A review paper by scientists at the Beijing Institute of Technology summarized recent efforts and future potentials in the use of in vitro biological neural networks (BNNs) for the realization of biological intelligence, with a focus on those related to robot intelligence.
The review paper, published on Jan. 10 in the journal Cyborg and Bionic Systems, provided an overview of 1) the underpinnings of intelligence presented in in vitro BNNs, such as memory and learning; 2) how these BNNs can be embodied with robots through bidirectional connection, forming so-called BNN-based neuro-robotic systems; 3) preliminary intelligent behaviors achieved by these neuro-robotic systems; and 4) current trends and future challenges in the research area of BNN-based neuro-robotic systems.
“our human brain is a complex biological neural network (BNN) composed of billions of neurons, which gives rise to our consciousness and intelligence. However, studying the brain as a whole is extremely challenging due to its intricate nature. By culturing a part of the neurons from the brain in a Petri dish, simpler BNNs, such as mini-brains, can be formed, allowing for easier observation and investigation of the network. These mini-brains may provide valuable insights into the enigmatic origins of consciousness and intelligence.” explained study author Zhiqiang Yu, an assistant researcher at the Beijing Institute of Technology.
“Interestingly, mini-brains are not only structurally similar to human brains, but they can also learn and memorize information in a similar way.” said Yu. In particular, these in vitro BNNs share the same basic structure as in vivo BNNs, where neurons are connected through synapses, and they exhibit short-term memory through fading and hidden memory processes. Additionally, these mini-brains can perform supervised learning and be trained to respond to specific stimuli signals. Recently, researchers have demonstrated that in vitro BNNs can even accomplish unsupervised learning tasks, such as separating mixed signals. “This fascinating ability may have something to do with the famous free energy principle. That is, these BNNs have a tendency to minimize their uncertainty about the outer world,” said Yu.
These abilities of in vitro BNNs are quite intriguing. However, only having such a ‘mini-brain’ on your hand is not enough for the rise of consciousness and intelligence. Our brain relies on our body to perceive, comprehend, and adapt to the outside world, and similarly, these mini-brains require a body to interact with their environment. A robot is an ideal candidate for this purpose, leading to a burgeoning interdisciplinary field at the intersection of neuroscience and robotics: BNN-based neuro-robotic systems.
“A stable bidirectional connection is a prerequisite for these systems.” said study authors, “In this review, we summarize the mainstream means of constructing such a bidirectional connection, which can be broadly classified into two categories based on the direction of connection: from robots to BNNs and from BNNs to robots.” The former involves transmitting sensor signals from the robot to BNNs, utilizing electrical, optical, and chemical stimulation methods, while the latter records the neural activities of BNNs and decode these activities into commands to control the robot, using extracellular, calcium, and intracellular recording techniques.
“Embodied by robots, in vitro BNNs exhibit a wide range of fascinating intelligent behaviors,” according to Yu. “These behaviors include supervised and unsupervised learning, memorization, mobile object tracking, active obstacle avoidance, and even learning to play games such as ‘Pong’.”
The intelligent behaviors displayed by these BNN-based neuro-robotic systems can be divided into two categories based on their dependence on either computing capacity or network plasticity, as explained by Yu. “In computing capacity-dependent behaviors, learning is unnecessary, and the BNN is regarded as an information processor that generates specific neural activities in response to stimuli. However, for the latter, learning is a crucial process, as the BNN adapts to stimuli and these changes are integral to the behaviors or tasks performed by the robot,” added Yu.
To facilitate easy comparison of the recording and stimulation techniques, encoding and decoding rules, training policies, and robot tasks, representative studies from these two categories have been compiled into two tables. Additionally, to provide readers with a historical overview of BNN-based neuro-robotic systems, several noteworthy studies have been selected and arranged chronologically.
The study authors also discussed current trends and main challenges in the field. According to Yu, “Four challenges are keen to be addressed and are being intensely investigated. How to fabricate BNNs in 3D, thereby making in vitro BNNs close to their in vivo counterparts, is the most urgent one of them”
Perhaps the most challenging aspect is how to train these robot-embodied BNNs. The study authors noted that BNNs are composed only of neurons and lack the participation of various neuromodulators, which makes it difficult to transplant various animal training methods to BNNs. Additionally, BNNs have their own limitations. While a monkey can be trained to ride a bicycle, it is much more challenging to accomplish tasks that require higher-level thought processes, such as playing Go.
“The mystery of how consciousness and intelligence emerge from the network of cells in our brains still eludes neuroscientists” said Yu. However, with the development of embodying in vitro BNNs with robots, we may observe more intelligent behaviors in them and bring people closer to the truth behind the mystery.
I think that ‘in vitro biological neural networks (BNNs) or mini-brains’ can also be called brain organoids, which seems to be the more popular term in some circles.
I received a May 31, 2023 ‘newsletter’ (via email) from Simon Fraser University’s (SFU) Metacreation Lab for Creative Artificial Intelligence and the first item celebrates some current and past work,
International Conference on New Interfaces for Musical Expressions | NIME 2023 May 31 – June 2 | Mexico City, Mexico
We’re excited to be a part of NIME 2023, launching in Mexico City this week!
As part of the NIME Paper Sessions, some of Metacreation’s labs and affiliates will be presenting a study based on case studies of musicians playing with virtual musical agents. Titled eTu{d,b}e, the paper was co-authored by Tommy Davis, Kasey LV Pocius, and Vincent Cusson, developers of the eTube instrument, along with music technology and interface researchers Marcelo Wanderley and Philippe Pasquier. Learn about the project and listen to sessions involving human and non-human musicians.
This research project involved experimenting with Spire Muse, a virtual performance agent co-developed by Metacreation Lab members. The paper introducing the system was awarded the best paper award at the 2021 International Conference on New Interfaces for Musical Expression (NIME).
Learn more about the NIME2023 conference and program at the link below, which will also present a series of online music concerts later this week.
Coming up later this summer and also from the May 31, 2023 newsletter,
Evaluating Human-AI Interaction for MMM-C: a Creative AI System for Music Composition | IJCAI [2023 International Joint Conference on Artificial Intelligence] Preview
For those following the impact of AI on music composition and production, we would like to share a sneak peek of a review of user experiences using an experimental AI-composition tool [Multi-Track Music Machine (MMM)] integrated into the Steinberg Cubase digital audio workstation. Conducted in partnership with Steinberg, this study will be presented at the 2023 International Joint Conference on Artificial Intelligence (IJCAI2023), as part of the Arts and Creativity track of the conference. This year’s IJCAI conference taking place in Macao from August 19th to Aug 25th, 2023.
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The conference is being held in Macao (or Macau), which is officially (according to its Wikipedia entry) the Macao Special Administrative Region of the People’s Republic of China (MSAR). It has a longstanding reputation as an international gambling and party mecca comparable to Las Vegas.
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).
How to handle non-human authors (ChatGPT and other AI agents)—the medical edition
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
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This is a link to and a citation for the JAMA editorial,
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.
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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.
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,
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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.
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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. …
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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.
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“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.
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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.
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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.”
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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.
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
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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.
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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.
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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.”
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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.
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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.”
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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.
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“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.
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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.
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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.
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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.
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“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.”
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.)
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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. …
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… 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]
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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 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.
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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.
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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.
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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.
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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.
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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
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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.
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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.”
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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.
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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,”
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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.
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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.)
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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,
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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.
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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.
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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,
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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]
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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),
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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.
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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.
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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.”
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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.
This is a cleaned up version of the Ada Lovelace story,
A pioneer in the field of computing, she has a remarkable life story as noted in this October 13, 2014 posting, and explored further in this October 13, 2015 posting (Ada Lovelace “… manipulative, aggressive, a drug addict …” and a genius but was she likable?) published to honour the 200th anniversary of her birth.
In a December 8, 2022 essay for The Conversation, Corinna Schlombs focuses on skills other than mathematics that influenced her thinking about computers (Note: Links have been removed),
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Growing up in a privileged aristocratic family, Lovelace was educated by home tutors, as was common for girls like her. She received lessons in French and Italian, music and in suitable handicrafts such as embroidery. Less common for a girl in her time, she also studied math. Lovelace continued to work with math tutors into her adult life, and she eventually corresponded with mathematician and logician Augustus De Morgan at London University about symbolic logic.
Lovelace drew on all of these lessons when she wrote her computer program – in reality, it was a set of instructions for a mechanical calculator that had been built only in parts.
The computer in question was the Analytical Engine designed by mathematician, philosopher and inventor Charles Babbage. Lovelace had met Babbage when she was introduced to London society. The two related to each other over their shared love for mathematics and fascination for mechanical calculation. By the early 1840s, Babbage had won and lost government funding for a mathematical calculator, fallen out with the skilled craftsman building the precision parts for his machine, and was close to giving up on his project. At this point, Lovelace stepped in as an advocate.
To make Babbage’s calculator known to a British audience, Lovelace proposed to translate into English an article that described the Analytical Engine. The article was written in French by the Italian mathematician Luigi Menabrea and published in a Swiss journal. Scholars believe that Babbage encouraged her to add notes of her own.
In her notes, which ended up twice as long as the original article, Lovelace drew on different areas of her education. Lovelace began by describing how to code instructions onto cards with punched holes, like those used for the Jacquard weaving loom, a device patented in 1804 that used punch cards to automate weaving patterns in fabric.
Having learned embroidery herself, Lovelace was familiar with the repetitive patterns used for handicrafts. Similarly repetitive steps were needed for mathematical calculations. To avoid duplicating cards for repetitive steps, Lovelace used loops, nested loops and conditional testing in her program instructions.
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Finally, Lovelace recognized that the numbers manipulated by the Analytical Engine could be seen as other types of symbols, such as musical notes. An accomplished singer and pianist, Lovelace was familiar with musical notation symbols representing aspects of musical performance such as pitch and duration, and she had manipulated logical symbols in her correspondence with De Morgan. It was not a large step for her to realize that the Analytical Engine could process symbols — not just crunch numbers — and even compose music.
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… Lovelace applied knowledge from what we today think of as disparate fields in the sciences, arts and the humanities. A well-rounded thinker, she created solutions that were well ahead of her time.
For more about Jacquard looms and computing, there’s Sarah Laskow’s September 16, 2014 article for The Atlantic, which includes some interesting details (Note: Links have been removed),
…, one of the very first machines that could run something like what we now call a “program” was used to make fabric. This machine—a loom—could process so much information that the fabric it produced could display pictures detailed enough that they might be mistaken for engravings.
Like, for instance, the image above [as of March 3, 2023, the image is not there]: a woven piece of fabric that depicts Joseph-Marie Jacquard, the inventor of the weaving technology that made its creation possible. As James Essinger recounts in Jacquard’sWeb, in the early 1840s Charles Babbage kept a copy at home and would ask guests to guess how it was made. They were usually wrong.
.. At its simplest, weaving means taking a series of parallel strings (the warp) lifting a selection of them up, and running another string (the weft) between the two layers, creating a crosshatch. …
The Jacquard loom, though, could process information about which of those strings should be lifted up and in what order. That information was stored in punch cards—often 2,000 or more strung together. The holes in the punch cards would let through only a selection of the rods that lifted the warp strings. In other words, the machine could replace the role of a person manually selecting which strings would appear on top. Once the punch cards were created, Jacquard looms could quickly make pictures with subtle curves and details that earlier would have take months to complete. …
… As Ada Lovelace wrote him: “We may say most aptly that the Analytical Engine weaves algebraical patterns just as the Jacquard-loom weaves flowers and leaves.”
For anyone who’s very curious about Jacquard looms, there’s a June 25, 2019 Objects and Stories article (Programming patterns: the story of the Jacquard loom) on the UK’s Science and Industry Museum (in Manchester) website.
Caption: Researchers from Pusan National University in Korea have conducted an in-depth study exploring the use of collaborative AI models to create new designs and the engagement of complex systems. This encourages human-AI collaborative designing which increases efficiency and improves sustainability. Credit:Yoon Kyung Lee from Pusan National University
A Korean researcher is exploring what a collaborative relationship between fashion designers and artificial intelligence (AI) would look like according to a January 6 ,2023 Pusan National University press release (also on EurekAlert but published January 12, 2023),
The use of artificial intelligence (AI) in the fashion industry has grown significantly in recent years. AI is being used for tasks such as personalizing fashion recommendations for customers, optimizing supply chain management, automating processes, and improving sustainability to reduce waste. However, creative processes in fashion designing continue to be human driven, mostly, and not a lot of research exists in the realm of using AI for designing in fashion. Moreover, studies are generally done with data scientists, who build the AI platforms and are involved with the technologic aspect of the process. However, the other side of this equation, i.e., designers themselves, are not roped into research often.
To investigate the practical applicability of AI models to implement creative designs and work with human designers, Assistant Professor Prof. Yoon Kyung Lee from Pusan National University in Korea conducted an in-depth study. Her study was made available online in Thinking Skills and Creativity on September 15, 2022, and subsequently published in Volume 46 of the Journal in December 2022.
“At a time when AI is so deeply ingrained into our lives, this study started instead with considering what a human can do better than AI,” says Prof. Lee, explaining her motivation behind the study. “Could there be an effective collaboration between humans and AI for the purpose of creative design?”
Prof. Lee started with generating new textile designs using deep convolution generative adversarial networks (DC-GANs) and cycle-GANs. The outputs from these models were compared to similar designs produced by design students.
The comparison revealed that though designs produced by both were similar, the biggest difference was the uniqueness and originality seen in the human designs, which came from the person’s experiences. However, the use of AI in repetitive tasks can improve the efficiency of designers and frees up their time to focus on more high-difficulty creative work. AI-generated designs can also be used as a learning tool for people who lack expertise in fashion want to explore their creativity. These people can create designs with assistance from AI. Thus, Prof. Lee proposes a human-AI collaborative network that integrates GANs with human creativity to produce designs. The professor also defined and studied the various elements of a complex system that are involved in human-AI collaborated design. She also went on to establish a human-AI model in which the designer collaborates with AI to create a novel design idea. The model is built in such a way that if the designer shares their creative process and ideas with others, the system can interconnect and evolve, thereby improving its designs.
The fashion industry can leverage this to foresee changes in the fashion industry and offer recommendations and co-creation services. Setting objectives, variables, and limits is part of the designer’s job in the Human-AI collaborative design environment. Therefore, their work should go beyond only the visual aspect and instead cover a variety of disciplines.
“In the future, everybody will be able to be a creator or designer with the help of AI models. So far, only professional fashion designers have been able to design and showcase clothes. But in the future, it will be possible for anyone to design the clothes they want and showcase their creativity,” concludes Prof. Lee.
We hope her dreams are very close to realization!
This is the first time I’ve seen a press release where the writer wishes well for the researcher. Nice touch!
This research into an analogue memristor comes from The Korea Institute of Science and Technology (KIST) according to a September 20, 2022 news item on Nanowerk, Note: A link has been removed,
Neuromorphic computing system technology mimicking the human brain has emerged and overcome the limitation of excessive power consumption regarding the existing von Neumann computing method. A high-performance, analog artificial synapse device, capable of expressing various synapse connection strengths, is required to implement a semiconductor device that uses a brain information transmission method. This method uses signals transmitted between neurons when a neuron generates a spike signal.
However, considering conventional resistance-variable memory devices widely used as artificial synapses, as the filament grows with varying resistance, the electric field increases, causing a feedback phenomenon, resulting in rapid filament growth. Therefore, it is challenging to implement considerable plasticity while maintaining analog (gradual) resistance variation concerning the filament type.
The Korea Institute of Science and Technology (KIST), led by Dr. YeonJoo Jeong’s team at the Center for Neuromorphic Engineering, solved the limitations of analog synaptic characteristics, plasticity and information preservation, which are chronic obstacles regarding memristors, neuromorphic semiconductor devices. He announced the development of an artificial synaptic semiconductor device capable of highly reliable neuromorphic computing (Nature Communications, “Cluster-type analogue memristor by engineering redox dynamics for high-performance neuromorphic computing”).
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Caption: Concept image of the article Credit: Korea Institute of Science and Technology (KIST)
The KIST research team fine-tuned the redox properties of active electrode ions to solve small synaptic plasticity hindering the performance of existing neuromorphic semiconductor devices. Furthermore, various transition metals were doped and used in the synaptic device, controlling the reduction probability of active electrode ions. It was discovered that the high reduction probability of ions is a critical variable in the development of high-performance artificial synaptic devices.
Therefore, a titanium transition metal, having a high ion reduction probability, was introduced by the research team into an existing artificial synaptic device. This maintains the synapse’s analog characteristics and the device plasticity at the synapse of the biological brain, approximately five times the difference between high and low resistances. Furthermore, they developed a high-performance neuromorphic semiconductor that is approximately 50 times more efficient.
Additionally, due to the high alloy formation reaction concerning the doped titanium transition metal, the information retention increased up to 63 times compared with the existing artificial synaptic device. Furthermore, brain functions, including long-term potentiation and long-term depression, could be more precisely simulated.
The team implemented an artificial neural network learning pattern using the developed artificial synaptic device and attempted artificial intelligence image recognition learning. As a result, the error rate was reduced by more than 60% compared with the existing artificial synaptic device; additionally, the handwriting image pattern (MNIST) recognition accuracy increased by more than 69%. The research team confirmed the feasibility of a high-performance neuromorphic computing system through this improved the artificial synaptic device.
Dr. Jeong of KIST stated, “This study drastically improved the synaptic range of motion and information preservation, which were the greatest technical barriers of existing synaptic mimics.” “In the developed artificial synapse device, the device’s analog operation area to express the synapse’s various connection strengths has been maximized, so the performance of brain simulation-based artificial intelligence computing will be improved.” Additionally, he mentioned, “In the follow-up research, we will manufacture a neuromorphic semiconductor chip based on the developed artificial synapse device to realize a high-performance artificial intelligence system, thereby further enhancing competitiveness in the domestic system and artificial intelligence semiconductor field.”
Bill C-27 (Digital Charter Implementation Act, 2022) is what I believe is called an omnibus bill as it includes three different pieces of proposed legislation (the Consumer Privacy Protection Act [CPPA], the Artificial Intelligence and Data Act [AIDA], and the Personal Information and Data Protection Tribunal Act [PIDPTA]). You can read the Innovation, Science and Economic Development (ISED) Canada summary here or a detailed series of descriptions of the act here on the ISED’s Canada’s Digital Charter webpage.
Months after the first reading in June 2022, Bill C-27 was mentioned here in a September 15, 2022 posting about a Canadian Science Policy Centre (CSPC) event featuring a panel discussion about the proposed legislation, artificial intelligence in particular. I dug down and found commentaries and additional information about the proposed bill with special attention to AIDA.
it seems discussion has been reactivated since the second reading was completed on April 24, 2023 and referred to committee for further discussion. (A report and third reading are still to be had in the House of Commons and then, there are three readings in the Senate before this legislation can be passed.)
Christian Paas-Lang has written an April 24, 2023 article for CBC (Canadian Broadcasting Corporation) news online that highlights concerns centred on AI from three cross-party Members of Parliament (MPs),
Once the domain of a relatively select group of tech workers, academics and science fiction enthusiasts, the debate over the future of artificial intelligence has been thrust into the mainstream. And a group of cross-party MPs say Canada isn’t yet ready to take on the challenge.
The popularization of AI as a subject of concern has been accelerated by the introduction of ChatGPT, an AI chatbot produced by OpenAI that is capable of generating a broad array of text, code and other content. ChatGPT relies on content published on the internet as well as training from its users to improve its responses.
ChatGPT has prompted such a fervour, said Katrina Ingram, founder of the group Ethically Aligned AI, because of its novelty and effectiveness.
“I would argue that we’ve had AI enabled infrastructure or technologies around for quite a while now, but we haven’t really necessarily been confronted with them, you know, face to face,” she told CBC Radio’s The House [radio segment embedded in article] in an interview that aired Saturday [April 22, 2023].
Ingram said the technology has prompted a series of concerns: about the livelihoods of professionals like artists and writers, about privacy, data collection and surveillance and about whether chatbots like ChatGPT can be used as tools for disinformation.
With the popularization of AI as an issue has come a similar increase in concern about regulation, and Ingram says governments must act now.
“We are contending with these technologies right now. So it’s really imperative that governments are able to pick up the pace,” she told host Catherine Cullen.
That sentiment — the need for speed — is one shared by three MPs from across party lines who are watching the development of the AI issue. Conservative MP Michelle Rempel Garner, NDP MP Brian Masse and Nathaniel Erskine-Smith of the Liberals also joined The House for an interview that aired Saturday.
“This is huge. This is the new oil,” said Masse, the NDP’s industry critic, referring to how oil had fundamentally shifted economic and geopolitical relationships, leading to a great deal of good but also disasters — and AI could do the same.
Issues of both speed and substance
The three MPs are closely watching Bill C-27, a piece of legislation currently being debated in the House of Commons that includes Canada’s first federal regulations on AI.
But each MP expressed concern that the bill may not be ready in time and changes would be needed [emphasis mine].
“This legislation was tabled in June of last year [2022], six months before ChatGPT was released and it’s like it’s obsolete. It’s like putting in place a framework to regulate scribes four months after the printing press came out,” Rempel Garner said. She added that it was wrongheaded to move the discussion of AI away from Parliament and segment it off to a regulatory body.
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Am I the only person who sees a problem with the “bill may not be ready in time and changes would be needed?” I don’t understand the rush (or how these people get elected). The point of a bill is to examine the ideas and make changes to it before it becomes legislation. Given how fluid the situation appears to be, a strong argument can be made for the current process which is three readings in the House of Commons, along with a committee report, and three readings in the senate before a bill, if successful, is passed into legislation.
Of course, the fluidity of the situation could also be an argument for starting over as Michael Geist’s (Canada Research Chair in Internet and E-Commerce Law at the University of Ottawa and member of the Centre for Law, Technology and Society) April 19, 2023 post on his eponymous blog suggests, Note: Links have been removed,
As anyone who has tried ChatGPT will know, at the bottom of each response is an option to ask the AI system to “regenerate response”. Despite increasing pressure on the government to move ahead with Bill C-27’s Artificial Intelligence and Data Act (AIDA), the right response would be to hit the regenerate button and start over. AIDA may be well-meaning and the issue of AI regulation critically important, but the bill is limited in principles and severely lacking in detail, leaving virtually all of the heavy lifting to a regulation-making process that will take years to unfold. While no one should doubt the importance of AI regulation, Canadians deserve better than virtue signalling on the issue with a bill that never received a full public consultation.
What prompts this post is a public letter based out of MILA that calls on the government to urgently move ahead with the bill signed by some of Canada’s leading AI experts. The letter states: …
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When the signatories to the letter suggest that there is prospect of moving AIDA forward before the summer, it feels like a ChatGPT error. There are a maximum of 43 days left on the House of Commons calendar until the summer. In all likelihood, it will be less than that. Bill C-27 is really three bills in one: major privacy reform, the creation of a new privacy tribunal, and AI regulation. I’ve watched the progress of enough bills to know that this just isn’t enough time to conduct extensive hearings on the bill, conduct a full clause-by-clause review, debate and vote in the House, and then conduct another review in the Senate. At best, Bill C-27 could make some headway at committee, but getting it passed with a proper review is unrealistic.
Moreover, I am deeply concerned about a Parliamentary process that could lump together these three bills in an expedited process. …
For anyone unfamiliar with MILA, it is also known as Quebec’s Artificial Intelligence Institute. (They seem to have replaced institute with ecosystem since the last time I checked.) You can see the document and list of signatories here.
Geist has a number of posts and podcasts focused on the bill and the easiest way to find them is to use the search term ‘Bill C-27’.
Maggie Arai at the University of Toronto’s Schwartz Reisman Institute for Technology and Society provides a brief overview titled, Five things to know about Bill C-27, in her April 18, 2022 commentary,
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On June 16, 2022, the Canadian federal government introduced Bill C-27, the Digital Charter Implementation Act 2022, in the House of Commons. Bill C-27 is not entirely new, following in the footsteps of Bill C-11 (the Digital Charter Implementation Act 2020). Bill C-11 failed to pass, dying on the Order Paper when the Governor General dissolved Parliament to hold the 2021 federal election. While some aspects of C-27 will likely be familiar to those who followed the progress of Bill C-11, there are several key differences.
The tabling of Bill C-27 represents an exciting step forward for Canada as it attempts to forge a path towards regulating AI that will promote innovation of this advanced technology, while simultaneously offering consumers assurance and protection from the unique risks this new technology it poses. This second attempt towards the CPPA and PIDPTA is similarly positive, and addresses the need for updated and increased consumer protection, privacy, and data legislation.
However, as the saying goes, the devil is in the details. As we have outlined, several aspects of how Bill C-27 will be implemented are yet to be defined, and how the legislation will interact with existing social, economic, and legal dynamics also remains to be seen.
There are also sections of C-27 that could be improved, including areas where policymakers could benefit from the insights of researchers with domain expertise in areas such as data privacy, trusted computing, platform governance, and the social impacts of new technologies. In the coming weeks, the Schwartz Reisman Institute will present additional commentaries from our community that explore the implications of C-27 for Canadians when it comes to privacy, protection against harms, and technological governance.
Bryan Short’s September 14, 2022 posting (The Absolute Bare Minimum: Privacy and the New Bill C-27) on the Open Media website critiques two of the three bills included in Bill C-27, Note: Links have been removed,
The Canadian government has taken the first step towards creating new privacy rights for people in Canada. After a failed attempt in 2020 and three years of inaction since the proposal of the digital charter, the government has tabled another piece of legislation aimed at giving people in Canada the privacy rights they deserve.
In this post, we’ll explore how Bill C-27 compares to Canada’s current privacy legislation, how it stacks up against our international peers, and what it means for you. This post considers two of the three acts being proposed in Bill C-27, the Consumer Privacy Protection Act (CPPA) and the Personal Information and Data Tribunal Act (PIDTA), and doesn’t discuss the Artificial Intelligence and Data Act [emphasis mine]. The latter Act’s engagement with very new and complex issues means we think it deserves its own consideration separate from existing privacy proposals, and will handle it as such.
If we were to give Bill C-27’s CPPA and PIDTA a grade, it’d be a D. This is legislation that does the absolute bare minimum for privacy protections in Canada, and in some cases it will make things actually worse. If they were proposed and passed a decade ago, we might have rated it higher. However, looking ahead at predictable movement in data practices over the next ten – or even twenty – years, these laws will be out of date the moment they are passed, and leave people in Canada vulnerable to a wide range of predatory data practices. For detailed analysis, read on – but if you’re ready to raise your voice, go check out our action calling for positive change before C-27 passes!
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Taking this all into account, Bill C-27 isn’t yet the step forward for privacy in Canada that we need. While it’s an improvement upon the last privacy bill that the government put forward, it misses so many areas that are critical for improvement, like failing to put people in Canada above the commercial interests of companies.
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If Open Media has followed up with an AIDA critique, I have not been able to find it on their website.
Lifting a glass, making a fist, entering a phone number using the index finger: it is amazing the things cutting-edge robotic hands can already do thanks to biomedical technology. However, things that work in the laboratory often encounter stumbling blocks when put to practice in daily life. The problem is the vast diversity of the intentions of each individual person, their surroundings and the things that can be found there, making a one size fits all solution all but impossible. A team at FAU is investigating how intelligent prostheses can be improved and made more reliable. The idea is that interactive artificial intelligence will help the prostheses to recognize human intent better, to register their surroundings and to continue to develop and improve over time. The project is to receive 4.5 million euros in funding from the EU, with FAU receiving 467,000 euros.
“We are literally working at the interface between humans and machines,” explains Prof. Dr. Claudio Castellini, professor of medical robotics at FAU. “The technology behind prosthetics for upper limbs has come on in leaps and bounds over the past decades.” Using surface electromyography, for example, skin electrodes at the remaining stump of the arm can detect the slightest muscle movements. These biosignals can be converted and transferred to the prosthetic limb as electrical impulses. “The wearer controls their artificial hand themselves using the stump. Methods taken from pattern recognition and interactive machine learning also allow people to teach their prosthetic their own individual needs when making a gesture or a movement.”
The advantages of AI over purely cosmetic prosthetics
At present, advanced robotic prosthetics have not yet reached optimal standards in terms of comfort, function and control, which is why many people with missing limbs still often prefer purely cosmetic prosthetics with no additional functions. The new EU Horizon project “AI-Powered Manipulation System for Advanced Robotic Service, Manufacturing and Prosthetics (IntelliMan)” therefore focuses on how these can interact with their environment even more effectively and for a specific purpose.
Researchers at FAU concentrate in particular on how to improve control of both real and virtual prosthetic upper limbs. The focus is on what is known as intent detection. Prof. Castellini and his team are continuing work on recording and analyzing human biosignals, and are designing innovative algorithms for machine learning aimed at detecting the individual movement patterns of individuals. User studies conducted on test persons both with and without physical disabilities are used to validate their results. Furthermore, FAU is also leading the area “Shared autonomy between humans and robots” in the EU project, aimed at checking the safety of the results.
At the interface between humans and machines
Prof. Castellini heads the “Assistive Intelligent Robotics” lab (AIROB) at FAU that focuses on controlling assistive robotics for the upper and lower limbs as well as functional electrostimulation. “We are exploiting the potential offered by intent detection to control assistive and rehabilitative robotics,” explains the researcher. “This covers wearable robots worn on the body such as prosthetics and exoskeletons, but also robot arms and simulations using virtual reality.” The professorship focuses particularly on biosignal processing of various sensor modalities and methods of machine learning for intent detection, in other words research directly at the interface between humans and machines.
In his previous research at the German Aerospace Center (DLR), where he was based until 2021, Castellini investigated the question of how virtual hand prosthetics could help amputees cope with phantom pain. Alongside Castellini, doctoral candidate Fabio Egle, a research associate at the professorship, is also actively involved in the IntelliMan project. The FAU share of the EU project will receive funding of 467,000 euros over a period of three and a half years, while the overall budget amounts to 6 million euros. The IntelliMan project is coordinated by the University of Bologna and the DLR, the Polytechnic University of Catalonia, the University of Genoa, Luigi Vanvitelli University in Campania and the Bavarian Research Alliance (BayFOR) are also involved.
There is a lot of anxiety about artificial intelligence in the arts, which can only be exacerbated by a question such as this, from a December 2, 2022 news item on ScienceDaily,
Can artificial intelligence write better poetry than humans?
The gap between human creativity and artificial intelligence seems to be narrowing. Previous studies have compared AI-generated versus human-written poems and whether people can distinguish between them.
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The answer doesn’t seem all that comforting and a December 2, 2022 Kyoto University press release (also on EurekAlert but published December 1, 2022), which originated the news item, provides more detail, some of it disconcerting,
Now, a study led by Yoshiyuki Ueda at Kyoto University Institute for the Future of Human and Society [Japan], has shown AI’s potential in creating literary art such as haiku — the shortest poetic form in the world — rivaling that of humans without human help.
Ueda’s team compared AI-generated haiku without human intervention, also known as human out of the loop, or HOTL, with a contrasting method known as human in the loop, or HITL.
The project involved 385 participants, each of whom evaluated 40 haiku poems — 20 each of HITL and HOTL — plus 40 composed entirely by professional haiku writers.
“It was interesting that the evaluators found it challenging to distinguish between the haiku penned by humans and those generated by AI,” remarks Ueda.
From the results, HITL haiku received the most praise for their poetic qualities, whereas HOTL and human-only verses had similar scores.
“In addition, a phenomenon called algorithm aversion was observed among our evaluators. They were supposed to be unbiased but instead became influenced by a kind of reverse psychology,” explains the author.
“In other words, they tended to unconsciously give lower scores to those they felt were AI-generated.”
Ueda points out that his research has put a spotlight on algorithm aversion as a new approach to AI art.
“Our results suggest that the ability of AI in the field of haiku creation has taken a leap forward, entering the realm of collaborating with humans to produce more creative works. Realizing the existence of algorithmic aversion will lead people to re-evaluate their appreciation of AI art.”
For those unfamiliar with Matsuo Bashō, he’s considered Japan’s most famous poet from the Edo period and Japan’s greatest master of haiku according to his Wikipedia entry. You can also find out more about Basho at the Poetry Foundation.
Caption: Dream artwork by Jewel Chang of Anglia Ruskin University, which will be on display at the Cambridge Festival. Credit: Jewel Chang, Anglia Ruskin University
Let’s clear up a few things. First, as noted in the headline, the Cambridge Festival (March 17 – April 2, 2023) is being held in the UK by the University of Cambridge in the town of Cambridge. Second, the specific festival event featured here is a display put together by students and professors at Anglia Ruskin University (ARU) and in the town of Cambridge as part of the festival and will be held for two days, March 31 – April 1, 2023.
Dreams are being turned into reality as new research investigating the unusual experiences of people with depersonalisation symptoms is being brought to life in an art exhibition at Anglia Ruskin University (ARU) in Cambridge, England.
ARU neuroscientist Dr Jane Aspell has led a major international study into depersonalisation, funded by the Bial Foundation. The “Living in a Dream” project, results from which will be published later this year, found that people who experience depersonalisation symptoms sometimes experience life from a very different perspective, both while awake and while dreaming.
Those experiencing depersonalisation often report feeling as though they are not real and that their body does not belong to them. Dr Aspell’s study, which is the first to examine how people with this disorder experience dreams, collected almost 1,000 dream reports from participants.
Now these dreams have been recreated by eight students from ARU’s MA Illustration course and the artwork will go on display for the first time on 31 March and 1 April as part of the Cambridge Festival.
This collaboration between art and science, led by psychologist Matt Gwyther and illustrator Dr Nanette Hoogslag, with the support of artist and creative technologist Emily Godden, has resulted in 12 original artworks, which have been created using the latest audio-visual technologies, including artificial intelligence (AI), and are presented using a mix of audio-visual installation, virtual reality (VR) experiences, and traditional media.
Dr Jane Aspell, Associate Professor of Cognitive Neuroscience at ARU and Head of the Self and Body Lab, said: “People who experience depersonalisation sometimes feel detached from their self and body, and a common complaint is that it’s like they are watching their own life as a film.
“Because their waking reality is so different, myself and my international collaborators – Dr Anna Ciaunica, Professor Bigna Lenggenhager and Dr Jennifer Windt – were keen to investigate how they experience their dreams.
“People who took part in the study completed daily ‘dream diaries’, and it is fabulous to see how these dreams have been recreated by this group of incredibly talented artists.”
Matt Gwyther added: “Dreams are both incredibly visual and surreal, and you lose so much when attempting to put them into words. By bringing them to life as art, it has not only produced fabulous artwork, but it also helps us as scientists better understand the experiences of our research participants.”
Amongst the artists contributing to the exhibition is MA student Jewel Chang, who has recreated a dream about being chased. When the person woke up, they continued to experience it and were unsure whether they were experiencing the dream or reality.
False awakenings and multiple layers of dreams can be confusing, affecting our perception of time and space. Jewel used AI to create an environment with depth and endless moving patterns that makes the visitor feel trapped in their dream, unable to escape.
Kelsey Wu, meanwhile, used special 3D software and cameras to recreate a dream of floating over hills and forests, and losing balance. The immersive piece, with the audience invited to sit on a grass-covered floor, creates a sense of loss of control of the body, which moves in an abnormal and unbalanced way, and evokes a struggle between illusion and reality as the landscape continuously moves.
Dr Nanette Hoogslag, Course Leader for the MA in Illustration at ARU, said: “This project has been a unique challenge, where students not only applied themselves in supporting scientific research, but investigated and used a range of new technologies, including virtual reality and AI-generated imagery. The final pieces are absolutely remarkable, and also slightly unsettling!”
