Markov models”, says Schmidhuber, who also notes that Google Voice integrated LSTMs in 2015. “With looped networks, the number of layers is potentially infinite”, says Faltings [?].

For Schmidhuber, deep learning is just one aspect of artificial intelligence; the real thing will lead to “the most important change in the history of our civilisation”. But Marchand-Maillet sees deep learning as “a bit of hype, leading us to believe that artificial intelligence can learn anything provided there’s data. But it’s still an open question as to whether deep learning can really be applied to every last domain”.

It’s nice to get an historical perspective and eye-opening to realize that scientists have been working on these concepts since the 1950s.