There’s a very good article about the upcoming AI (artificial intelligence) safety talks on the British Broadcasting Corporation (BBC) news website (plus some juicy perhaps even gossipy news about who may not be attending the event) but first, here’s the August 24, 2023 UK government press release making the announcement,
Iconic Bletchley Park to host UK AI Safety Summit in early November [2023]
Major global event to take place on the 1st and 2nd of November.[2023]
– UK to host world first summit on artificial intelligence safety in November
– Talks will explore and build consensus on rapid, international action to advance safety at the frontier of AI technology
– Bletchley Park, one of the birthplaces of computer science, to host the summit
International governments, leading AI companies and experts in research will unite for crucial talks in November on the safe development and use of frontier AI technology, as the UK Government announces Bletchley Park as the location for the UK summit.
The major global event will take place on the 1st and 2nd November to consider the risks of AI, especially at the frontier of development, and discuss how they can be mitigated through internationally coordinated action. Frontier AI models hold enormous potential to power economic growth, drive scientific progress and wider public benefits, while also posing potential safety risks if not developed responsibly.
To be hosted at Bletchley Park in Buckinghamshire, a significant location in the history of computer science development and once the home of British Enigma codebreaking – it will see coordinated action to agree a set of rapid, targeted measures for furthering safety in global AI use.
Preparations for the summit are already in full flow, with Matt Clifford and Jonathan Black recently appointed as the Prime Minister’s Representatives. Together they’ll spearhead talks and negotiations, as they rally leading AI nations and experts over the next three months to ensure the summit provides a platform for countries to work together on further developing a shared approach to agree the safety measures needed to mitigate the risks of AI.
Prime Minister Rishi Sunak said:
“The UK has long been home to the transformative technologies of the future, so there is no better place to host the first ever global AI safety summit than at Bletchley Park this November.
To fully embrace the extraordinary opportunities of artificial intelligence, we must grip and tackle the risks to ensure it develops safely in the years ahead.
With the combined strength of our international partners, thriving AI industry and expert academic community, we can secure the rapid international action we need for the safe and responsible development of AI around the world.”
Technology Secretary Michelle Donelan said:
“International collaboration is the cornerstone of our approach to AI regulation, and we want the summit to result in leading nations and experts agreeing on a shared approach to its safe use.
The UK is consistently recognised as a world leader in AI and we are well placed to lead these discussions. The location of Bletchley Park as the backdrop will reaffirm our historic leadership in overseeing the development of new technologies.
AI is already improving lives from new innovations in healthcare to supporting efforts to tackle climate change, and November’s summit will make sure we can all realise the technology’s huge benefits safely and securely for decades to come.”
The summit will also build on ongoing work at international forums including the OECD, Global Partnership on AI, Council of Europe, and the UN and standards-development organisations, as well as the recently agreed G7 Hiroshima AI Process.
The UK boasts strong credentials as a world leader in AI. The technology employs over 50,000 people, directly supports one of the Prime Minister’s five priorities by contributing £3.7 billion to the economy, and is the birthplace of leading AI companies such as Google DeepMind. It has also invested more on AI safety research than any other nation, backing the creation of the Foundation Model Taskforce with an initial £100 million.
Foreign Secretary James Cleverly said:
“No country will be untouched by AI, and no country alone will solve the challenges posed by this technology. In our interconnected world, we must have an international approach.
The origins of modern AI can be traced back to Bletchley Park. Now, it will also be home to the global effort to shape the responsible use of AI.”
Bletchley Park’s role in hosting the summit reflects the UK’s proud tradition of being at the frontier of new technology advancements. Since Alan Turing’s celebrated work some eight decades ago, computing and computer science have become fundamental pillars of life both in the UK and across the globe.
Iain Standen, CEO of the Bletchley Park Trust, said:
“Bletchley Park Trust is immensely privileged to have been chosen as the venue for the first major international summit on AI safety this November, and we look forward to welcoming the world to our historic site.
It is fitting that the very spot where leading minds harnessed emerging technologies to influence the successful outcome of World War 2 will, once again, be the crucible for international co-ordinated action.
We are incredibly excited to be providing the stage for discussions on global safety standards, which will help everyone manage and monitor the risks of artificial intelligence.”
The roots of AI can be traced back to the leading minds who worked at Bletchley during World War 2, with codebreakers Jack Good and Donald Michie among those who went on to write extensive works on the technology. In November [2023], it will once again take centre stage as the international community comes together to agree on important guardrails which ensure the opportunities of AI can be realised, and its risks safely managed.
The announcement follows the UK government allocating £13 million to revolutionise healthcare research through AI, unveiled last week. The funding supports a raft of new projects including transformations to brain tumour surgeries, new approaches to treating chronic nerve pain, and a system to predict a patient’s risk of developing future health problems based on existing conditions.
Tom Gerken’s August 24, 2023 BBC news article (an analysis by Zoe Kleinman follows as part of the article) fills in a few blanks, Note: Links have been removed,
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World leaders will meet with AI companies and experts on 1 and 2 November for the discussions.
The global talks aim to build an international consensus on the future of AI.
The summit will take place at Bletchley Park, where Alan Turing, one of the pioneers of modern computing, worked during World War Two.
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It is unknown which world leaders will be invited to the event, with a particular question mark over whether the Chinese government or tech giant Baidu will be in attendance.
The BBC has approached the government for comment.
The summit will address how the technology can be safely developed through “internationally co-ordinated action” but there has been no confirmation of more detailed topics.
It comes after US tech firm Palantir rejected calls to pause the development of AI in June, with its boss Alex Karp saying it was only those with “no products” who wanted a pause.
And in July [2023], children’s charity the Internet Watch Foundation called on Mr Sunak to tackle AI-generated child sexual abuse imagery, which it says is on the rise.
Kleinman’s analysis includes this, Note: A link has been removed,
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Will China be represented? Currently there is a distinct east/west divide in the AI world but several experts argue this is a tech that transcends geopolitics. Some say a UN-style regulator would be a better alternative to individual territories coming up with their own rules.
If the government can get enough of the right people around the table in early November [2023], this is perhaps a good subject for debate.
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Three US AI giants – OpenAI, Anthropic and Palantir – have all committed to opening London headquarters.
But there are others going in the opposite direction – British DeepMind co-founder Mustafa Suleyman chose to locate his new AI company InflectionAI in California. He told the BBC the UK needed to cultivate a more risk-taking culture in order to truly become an AI superpower.
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Many of those who worked at Bletchley Park decoding messages during WW2 went on to write and speak about AI in later years, including codebreakers Irving John “Jack” Good and Donald Michie.
Soon after the War, [Alan] Turing proposed the imitation game – later dubbed the “Turing test” – which seeks to identify whether a machine can behave in a way indistinguishable from a human.
Insight into political jockeying (i.e., some juicy news bits)
This has recently been reported by BBC, from an October 17 (?). 2023 news article by Jessica Parker & Zoe Kleinman on BBC news online,
German Chancellor Olaf Scholz may turn down his invitation to a major UK summit on artificial intelligence, the BBC understands.
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While no guest list has been published of an expected 100 participants, some within the sector say it’s unclear if the event will attract top leaders.
A government source insisted the summit is garnering “a lot of attention” at home and overseas.
The two-day meeting is due to bring together leading politicians as well as independent experts and senior execs from the tech giants, who are mainly US based.
The first day will bring together tech companies and academics for a discussion chaired by the Secretary of State for Science, Innovation and Technology, Michelle Donelan.
The second day is set to see a “small group” of people, including international government figures, in meetings run by PM Rishi Sunak.
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Though no final decision has been made, it is now seen as unlikely that the German Chancellor will attend.
That could spark concerns of a “domino effect” with other world leaders, such as the French President Emmanuel Macron, also unconfirmed.
Government sources say there are heads of state who have signalled a clear intention to turn up, and the BBC understands that high-level representatives from many US-based tech giants are going.
The foreign secretary confirmed in September [2023] that a Chinese representative has been invited, despite controversy.
Some MPs within the UK’s ruling Conservative Party believe China should be cut out of the conference after a series of security rows.
It is not known whether there has been a response to the invitation.
China is home to a huge AI sector and has already created its own set of rules to govern responsible use of the tech within the country.
The US, a major player in the sector and the world’s largest economy, will be represented by Vice-President Kamala Harris.
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Britain is hoping to position itself as a key broker as the world wrestles with the potential pitfalls and risks of AI.
However, Berlin is thought to want to avoid any messy overlap with G7 efforts, after the group of leading democratic countries agreed to create an international code of conduct.
Germany is also the biggest economy in the EU – which is itself aiming to finalise its own landmark AI Act by the end of this year.
It includes grading AI tools depending on how significant they are, so for example an email filter would be less tightly regulated than a medical diagnosis system.
The European Commission President Ursula von der Leyen is expected at next month’s summit, while it is possible Berlin could send a senior government figure such as its vice chancellor, Robert Habeck.
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A source from the Department for Science, Innovation and Technology said: “This is the first time an international summit has focused on frontier AI risks and it is garnering a lot of attention at home and overseas.
“It is usual not to confirm senior attendance at major international events until nearer the time, for security reasons.”
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
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.”
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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,
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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.
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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.
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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/]
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).
Sougwen Chung, Omnia per Omnia, 2018, video (excerpt), Courtesy of the Artist
*A Roomba is a robot vacuum cleaner produced and sold by iRobot.
As far as I know, this is the Vancouver Art Gallery’s first art/science or art/technology exhibit and it is an alternately fascinating, exciting, and frustrating take on artificial intelligence and its impact on the visual arts. Curated by Bruce Grenville, VAG Senior Curator, and Glenn Entis, Guest Curator, the show features 20 ‘objects’ designed to both introduce viewers to the ‘imitation game’ and to challenge them. From the VAG Imitation Game webpage,
The Imitation Game surveys the extraordinary uses (and abuses) of artificial intelligence (AI) in the production of modern and contemporary visual culture around the world. The exhibition follows a chronological narrative that first examines the development of artificial intelligence, from the 1950s to the present [emphasis mine], through a precise historical lens. Building on this foundation, it emphasizes the explosive growth of AI across disciplines, including animation, architecture, art, fashion, graphic design, urban design and video games, over the past decade. Revolving around the important roles of machine learning and computer vision in AI research and experimentation, The Imitation Game reveals the complex nature of this new tool and demonstrates its importance for cultural production.
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And now …
As you’ve probably guessed, my friend, you’ll find a combination of both background information and commentary on the show.
I’ve initially focused on two people (a scientist and a mathematician) who were seminal thinkers about machines, intelligence, creativity, and humanity. I’ve also provided some information about the curators, which hopefully gives you some insight into the show.
As for the show itself, you’ll find a few of the ‘objects’ highlighted with one of them being investigated at more length. The curators devoted some of the show to ethical and social justice issues, accordingly, the Vancouver Art Gallery hosted the University of British Columbia’s “Speculative Futures: Artificial Intelligence Symposium” on April 7, 2022,
Presented in conjunction with the exhibition The Imitation Game: Visual Culture in the Age of Artificial Intelligence, the Speculative Futures Symposium examines artificial intelligence and the specific uses of technology in its multifarious dimensions. Across four different panel conversations, leading thinkers of today will explore the ethical implications of technology and discuss how they are working to address these issues in cultural production.”
So, you’ll find more on these topics here too.
And for anyone else reading this (not you, my friend who is ‘strong’ AI and not similar to the ‘weak’ AI found in this show), there is a description of ‘weak’ and ‘strong’ AI on the avtsim.com/weak-ai-strong-ai webpage, Note: A link has been removed,
There are two types of AI: weak AI and strong AI.
Weak, sometimes called narrow, AI is less intelligent as it cannot work without human interaction and focuses on a more narrow, specific, or niched purpose. …
Strong AI on the other hand is in fact comparable to the fictitious AIs we see in media like the terminator. The theoretical Strong AI would be equivalent or greater to human intelligence.
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My dear friend, I hope you will enjoy.
The Imitation Game and ‘mad, bad, and dangerous to know’
In some circles, it’s better known as ‘The Turing Test;” the Vancouver Art Gallery’s ‘Imitation Game’ hosts a copy of Alan Turing’s foundational paper for establishing whether artificial intelligence is possible (I thought this was pretty exciting).
Here’s more from The Turing Test essay by Graham Oppy and David Dowe for the Stanford Encyclopedia of Philosophy,
The phrase “The Turing Test” is most properly used to refer to a proposal made by Turing (1950) as a way of dealing with the question whether machines can think. According to Turing, the question whether machines can think is itself “too meaningless” to deserve discussion (442). However, if we consider the more precise—and somehow related—question whether a digital computer can do well in a certain kind of game that Turing describes (“The Imitation Game”), then—at least in Turing’s eyes—we do have a question that admits of precise discussion. Moreover, as we shall see, Turing himself thought that it would not be too long before we did have digital computers that could “do well” in the Imitation Game.
The phrase “The Turing Test” is sometimes used more generally to refer to some kinds of behavioural tests for the presence of mind, or thought, or intelligence in putatively minded entities. …
Next to the display holding Turing’s paper, is another display with an excerpt of an explanation from Turing about how he believed Ada Lovelace would have responded to the idea that machines could think based on a copy of some of her writing (also on display). She proposed that creativity, not thinking, is what set people apart from machines. (See the April 17, 2020 article “Thinking Machines? Has the Lovelace Test Been Passed?’ on mindmatters.ai.)
It’s like a dialogue between two seminal thinkers who lived about 100 years apart; Lovelace, born in 1815 and dead in 1852, and Turing, born in 1912 and dead in 1954. Both have fascinating back stories (more about those later) and both played roles in how computers and artificial intelligence are viewed.
Adding some interest to this walk down memory lane is a 3rd display, an illustration of the ‘Mechanical Turk‘, a chess playing machine that made the rounds in Europe from 1770 until it was destroyed in 1854. A hoax that fooled people for quite a while it is a reminder that we’ve been interested in intelligent machines for centuries. (Friend, Turing and Lovelace and the Mechanical Turk are found in Pod 1.)
Back story: Turing and the apple
Turing is credited with being instrumental in breaking the German ENIGMA code during World War II and helping to end the war. I find it odd that he ended up at the University of Manchester in the post-war years. One would expect him to have been at Oxford or Cambridge. At any rate, he died in 1954 of cyanide poisoning two years after he was arrested for being homosexual and convicted of indecency. Given the choice of incarceration or chemical castration, he chose the latter. There is, to this day, debate about whether or not it was suicide. Here’s how his death is described in this Wikipedia entry (Note: Links have been removed),
On 8 June 1954, at his house at 43 Adlington Road, Wilmslow,[150] Turing’s housekeeper found him dead. He had died the previous day at the age of 41. Cyanide poisoning was established as the cause of death.[151] When his body was discovered, an apple lay half-eaten beside his bed, and although the apple was not tested for cyanide,[152] it was speculated that this was the means by which Turing had consumed a fatal dose. An inquest determined that he had committed suicide. Andrew Hodges and another biographer, David Leavitt, have both speculated that Turing was re-enacting a scene from the Walt Disney film Snow White and the Seven Dwarfs (1937), his favourite fairy tale. Both men noted that (in Leavitt’s words) he took “an especially keen pleasure in the scene where the Wicked Queen immerses her apple in the poisonous brew”.[153] Turing’s remains were cremated at Woking Crematorium on 12 June 1954,[154] and his ashes were scattered in the gardens of the crematorium, just as his father’s had been.[155]
Philosopher Jack Copeland has questioned various aspects of the coroner’s historical verdict. He suggested an alternative explanation for the cause of Turing’s death: the accidental inhalation of cyanide fumes from an apparatus used to electroplate gold onto spoons. The potassium cyanide was used to dissolve the gold. Turing had such an apparatus set up in his tiny spare room. Copeland noted that the autopsy findings were more consistent with inhalation than with ingestion of the poison. Turing also habitually ate an apple before going to bed, and it was not unusual for the apple to be discarded half-eaten.[156] Furthermore, Turing had reportedly borne his legal setbacks and hormone treatment (which had been discontinued a year previously) “with good humour” and had shown no sign of despondency prior to his death. He even set down a list of tasks that he intended to complete upon returning to his office after the holiday weekend.[156] Turing’s mother believed that the ingestion was accidental, resulting from her son’s careless storage of laboratory chemicals.[157] Biographer Andrew Hodges theorised that Turing arranged the delivery of the equipment to deliberately allow his mother plausible deniability with regard to any suicide claims.[158]
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The US Central Intelligence Agency (CIA) also has an entry for Alan Turing dated April 10, 2015 it’s titled, The Enigma of Alan Turing.
Back story: Ada Byron Lovelace, the 2nd generation of ‘mad, bad, and dangerous to know’
A mathematician and genius in her own right, Ada Lovelace’s father George Gordon Byron, better known as the poet Lord Byron, was notoriously described as ‘mad, bad, and dangerous to know’.
Lovelace too could have been been ‘mad, bad, …’ but she is described less memorably as “… manipulative and aggressive, a drug addict, a gambler and an adulteress, …” as mentioned in my October 13, 20215 posting. It marked the 200th anniversary of her birth, which was celebrated with a British Broadcasting Corporation (BBC) documentary and an exhibit at the Science Museum in London, UK.
She belongs in the Vancouver Art Gallery’s show along with Alan Turing due to her prediction that computers could be made to create music. She also published the first computer program. Her feat is astonishing when you know only one working model {1/7th of the proposed final size) of a computer was ever produced. (The machine invented by Charles Babbage was known as a difference engine. You can find out more about the Difference engine on Wikipedia and about Babbage’s proposed second invention, the Analytical engine.)
(Byron had almost nothing to do with his daughter although his reputation seems to have dogged her. You can find out more about Lord Byron here.)
Bruce Grenville, VAG Chief/Senior Curator, seems to specialize in pulling together diverse materials to illustrate ‘big’ topics. His profile for Emily Carr University of Art + Design (where Grenville teaches) mentions these shows ,
… He has organized many thematic group exhibitions including, MashUp: The Birth of Modern Culture [emphasis mine], 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; KRAZY! The Delirious World [emphasis mine] of Anime + Manga + Video Games + Art, a timely and important survey of modern and contemporary visual culture from around the world;Home and Away: Crossing Cultures on the Pacific Rim [emphasis mine] a look at the work of six artists from Vancouver, Beijing, Ho Chi Minh City, Seoul and Los Angeles, who share a history of emigration and diaspora. …
Glenn Entis, Guest Curator and founding faculty member of Vancouver’s Centre for Digital Media (CDM) is Grenville’s co-curator, from Entis’ CDM profile,
“… an Academy Award-winning animation pioneer and games industry veteran. The former CEO of Dreamworks Interactive, Glenn worked with Steven Spielberg and Jeffrey Katzenberg on a number of video games …,”
Steve Newton in his March 4, 2022 preview does a good job of describing the show although I strongly disagree with the title of his article which proclaims “The Vancouver Art Gallery takes a deep dive into artificial intelligence with The Imitation Game.” I think it’s more of a shallow dive meant to cover more distance than depth,
… The exhibition kicks off with an interactive introduction inviting visitors to actively identify diverse areas of cultural production influenced by AI.
“That was actually one of the pieces that we produced in collaboration with the Centre for Digital Media,” Grenville notes, “so we worked with some graduate-student teams that had actually helped us to design that software. It was the beginning of COVID when we started to design this, so we actually wanted a no-touch interactive. So, really, the idea was to say, ‘Okay, this is the very entrance to the exhibition, and artificial intelligence, this is something I’ve heard about, but I’m not really sure how it’s utilized in ways. But maybe I know something about architecture; maybe I know something about video games; maybe I know something about the history of film.
“So you point to these 10 categories of visual culture [emphasis mine]–video games, architecture, fashion design, graphic design, industrial design, urban design–so you point to one of those, and you might point to ‘film’, and then when you point at it that opens up into five different examples of what’s in the show, so it could be 2001: A Space Odyssey, or Bladerunner, or World on a Wire.”
After the exhibition’s introduction—which Grenville equates to “opening the door to your curiosity” about artificial intelligence–visitors encounter one of its main categories, Objects of Wonder, which speaks to the history of AI and the critical advances the technology has made over the years.
“So there are 20 Objects of Wonder [emphasis mine],” Grenville says, “which go from 1949 to 2022, and they kind of plot out the history of artificial intelligence over that period of time, focusing on a specific object. Like [mathematician and philosopher] Norbert Wiener made this cybernetic creature, he called it a ‘Moth’, in 1949. So there’s a section that looks at this idea of kind of using animals–well, machine animals–and thinking about cybernetics, this idea of communication as feedback, early thinking around neuroscience and how neuroscience starts to imagine this idea of a thinking machine.
“It’s interesting,” Grenville ponders, “artificial intelligence is virtually unregulated. [emphasis mine] You know, if you think about the regulatory bodies that govern TV or radio or all the types of telecommunications, there’s no equivalent for artificial intelligence, which really doesn’t make any sense. And so what happens is, sometimes with the best intentions [emphasis mine]—sometimes not with the best intentions—choices are made about how artificial intelligence develops. So one of the big ones is facial-recognition software [emphasis mine], and any body-detection software that’s being utilized.
In addition to it being the best overview of the show I’ve seen so far, this is the only one where you get a little insight into what the curators were thinking when they were developing it.
A deep dive into AI?
it was only while searching for a little information before the show that I realized I don’t have any definitions for artificial intelligence! What is AI? Sadly, there are no definitions of AI in the exhibit.
It seems even experts don’t have a good definition. Take a look at this,
The definition of AI is fluid [emphasis mine] and reflects a constantly shifting landscape marked by technological advancements and growing areas of application. Indeed, it has frequently been observed that once AI becomes capable of solving a particular problem or accomplishing a certain task, it is often no longer considered to be “real” intelligence [emphasis mine] (Haenlein & Kaplan, 2019). A firm definition was not applied for this report [emphasis mine], given the variety of implementations described above. However, for the purposes of deliberation, the Panel chose to interpret AI as a collection of statistical and software techniques, as well as the associated data and the social context in which they evolve — this allows for a broader and more inclusive interpretation of AI technologies and forms of agency. The Panel uses the term AI interchangeably to describe various implementations of machine-assisted design and discovery, including those based on machine learning, deep learning, and reinforcement learning, except for specific examples where the choice of implementation is salient. [p. 6 print version; p. 34 PDF version]
Sometimes a show will take you in an unexpected direction. I feel a lot better ‘not knowing’. Still, I wish the curators had acknowledged somewhere in the show that artificial intelligence is a slippery concept. Especially when you add in robots and automatons. (more about them later)
21st century technology in a 19th/20th century building
Void stairs inside the building. Completed in 1906, the building was later designated as a National Historic Site in 1980 [downloaded from https://en.wikipedia.org/wiki/Vancouver_Art_Gallery#cite_note-canen-7]
Just barely making it into the 20th century, the building where the Vancouver Art Gallery currently resides was for many years the provincial courthouse (1911 – 1978). In some ways, it’s a disconcerting setting for this show.
They’ve done their best to make the upstairs where the exhibit is displayed look like today’s galleries with their ‘white cube aesthetic’ and strong resemblance to the scientific laboratories seen in movies.
(For more about the dominance, since the 1930s, of the ‘white cube aesthetic’ in art galleries around the world, see my July 26, 2021 posting; scroll down about 50% of the way.)
It makes for an interesting tension, the contrast between the grand staircase, the cupola, and other architectural elements and the sterile, ‘laboratory’ environment of the modern art gallery.
20 Objects of Wonder and the flow of the show
It was flummoxing. Where are the 20 objects? Why does it feel like a maze in a laboratory? Loved the bees, but why? Eeeek Creepers! What is visual culture anyway? Where am I?
The objects of the show
It turns out that the curators have a more refined concept for ‘object’ than I do. There weren’t 20 material objects, there were 20 numbered ‘pods’ with perhaps a screen or a couple of screens or a screen and a material object or two illustrating the pod’s topic.
Looking up a definition for the word (accessed from a June 9, 2022 duckduckgo.com search). yielded this, (the second one seems à propos),
objectŏb′jĭkt, -jĕkt″
noun
1. Something perceptible by one or more of the senses, especially by vision or touch; a material thing.
2. A focus of attention, feeling, thought, or action.
3. A limiting factor that must be considered.
The American Heritage® Dictionary of the English Language, 5th Edition.
Each pod = a focus of attention.
The show’s flow is a maze. Am I a rat?
The pods are defined by a number and by temporary walls. So if you look up, you’ll see a number and a space partly enclosed by a temporary wall or two.
It’s a very choppy experience. For example, one minute you can be in pod 1 and, when you turn the corner, you’re in pod 4 or 5 or ? There are pods I’ve not seen, despite my two visits, because I kept losing my way. This led to an existential crisis on my second visit. “Had I missed the greater meaning of this show? Was there some sort of logic to how it was organized? Was there meaning to my life? Was I a rat being nudged around in a maze?” I didn’t know.
Thankfully, I have since recovered. But, I will return to my existential crisis later, with a special mention for “Creepers.”
The fascinating
My friend, you know I appreciated the history and in addition to Alan Turing, Ada Lovelace and the Mechanical Turk, at the beginning of the show, they included a reference to Ovid (or Pūblius Ovidius Nāsō), a Roman poet who lived from 43 BCE – 17/18 CE in one of the double digit (17? or 10? or …) in one of the pods featuring a robot on screen. As to why Ovid might be included, this excerpt from a February 12, 2018 posting on the cosmolocal.org website provides a clue (Note. Links have been removed),
The University of King’s College [Halifax, Nova Scotia] presents Automatons! From Ovid to AI, a nine-lecture series examining the history, issues and relationships between humans, robots, and artificial intelligence [emphasis mine]. The series runs from January 10 to April 4 [2018], and features leading scholars, performers and critics from Canada, the US and Britain.
“Drawing from theatre, literature, art, science and philosophy, our 2018 King’s College Lecture Series features leading international authorities exploring our intimate relationships with machines,” says Dr. Gordon McOuat, professor in the King’s History of Science and Technology (HOST) and Contemporary Studies Programs.
…
“From the myths of Ovid [emphasis mine] and the automatons [emphasis mine] of the early modern period to the rise of robots, cyborgs, AI and artificial living things in the modern world, the 2018 King’s College Lecture Series examines the historical, cultural, scientific and philosophical place of automatons in our lives—and our future,” adds McOuat.
…
I loved the way the curators managed to integrate the historical roots for artificial intelligence and, by extension, the world of automatons, robots, cyborgs, and androids. Yes, starting the show with Alan Turing and Ada Lovelace could be expected but Norbert Wiener’s Moth (1949) acts as a sort of preview for Sougwen Chung’s “Omnia per Omnia, 2018” (GIF seen at the beginning of this post). Take a look for yourself (from the cyberneticzoo.com September 19, 2009 posting by cyberne1. Do you see the similarity or am I the only one?
[sourced from Google images, Source:life) & downloaded from https://cyberneticzoo.com/cyberneticanimals/1949-wieners-moth-wiener-wiesner-singleton/]
Sculpture
This is the first time I’ve come across an AI/sculpture project. The VAG show features Scott Eaton’s sculptures on screens in a room devoted to his work.
Scott Eaton: Entangled II, 2019
4k video (still) Courtesy of the Artist [downloaded from https://www.vanartgallery.bc.ca/exhibitions/the-imitation-game]
This looks like an image of a piece of ginger root and It’s fascinating to watch the process as the AI agent ‘evolves’ Eaton’s drawings into onscreen sculptures. It would have enhanced the experience if at least one of Eaton’s ‘evolved’ and physically realized sculptures had been present in the room but perhaps there were financial and/or logistical reasons for the absence.
Both Chung and Eaton are collaborating with an AI agent. In Chung’s case the AI is integrated into the paintbots with which she interacts and paints alongside and in Eaton’s case, it’s via a computer screen. In both cases, the work is mildly hypnotizing in a way that reminds me of lava lamps.
One last note about Chung and her work. She was one of the artists invited to present new work at an invite-only April 22, 2022 Embodied Futures workshop at the “What will life become?” event held by the Berrgruen Institute and the University of Southern California (USC),
Embodied Futures invites participants to imagine novel forms of life, mind, and being through artistic and intellectual provocations on April 22 [2022].
Beginning at 1 p.m., together we will experience the launch of five artworks commissioned by the Berggruen Institute. We asked these artists: How does your work inflect how we think about “the human” in relation to alternative “embodiments” such as machines, AIs, plants, animals, the planet, and possible alien life forms in the cosmos? [emphases mine] Later in the afternoon, we will take provocations generated by the morning’s panels and the art premieres in small breakout groups that will sketch futures worlds, and lively entities that might dwell there, in 2049.
…
This leads to (and my friend, while I too am taking a shallow dive, for this bit I’m going a little deeper):
Bees and architecture
Neri Oxman’s contribution (Golden Bee Cube, Synthetic Apiary II [2020]) is an exhibit featuring three honeycomb structures and a video featuring the bees in her synthetic apiary.
Neri Oxman and the MIT Mediated Matter Group, Golden Bee Cube, Synthetic Apiary II, 2020, beeswax, acrylic, gold particles, gold powder Courtesy of Neri Oxman and the MIT Mediated Matter Group
Neri Oxman (then a faculty member of the Mediated Matter Group at the Massachusetts Institute of Technology) described the basis for the first and all other iterations of her synthetic apiary in Patrick Lynch’s October 5, 2016 article for ‘ArchDaily; Broadcasting Architecture Worldwide’, Note: Links have been removed,
Designer and architect Neri Oxman and the Mediated Matter group have announced their latest design project: the Synthetic Apiary. Aimed at combating the massive bee colony losses that have occurred in recent years, the Synthetic Apiary explores the possibility of constructing controlled, indoor environments that would allow honeybee populations to thrive year-round.
…
“It is time that the inclusion of apiaries—natural or synthetic—for this “keystone species” be considered a basic requirement of any sustainability program,” says Oxman.
In developing the Synthetic Apiary, Mediated Matter studied the habits and needs of honeybees, determining the precise amounts of light, humidity and temperature required to simulate a perpetual spring environment. [emphasis mine] They then engineered an undisturbed space where bees are provided with synthetic pollen and sugared water and could be evaluated regularly for health.
…
In the initial experiment, the honeybees’ natural cycle proved to adapt to the new environment, as the Queen was able to successfully lay eggs in the apiary. The bees showed the ability to function normally in the environment, suggesting that natural cultivation in artificial spaces may be possible across scales, “from organism- to building-scale.”
“At the core of this project is the creation of an entirely synthetic environment enabling controlled, large-scale investigations of hives,” explain the designers.
…
Mediated Matter chose to research into honeybees not just because of their recent loss of habitat, but also because of their ability to work together to create their own architecture, [emphasis mine] a topic the group has explored in their ongoing research on biologically augmented digital fabrication, including employing silkworms to create objects and environments at product, architectural, and possibly urban, scales.
“The Synthetic Apiary bridges the organism- and building-scale by exploring a “keystone species”: bees. Many insect communities present collective behavior known as “swarming,” prioritizing group over individual survival, while constantly working to achieve common goals. Often, groups of these eusocial organisms leverage collaborative behavior for relatively large-scale construction. For example, ants create extremely complex networks by tunneling, wasps generate intricate paper nests with materials sourced from local areas, and bees deposit wax to build intricate hive structures.”
…
This January 19, 2022 article by Crown Honey for its eponymous blog updates Oxman’s work (Note 1: All emphases are mine; Note 2: A link has been removed),
…
Synthetic Apiary II investigates co-fabrication between humans and honey bees through the use of designed environments in which Apis mellifera colonies construct comb. These designed environments serve as a means by which to convey information to the colony. The comb that the bees construct within these environments comprises their response to the input information, enabling a form of communication through which we can begin to understand the hive’s collective actions from their perspective.
Some environments are embedded with chemical cues created through a novel pheromone 3D-printing process, while others generate magnetic fields of varying strength and direction. Others still contain geometries of varying complexity or designs that alter their form over time.
When offered wax augmented with synthetic biomarkers, bees appear to readily incorporate it into their construction process, likely due to the high energy cost of producing fresh wax. This suggests that comb construction is a responsive and dynamic process involving complex adaptations to perturbations from environmental stimuli, not merely a set of predefined behaviors building toward specific constructed forms. Each environment therefore acts as a signal that can be sent to the colony to initiate a process of co-fabrication.
Characterization of constructed comb morphology generally involves visual observation and physical measurements of structural features—methods which are limited in scale of analysis and blind to internal architecture. In contrast, the wax structures built by the colonies in Synthetic Apiary II are analyzed through high-throughput X-ray computed tomography (CT) scans that enable a more holistic digital reconstruction of the hive’s structure.
Geometric analysis of these forms provides information about the hive’s design process, preferences, and limitations when tied to the inputs, and thereby yields insights into the invisible mediations between bees and their environment. Developing computational tools to learn from bees can facilitate the very beginnings of a dialogue with them. Refined by evolution over hundreds of thousands of years, their comb-building behaviors and social organizations may reveal new forms and methods of formation that can be applied across our human endeavors in architecture, design, engineering, and culture.
Further, with a basic understanding and language established, methods of co-fabrication together with bees may be developed, enabling the use of new biocompatible materials and the creation of more efficient structural geometries that modern technology alone cannot achieve.
In this way, we also move our built environment toward a more synergistic embodiment, able to be more seamlessly integrated into natural environments through material and form, even providing habitats of benefit to both humans and nonhumans. It is essential to our mutual survival for us to not only protect but moreover to empower these critical pollinators – whose intrinsic behaviors and ecosystems we have altered through our industrial processes and practices of human-centric design – to thrive without human intervention once again.
In order to design our way out of the environmental crisis that we ourselves created, we must first learn to speak nature’s language. …
The three (natural, gold nanoparticle, and silver nanoparticle) honeycombs in the exhibit are among the few physical objects (the others being the historical documents and the paintbots with their canvasses) in the show and it’s almost a relief after the parade of screens. It’s the accompanying video that’s eerie. Everything is in white, as befits a science laboratory, in this synthetic apiary where bees are fed sugar water and fooled into a spring that is eternal.
Courtesy: Massachusetts Institute of Technology Copyright: Mediated Matter [downloaded from https://www.media.mit.edu/projects/synthetic-apiary/overview/]
(You may want to check out Lynch’s October 5, 2016 article or Crown Honey’s January 19, 2022 article as both have embedded images and the Lynch article includes a Synthetic Apiary video. The image above is a still from the video.)
As I asked a friend, where are the flowers? Ron Miksha, a bee ecologist working at the University of Calgary, details some of the problems with Oxman’s Synthetic Apiary this way in his October 7, 2016 posting on his Bad Beekeeping Blog,
In a practical sense, the synthetic apiary fails on many fronts: Bees will survive a few months on concoctions of sugar syrup and substitute pollen, but they need a natural variety of amino acids and minerals to actually thrive. They need propolis and floral pollen. They need a ceiling 100 metres high and a 2-kilometre hallway if drone and queen will mate, or they’ll die after the old queen dies. They need an artificial sun that travels across the sky, otherwise, the bees will be attracted to artificial lights and won’t return to their hive. They need flowery meadows, fresh water, open skies. [emphasis mine] They need a better holodeck.
Dorothy Woodend’s March 10, 2022 review of the VAG show for The Tyee poses other issues with the bees and the honeycombs,
…
When AI messes about with other species, there is something even more unsettling about the process. American-Israeli artist Neri Oxman’s Golden Bee Cube, Synthetic Apiary II, 2020 uses real bees who are proffered silver and gold [nanoparticles] to create their comb structures. While the resulting hives are indeed beautiful, rendered in shades of burnished metal, there is a quality of unease imbued in them. Is the piece akin to apiary torture chambers? I wonder how the bees feel about this collaboration and whether they’d like to renegotiate the deal.
…
There’s no question the honeycombs are fascinating and disturbing but I don’t understand how artificial intelligence was a key factor in either version of Oxman’s synthetic apiary. In the 2022 article by Crown Honey, there’s this “Developing computational tools to learn from bees can facilitate the very beginnings of a dialogue with them [honeybees].” It’s probable that the computational tools being referenced include AI and the Crown Honey article seems to suggest those computational tools are being used to analyze the bees behaviour after the fact.
Yes, I can imagine a future where ‘strong’ AI (such as you, my friend) is in ‘dialogue’ with the bees and making suggestions and running the experiments but it’s not clear that this is the case currently. The Oxman exhibit contribution would seem to be about the future and its possibilities whereas many of the other ‘objects’ concern the past and/or the present.
Friend, let’s take a break, shall we? Part 2 is coming up.
The Turing test first known as the ‘Imitation Game’, was designed by scientist Alan Turing in 1950 to see if a machine’s behaviour (in this case, a ‘conversation’) could fool someone into believing it was human. It’s a basic test to help determine true artificial intelligence.
These days ‘artificial intelligence’ seems to be everywhere, although I’m not sure that all these algorithms would pass the Turing test. Some of the latest material I’ve seen suggests that writers and editors may have to rethink their roles in future. Let’s start with the beer and wine reviews.
In mid-2020, the computer science team of Keith Carlson, Allen Riddell and Dan Rockmore was stuck on a problem. It wasn’t a technical challenge. The computer code they had developed to write product reviews was working beautifully. But they were struggling with a practical question.
“Getting the code to write reviews was only the first part of the challenge,” says Carlson, Guarini ’21, a doctoral research fellow at the Tuck School of Business, “The remaining challenge was figuring out how and where it could be used.”
The original study took on two challenges: to design code that could write original, human-quality product reviews using a small set of product features and to see if the algorithm could be adapted to write “synthesis reviews” for products from a large number of existing reviews.
Review writing can be challenging because of the overwhelming number of products available. The team wanted to see if artificial intelligence was up to the task of writing opinionated text about vast product classes.
They focused on wine and beer reviews because of the extensive availability of material to train the algorithm. The relatively narrow vocabularies used to describe the products also makes it open to the techniques of AI systems and natural language processing tools.
The project was kickstarted by Riddell, a former fellow at the Neukom Institute for Computational Science, and developed with Carlson under the guidance of Rockmore, the William H. Neukom 1964 Distinguished Professor of Computational Science.
The code couldn’t taste the products, but it did ingest reams of written material. After training the algorithm on hundreds of thousands of published wine and beer reviews, the team found that the code could complete both tasks.
One result read: “This is a sound Cabernet. It’s very dry and a little thin in blackberry fruit, which accentuates the acidity and tannins. Drink up.”
Another read: “Pretty dark for a rosé, and full-bodied, with cherry, raspberry, vanilla and spice flavors. It’s dry with good acidity.”
“But now what?” Carlson explains as a question that often gnaws at scientists. The team wondered, “Who else would care?”
“I didn’t want to quit there,” says Rockmore. “I was sure that this work could be interesting to a wider audience.”
Sensing that the paper could have relevance in marketing, the team walked the study to Tuck Drive to see what others would think.
“Brilliant,” Praveen Kopalle, the Signal Companies’ Professor of Management at Tuck School of Business, recalls thinking when first reviewing the technical study.
Kopalle knew that the research was important. It could even “disrupt” the online review industry, a huge marketplace of goods and services.
“The paper has a lot of marketing applications, particularly in the context of online reviews where we can create reviews or descriptions of products when they may not already exist,” adds Kopalle. “In fact, we can even think about summarizing reviews for products and services as well.”
With the addition of Prasad Vana, assistant professor of business administration at Tuck, the team was complete. Vana reframed the technical feat of creating review-writing code into that of a market-friendly tool that can assist consumers, marketers, and professional reviewers.
“This is a sound Cabernet. It’s very dry and a little thin in blackberry fruit, which accentuates the acidity and tannins. Drink up.” Attribution: Artificial Intelligence review from Dartmouth project
The resulting research, published in International Journal of Research in Marketing, surveyed independent participants to confirm that the AI system wrote human-like reviews in both challenges.
“Using artificial intelligence to write and synthesize reviews can create efficiencies on both sides of the marketplace,” said Vana. “The hope is that AI can benefit reviewers facing larger writing workloads and consumers who have to sort through so much content about products.”
The paper also dwells on the ethical concerns raised by computer-generated content. It notes that marketers could get better acceptance by falsely attributing the reviews to humans. To address this, the team advocates for transparency when computer-generated text is used.
They also address the issue of computers taking human jobs. Code should not replace professional product reviewers, the team insists in the paper. The technology is meant to make the tasks of producing and reading the material more efficient. [emphasis mine]
“It’s interesting to imagine how this could benefit restaurants that cannot afford sommeliers or independent sellers on online platforms who may sell hundreds of products,” says Vana.
According to Carlson, the paper’s first author, the project demonstrates the potential of AI, the power of innovative thinking, and the promise of cross-campus collaboration.
“It was wonderful to work with colleagues with different expertise to take a theoretical idea and bring it closer to the marketplace,” says Carlson. “Together we showed how our work could change marketing and how people could use it. That could only happen with collaboration.”
A revised April 29, 2022 version was published on EurekAlert and some of the differences are interesting (to me, if no one else). As you see, there’s a less ‘friendly’ style and the ‘jobs’ issue has been approached differently. Note: Links have been removed,
Artificial intelligence systems can be trained to write human-like product reviews that assist consumers, marketers and professional reviewers, according to a study from Dartmouth College, Dartmouth’s Tuck School of Business, and Indiana University.
The research, published in the International Journal of Research in Marketing, also identifies ethical challenges raised by the use of the computer-generated content.
“Review writing is challenging for humans and computers, in part, because of the overwhelming number of distinct products,” said Keith Carlson, a doctoral research fellow at the Tuck School of Business. “We wanted to see how artificial intelligence can be used to help people that produce and use these reviews.”
For the research, the Dartmouth team set two challenges. The first was to determine whether a machine can be taught to write original, human-quality reviews using only a small number of product features after being trained on a set of existing content. Secondly, the team set out to see if machine learning algorithms can be used to write syntheses of reviews of products for which many reviews already exist.
“Using artificial intelligence to write and synthesize reviews can create efficiencies on both sides of the marketplace,” said Prasad Vana, assistant professor of business administration at Tuck School of Business. “The hope is that AI can benefit reviewers facing larger writing workloads and consumers that have to sort through so much content about products.”
The researchers focused on wine and beer reviews because of the extensive availability of material to train the computer algorithms. Write-ups of these products also feature relatively focused vocabularies, an advantage when working with AI systems.
To determine whether a machine could write useful reviews from scratch, the researchers trained an algorithm on about 180,000 existing wine reviews. Metadata tags for factors such as product origin, grape variety, rating, and price were also used to train the machine-learning system.
When comparing the machine-generated reviews against human reviews for the same wines, the research team found agreement between the two versions. The results remained consistent even as the team challenged the algorithms by changing the amount of input data that was available for reference.
The machine-written material was then assessed by non-expert study participants to test if they could determine whether the reviews were written by humans or a machine. According to the research paper, the participants were unable to distinguish between the human and AI-generated reviews with any statistical significance. Furthermore, their intent to purchase a wine was similar across human versus machine generated reviews of the wine.
Having found that artificial intelligence can write credible wine reviews, the research team turned to beer reviews to determine the effectiveness of using AI to write “review syntheses.” Rather than being trained to write new reviews, the algorithm was tasked with aggregating elements from existing reviews of the same product. This tested AI’s ability to identify and provide limited but relevant information about products based on a large volume of varying opinions.
“Writing an original review tests the computer’s expressive ability based on a relatively narrow set of data. Writing a synthesis review is a related but distinct task where the system is expected to produce a review that captures some of the key ideas present in an existing set of reviews for a product,” said Carlson, who conducted the research while a PhD candidate in computer science at Dartmouth.
To test the algorithm’s ability to write review syntheses, researchers trained it on 143,000 existing reviews of over 14,000 beers. As with the wine dataset, the text of each review was paired with metadata including the product name, alcohol content, style, and scores given by the original reviewers.
As with the wine reviews, the research used independent study participants to judge whether the machine-written summaries captured and summarized the opinions of numerous reviews in a useful, human-like manner.
According to the paper, the model was successful at taking the reviews of a product as input and generating a synthesis review for that product as output.
“Our modeling framework could be useful in any situation where detailed attributes of a product are available and a written summary of the product is required,” said Vana. “It’s interesting to imagine how this could benefit restaurants that cannot afford sommeliers or independent sellers on online platforms who may sell hundreds of products.”
Both challenges used a deep learning neural net based on transformer architecture to ingest, process and output review language.
According to the research team, the computer systems are not intended to replace professional writers and marketers, but rather to assist them in their work. A machine-written review, for instance, could serve as a time-saving first draft of a review that a human reviewer could then revise. [emphasis mine]
The research can also help consumers. Syntheses reviews—like those on beer in the study—can be expanded to the constellation of products and services in online marketplaces to assist people who have limited time to read through many product reviews.
In addition to the benefits of machine-written reviews, the research team highlights some of the ethical challenges presented by using computer algorithms to influence human consumer behavior.
Noting that marketers could get better acceptance of machine-generated reviews by falsely attributing them to humans, the team advocates for transparency when computer-generated reviews are offered.
“As with other technology, we have to be cautious about how this advancement is used,” said Carlson. “If used responsibly, AI-generated reviews can be both a productivity tool and can support the availability of useful consumer information.”
Researchers contributing to the study include Praveen Kopalle, Dartmouth’s Tuck School of Business; Allen Riddell, Indiana University, and Daniel Rockmore, Dartmouth College.
I wonder if the second news release was written by an AI agent.
Daniel (Dan) Rockmore was mentioned here in a May 6, 2016 posting about a competition he’d set up through Dartmouth College,’s Neukom Institute. The competition, which doesn’t seem to have been run since 2018, was called Turing Tests in Creative Arts.
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In a partnership that began almost two years ago, ACS has now progressed to a full integration of Writefull’s application programming interfaces (APIs) for three key uses.
One of the world’s largest scientific societies, ACS publishes more than 300,000 research manuscripts in more than 60 scholarly journals per year.
Writefull’s proprietary AI technology is trained on millions of scientific papers using Deep Learning. It identifies potential language issues with written texts, offers solutions to those issues, and automatically assesses texts’ language quality. Thanks to Writefull’s APIs, its tech can be applied at all key points in the editorial workflows.
Writefull’s Manuscript Categorization API is now used by ACS before copyediting to automatically classify all accepted manuscripts by their language quality. Using ACS’s own classification criteria, the API assigns a level-of-edit grade to manuscripts at scale without editors having to open documents and review the text. After thorough benchmarking alongside human editors, Writefull reached more than 95% alignment in grading texts, significantly reducing the time ACS spends on manuscript evaluation.
The same Manuscript Categorization API is now part of ACS’s quality control program, to evaluate the language in manuscripts after copyediting.
Writefull’s Metadata API is also being used to automate aspects of manuscript review, ensuring that all elements of an article are complete prior to publication. The same API is used by Open Access publisher Hindawi as a pre-submission structural checks tool for authors.
Juan Castro, co-founder and CEO of Writefull, says: “Our partnership with the American Chemical Society over the past two years has been aimed at thoroughly vetting and shaping our services to meet ACS’s needs. Writefull’s AI-based language services empower publishers to increase their workflow efficiency and positively impact production costs, while also maintaining the quality and integrity of the manuscript.”
Digital Science is a technology company working to make research more efficient. We invest in, nurture and support innovative businesses and technologies that make all parts of the research process more open and effective. Our portfolio includes admired brands including Altmetric, Dimensions, Figshare, ReadCube, Symplectic, IFI CLAIMS, GRID, Overleaf, Ripeta and Writefull. We believe that together, we can help researchers make a difference. Visit www.digital-science.com and follow @digitalsci on Twitter.
Writefull is a technology startup that creates tools to help researchers improve their writing in English. The first version of the Writefull product allowed researchers to discover patterns in academic language, such as frequent word combinations and synonyms in context. The new version utilises Natural Language Processing and Deep Learning algorithms that will give researchers feedback on their full texts. Visit writefull.com and follow @writefullapp on Twitter.
The American Chemical Society (ACS) is a nonprofit organization chartered by the U.S. Congress. ACS’ mission is to advance the broader chemistry enterprise and its practitioners for the benefit of Earth and all its people. The Society is a global leader in promoting excellence in science education and providing access to chemistry-related information and research through its multiple research solutions, peer-reviewed journals, scientific conferences, eBooks and weekly news periodical Chemical & Engineering News. ACS journals are among the most cited, most trusted and most read within the scientific literature; however, ACS itself does not conduct chemical research. As a leader in scientific information solutions, its CAS division partners with global innovators to accelerate breakthroughs by curating, connecting and analyzing the world’s scientific knowledge. ACS’ main offices are in Washington, D.C., and Columbus, Ohio. Visit www.acs.org and follow @AmerChemSociety on Twitter.
So what?
An artificial intelligence (AI) agent being used for writing assignments is not new (see my July 16, 2014 posting titled, “Writing and AI or is a robot writing this blog?“). The argument that these agents will assist rather than replace (pick an occupation: e.g., writers, doctors, programmers, scientists, etc) is almost always used as scientists explain that AI agents will take over the boring work giving you (the human) more opportunities to do interesting work. The AI-written beer and wine reviews described here support at least part of the argument—for the time being.
It’s true that an AI agent can’t taste beer or wine but that can change as this August 8, 2019 article by Alice Johnston for CNN hints (Note: Links have been removed),
An artificial “tongue” that can taste minute differences between varieties of Scotch whisky could be the key to identifying counterfeit alcohol, scientists say.
Engineers from the universities of Glasgow and Strathclyde in Scotland created a device made of gold and aluminum and measured how it absorbed light when submerged in different kinds of whisky.
Analysis of the results allowed the scientists to identify the samples from Glenfiddich, Glen Marnoch and Laphroaig with more than 99% accuracy
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BTW, my earliest piece on artificial tongues is a July 28, 2011 posting, “Bio-inspired electronic tongue replaces sommelier?,” about research in Spain.
For a contrast, this is the first time I can recall seeing anything about an artificial intelligence agent that edits and Writefall’s use at the ACS falls into the ‘doing all the boring work’ category and narrative quite neatly.
Having looked at a definition of the various forms of editing and core skills, I”m guessing that AI will take over every aspect (from the Editors’ Association of Canada, Definitions of Editorial Skills webpage),
CORE SKILLS
Structural Editing
Assessing and shaping draft material to improve its organization and content. Changes may be suggested to or drafted for the writer. Structural editing may include:
revising, reordering, cutting, or expanding material
writing original material
determining whether permissions are necessary for third-party material
recasting material that would be better presented in another form, or revising material for a different medium (such as revising print copy for web copy)
clarifying plot, characterization, or thematic elements
Also known as substantive editing, manuscript editing, content editing, or developmental editing.
Stylistic Editing
Editing to clarify meaning, ensure coherence and flow, and refine the language. It includes:
eliminating jargon, clichés, and euphemisms
establishing or maintaining the language level appropriate for the intended audience, medium, and purpose
adjusting the length and structure of sentences and paragraphs
establishing or maintaining tone, mood, style, and authorial voice or level of formality
Also known as line editing (which may also include copy editing).
Copy Editing
Editing to ensure correctness, accuracy, consistency, and completeness. It includes:
editing for grammar, spelling, punctuation, and usage
checking for consistency and continuity of mechanics and facts, including anachronisms, character names, and relationships
editing tables, figures, and lists
notifying designers of any unusual production requirements
developing a style sheet or following one that is provided
correcting or querying general information that should be checked for accuracy
It may also include:
marking levels of headings and the approximate placement of art
Canadianizing or other localizing
converting measurements
providing or changing the system of citations
editing indexes
obtaining or listing permissions needed
checking front matter, back matter, and cover copy
checking web links
Note that “copy editing” is often loosely used to include stylistic editing, structural editing, fact checking, or proofreading. Editors Canada uses it only as defined above.
Proofreading
Examining material after layout or in its final format to correct errors in textual and visual elements. The material may be read in isolation or against a previous version. It includes checking for:
adherence to design
minor mechanical errors (such as spelling mistakes or deviations from style sheet)
consistency and accuracy of elements in the material (such as cross-references, running heads, captions, web page heading tags, hyperlinks, and metadata)
It may also include:
distinguishing between printer’s, designer’s, or programmer’s errors and writer’s or editor’s alterations
copyfitting
flagging or checking locations of art
inserting page numbers or checking them against content and page references
Note that proofreading is checking a work after editing; it is not a substitute for editing.
I’m just as happy to get rid of ‘boring’ parts of my work as anyone else but that’s how I learned in the first place and I haven’t seen any discussion about the importance of boring, repetitive tasks for learning.
Metaphors can be powerful in both good ways and bad. I once read that there was a ‘lighthouse’ metaphor used to explain a scientific concept to high school students which later caused problems for them when they were studying the biological sciences as university students. It seems there’s research now to back up the assertion about metaphors and their powers. From an Oct. 7, 2016 news item on phys.org,
Whether ideas are “like a light bulb” or come forth as “nurtured seeds,” how we describe discovery shapes people’s perceptions of both inventions and inventors. Notably, Kristen Elmore (Bronfenbrenner Center for Translational Research at Cornell University) and Myra Luna-Lucero (Teachers College, Columbia University) have shown that discovery metaphors influence our perceptions of the quality of an idea and of the ability of the idea’s creator. The research appears in the journal Social Psychological and Personality Science.
While the metaphor that ideas appear “like light bulbs” is popular and appealing, new research shows that discovery metaphors influence our understanding of the scientific process and perceptions of the ability of inventors based on their gender. [downloaded from http://www.spsp.org/news-center/press-release/metaphors-bias-perception]
While those involved in research know there are many trials and errors and years of work before something is understood, discovered or invented, our use of words for inspiration may have an unintended and underappreciated effect of portraying good ideas as a sudden and exceptional occurrence.
In a series of experiments, Elmore and Luna-Lucero tested how people responded to ideas that were described as being “like a light bulb,” “nurtured like a seed,” or a neutral description.
According the authors, the “light bulb metaphor implies that ‘brilliant’ ideas result from sudden and spontaneous inspiration, bestowed upon a chosen few (geniuses) while the seed metaphor implies that ideas are nurtured over time, ‘cultivated’ by anyone willing to invest effort.”
The first study looked at how people reacted to a description of Alan Turing’s invention of a precursor to the modern computer. It turns out light bulbs are more remarkable than seeds.
“We found that an idea was seen as more exceptional when described as appearing like a light bulb rather than nurtured like a seed,” said Elmore.
But this pattern changed when they used these metaphors to describe a female inventor’s ideas. When using the “like a light bulb” and “nurtured seed” metaphors, the researchers found “women were judged as better idea creators than men when ideas were described as nurtured over time like seeds.”
The results suggest gender stereotypes play a role in how people perceived the inventors.
In the third study, the researchers presented participants with descriptions of the work of either a female (Hedy Lamarr) or a male (George Antheil) inventor, who together created the idea for spread-spectrum technology (a precursor to modern wireless communications). Indeed, the seed metaphor “increased perceptions that a female inventor was a genius, while the light bulb metaphor was more consistent with stereotypical views of male genius,” stated Elmore.
Elmore plans to expand upon their research on metaphors by examining the interactions of teachers and students in real world classroom settings.
“The ways that teachers and students talk about ideas may impact students’ beliefs about how good ideas are created and who is likely to have them,” said Elmore. “Having good ideas is relevant across subjects—whether students are creating a hypothesis in science or generating a thesis for their English paper—and language that stresses the role of effort rather than inspiration in creating ideas may have real benefits for students’ motivation.”
While Elmore and Luna-Lucero are focused on a nuanced analysis of specific metaphors, Richard Holmes’s book, ‘The Age of Wonder: How the Romantic Generation Discovered the Beauty and Terror of Science’, notes that the ‘Eureka’ (light bulb) moment for scientific discovery and the notion of a ‘single great man’ (a singular genius) as the discoverer has its roots in romantic (Shelley, Keats, etc.) poetry.
There’s an intriguing competition taking place at Dartmouth College (US) according to a May 2, 2016 piece on phys.org (Note: Links have been removed),
Algorithms help us to choose which films to watch, which music to stream and which literature to read. But what if algorithms went beyond their jobs as mediators of human culture and started to create culture themselves?
In 1950 English mathematician and computer scientist Alan Turing published a paper, “Computing Machinery and Intelligence,” which starts off by proposing a thought experiment that he called the “Imitation Game.” In one room is a human “interrogator” and in another room a man and a woman. The goal of the game is for the interrogator to figure out which of the unknown hidden interlocutors is the man and which is the woman. This is to be accomplished by asking a sequence of questions with responses communicated either by a third party or typed out and sent back. “Winning” the Imitation Game means getting the identification right on the first shot.
Turing then modifies the game by replacing one interlocutor with a computer, and asks whether a computer will be able to converse sufficiently well that the interrogator cannot tell the difference between it and the human. This version of the Imitation Game has come to be known as the “Turing Test.”
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On May 18 [2016] at Dartmouth, we will explore a different area of intelligence, taking up the question of distinguishing machine-generated art. Specifically, in our “Turing Tests in the Creative Arts,” we ask if machines are capable of generating sonnets, short stories, or dance music that is indistinguishable from human-generated works, though perhaps not yet so advanced as Shakespeare, O. Henry or Daft Punk.
The piece on phys.org is a crossposting of a May 2, 2016 article by Michael Casey and Daniel N. Rockmore for The Conversation. The article goes on to describe the competitions,
The dance music competition (“Algorhythms”) requires participants to construct an enjoyable (fun, cool, rad, choose your favorite modifier for having an excellent time on the dance floor) dance set from a predefined library of dance music. In this case the initial random “seed” is a single track from the database. The software package should be able to use this as inspiration to create a 15-minute set, mixing and modifying choices from the library, which includes standard annotations of more than 20 features, such as genre, tempo (bpm), beat locations, chroma (pitch) and brightness (timbre).
In what might seem a stiffer challenge, the sonnet and short story competitions (“PoeTix” and “DigiLit,” respectively) require participants to submit self-contained software packages that upon the “seed” or input of a (common) noun phrase (such as “dog” or “cheese grater”) are able to generate the desired literary output. Moreover, the code should ideally be able to generate an infinite number of different works from a single given prompt.
To perform the test, we will screen the computer-made entries to eliminate obvious machine-made creations. We’ll mix human-generated work with the rest, and ask a panel of judges to say whether they think each entry is human- or machine-generated. For the dance music competition, scoring will be left to a group of students, dancing to both human- and machine-generated music sets. A “winning” entry will be one that is statistically indistinguishable from the human-generated work.
The competitions are open to any and all comers [competition is now closed; the deadline was April 15, 2016]. To date, entrants include academics as well as nonacademics. As best we can tell, no companies have officially thrown their hats into the ring. This is somewhat of a surprise to us, as in the literary realm companies are already springing up around machine generation of more formulaic kinds of “literature,” such as earnings reports and sports summaries, and there is of course a good deal of AI automation around streaming music playlists, most famously Pandora.
The authors discuss issues with judging the entries,
Evaluation of the entries will not be entirely straightforward. Even in the initial Imitation Game, the question was whether conversing with men and women over time would reveal their gender differences. (It’s striking that this question was posed by a closeted gay man [Alan Turing].) The Turing Test, similarly, asks whether the machine’s conversation reveals its lack of humanity not in any single interaction but in many over time.
It’s also worth considering the context of the test/game. Is the probability of winning the Imitation Game independent of time, culture and social class? Arguably, as we in the West approach a time of more fluid definitions of gender, that original Imitation Game would be more difficult to win. Similarly, what of the Turing Test? In the 21st century, our communications are increasingly with machines (whether we like it or not). Texting and messaging have dramatically changed the form and expectations of our communications. For example, abbreviations, misspellings and dropped words are now almost the norm. The same considerations apply to art forms as well.
The authors also pose the question: Who is the artist?
Thinking about art forms leads naturally to another question: who is the artist? Is the person who writes the computer code that creates sonnets a poet? Is the programmer of an algorithm to generate short stories a writer? Is the coder of a music-mixing machine a DJ?
Where is the divide between the artist and the computational assistant and how does the drawing of this line affect the classification of the output? The sonnet form was constructed as a high-level algorithm for creative work – though one that’s executed by humans. Today, when the Microsoft Office Assistant “corrects” your grammar or “questions” your word choice and you adapt to it (either happily or out of sheer laziness), is the creative work still “yours” or is it now a human-machine collaborative work?
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That’s an interesting question and one I asked in the context of two ‘mashup’ art exhibitions in Vancouver (Canada) in my March 8, 2016 posting.
Getting back to back to Dartmouth College and its Neukom Institute Prizes in Computational Arts, here’s a list of the competition judges from the competition homepage,
The announcements will be made Wednesday, May 18, 2016. I can hardly wait!
Addendum
Martin Robbins has written a rather amusing May 6, 2016 post for the Guardian science blogs on AI and art critics where he also notes that the question: What is art? is unanswerable (Note: Links have been removed),
Jonathan Jones is unhappy about artificial intelligence. It might be hard to tell from a casual glance at the art critic’s recent column, “The digital Rembrandt: a new way to mock art, made by fools,” but if you look carefully the subtle clues are there. His use of the adjectives “horrible, tasteless, insensitive and soulless” in a single sentence, for example.
The source of Jones’s ire is a new piece of software that puts… I’m so sorry… the ‘art’ into ‘artificial intelligence’. By analyzing a subset of Rembrandt paintings that featured ‘bearded white men in their 40s looking to the right’, its algorithms were able to extract the key features that defined the Dutchman’s style. …
Of course an artificial intelligence is the worst possible enemy of a critic, because it has no ego and literally does not give a crap what you think. An arts critic trying to deal with an AI is like an old school mechanic trying to replace the battery in an iPhone – lost, possessing all the wrong tools and ultimately irrelevant. I’m not surprised Jones is angry. If I were in his shoes, a computer painting a Rembrandt would bring me out in hives.
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Can a computer really produce art? We can’t answer that without dealing with another question: what exactly is art? …
I wonder what either Robbins or Jones will make of the Dartmouth competition?
Ada Lovelace Day! Yes, it’s today, Tuesday, Oct. 13, 2015, the day after Thanksgiving. (You can check out my Oct. 14, 2014 posting for a brief Ada Lovelace history and information about an opera based on her life.)
Ada Lovelace Day was founded in 2009 by Suw Charman-Anderson and 2015 seems to have been a banner year for Lovelace where 200th anniversary of her birth is being celebrated not only with a Day featuring events around the world but also with an exhibit in the Science Museum (London, UK) and a documentary on the BBC (British Broadcasting Corporation). An Oct. 12, 2015 article by Zoe Kleinman for BBC news online features both the exhibit and the documentary (Note: A link has been removed),
An exhibition showcasing the work and life of Victorian mathematician Ada Lovelace opens at the Science Museum in London this week [on Oct. 13, 2015].
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The small exhibition includes a working model of the machine, which was never built because of funding issues.
Also on display is a lock of her hair.
Ada Lovelace was often unwell and was prescribed the opiate laudanum, to be taken with wine, by her doctor.
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Ada Lovelace was the daughter of the poet Lord Byron and mathematician Annabella Milbanke.
“Intelligent she might have been, but she was also manipulative and aggressive, a drug addict, a gambler and an adulteress,” said mathematician Hannah Fry, who made a BBC documentary about her.
Hannah Fry has written an essay about Lovelace and what she discovered while making the documentary that can be found here,
I need to make a confession. Before starting this film, intrigued as I was by her story, I questioned if Ada Lovelace truly deserved the pedestal on which she has been placed by modern scientists and mathematicians. I wondered if she is really worthy of standing as a symbol for our subject. One thing is in little doubt. Ada’s story is a captivating tale.
The 19th century amateur mathematician, best known for her detailed notes on Charles Babbage’s Analytical Engine, is often held up as a symbol for women in science. Never more so now than in the 200th anniversary of her birth.
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Alongside the character flaws, there are also some who still debate the validity of Ada’s accomplishments.
The machine which Ada prophesised could create music was Babbage’s invention after all – surely he must have known it’s potential?
Although she certainly published the world’s first computer programme, can we be sure she was its author. In any case, the machine was never built. Her work ultimately had no tangible impact on the world whatsoever.
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For me, Doron [Doron Swade – an expert in the history of computing and, while a curator at the Science Museum in London, the man responsible for bringing Babbage’s Difference Engine to life] also put an end to the discussion of Lovelace’s contribution. Her notes and letters to Babbage make it clear that Ada understood the potential of computers in a way that he never did, and that nobody ever had. In Doron’s words:
“This is not a suggestive hint. This is not a backwards projection. This is Lovelace thumping the table saying this is what is significant about this machine “
Calculated conclusion
Her foresight was so extraordinary that it would take another hundred years and Alan Turing to recognise the significance of her work. But it was an achievement that was probably as much a product of her artistic heritage as her scientific training.
Fry experienced a revelation while working on the documentary,
I think I’d become so used to expecting my role models to be unnaturally perfect people and elevating them to unachievably high levels that I couldn’t see why Ada deserved to be there.
But in making this programme I’ve realised that I was thinking about things in the wrong way.
Ada was very, very far from perfect, but perfection is not a pre-requisite to accomplishing something impressive. Our science role models shouldn’t always be there to celebrate the unachievable.
We should also be normalising the mundane and the ordinary – embracing our flaws and our failures. And that’s exactly why she is the ideal inspirational figure.
Sadly, the sentiment about acceptance is undercut by the essay’s sidebar, Who was Ada Lovelace?,
She was a contradiction: self-centred and obstinate, yet lacking in confidence; charismatic and enchanting, yet forceful and manipulative.
Ultimately, Ada was probably quite a difficult person to like. [emphasis mine]
It’s 200 years later and women still have to be concerned with likability. Even Jennifer Lawrence (Hunger Games) worries about it as she notes in the Oct. 13, 2015 issue (no. 3) of Lenny (Lena Dunham’s [Girls tv series] newsletter) h/t Laineygossip,
… if I’m honest with myself, I would be lying if I didn’t say there was an element of wanting to be liked that influenced my decision to close the deal without a real fight. I didn’t want to seem “difficult” or “spoiled.” At the time, that seemed like a fine idea, until I saw the payroll on the Internet and realized every man I was working with definitely didn’t worry about being “difficult” or “spoiled.” This could be a young-person thing. It could be a personality thing. I’m sure it’s both. But this is an element of my personality that I’ve been working against for years, and based on the statistics, I don’t think I’m the only woman with this issue. Are we socially conditioned to behave this way? We’ve only been able to vote for what, 90 years? I’m seriously asking — my phone is on the counter and I’m on the couch, so a calculator is obviously out of the question. Could there still be a lingering habit of trying to express our opinions in a certain way that doesn’t “offend” or “scare” men?
She acknowledges that she’s well paid by any standard but she’s pointing out that her male colleagues don’t have to worry about whether or not they’ll be liked or viewed as difficult when they negotiate or even when they express an opinion,
A few weeks ago at work, I spoke my mind and gave my opinion in a clear and no-bullshit way; no aggression, just blunt. The man I was working with (actually, he was working for me) said, “Whoa! We’re all on the same team here!” As if I was yelling at him. I was so shocked because nothing that I said was personal, offensive, or, to be honest, wrong. All I hear and see all day are men speaking their opinions, and I give mine in the same exact manner, and you would have thought I had said something offensive.
… Jeremy Renner, Christian Bale, and Bradley Cooper all fought and succeeded in negotiating powerful deals for themselves. If anything, I’m sure they were commended for being fierce and tactical, while I was busy worrying about coming across as a brat and not getting my fair share.
Bringing it back to the topic of science, how often does a male scientist get described as “a difficult person to like.” It would take more than drug addiction, adultery, stating an opinion in a forthright fashion, and/or being manipulative for a man to earn that label.
Getting back to Ada and the celebrations, there’s an Oct. 12, 2015 preview of her Science Museum exhibit by Nicola Davis for the Guardian (Note: A link has been removed),
In the bowels of London’s Science Museum, Dr Tilly Blyth gingerly opens an envelope. Inside is a lock of long, dark hair tied with a green ribbon. It’s a curiously poignant moment. The lively, intelligent woman to whom it belonged died young, but her mathematical work with computer pioneer Charles Babbage has seen her become a paragon for women in science and technology. Gazing down at the tresses, the centuries seem to shrink away. Ladies and gentlemen, Ada Lovelace is in the room.
The exhibit opens today, October 13, 2015 and runs until March 31, 2016. You can find out more here.
Here’s my favourite Ada Lovelace image; it’s being used in the exhibit’s promotional materials,
Courtesy Science Museum (London, UK)
You can find out more about Ada Lovelace Day 2015 events such as the annual flagship event on the findingada.com website,
The academic paper for this latest research from Delft University of Technology (TU Delft, Netherlands), uses the term ‘bacterial sculptures,’ an intriguing idea that seems to have influenced the artistic illustration accompanying the research announcement.
Artistic rendering live E.coli bacteria that have been shaped into a rectangle, triangle, circle, and square (from front to back). Colors indicate the density of the Min proteins that represent a snapshot in time (based on actual data), as these proteins oscillate back and forth within the bacterium, to determine the mid plane of the cell for cellular division. Image credit: ‘Image Cees Dekker lab TU Delft / Tremani’
A June 22, 2015 news item on Nanowerk provides more insight into the research (Note: A link has been removed),
The E.coli bacterium, a very common resident of people’s intestines, is shaped as a tiny rod about 3 micrometers long. For the first time, scientists from the Kavli Institute of Nanoscience at Delft University have found a way to use nanotechnology to grow living E.coli bacteria into very different shapes: squares, triangles, circles, and even as letters spelling out ‘TU Delft’. They also managed to grow supersized E.coli with a volume thirty times larger than normal. These living oddly-shaped bacteria allow studies of the internal distribution of proteins and DNA in entirely new ways.
In this week’s Nature Nanotechnology (“Symmetry and scale orient Min protein patterns in shaped bacterial sculptures”), the scientists describe how these custom-designed bacteria still manage to perfectly locate ‘the middle of themselves’ for their cell division. They are found to do so using proteins that sense the cell shape, based on a mathematical principle proposed by computer pioneer Alan Turing in 1953.
“If cells can’t divide properly, biological life wouldn’t be possible. Cells need to distribute their cell volume and genetic materials equally into their daughter cells to proliferate.”, says prof. Cees Dekker, “It is fascinating that even a unicellular organism knows how to divide very precisely. The distribution of certain proteins in the cell is key to regulating this, but how exactly do those proteins get that done?”
Turing
As the work of the Delft scientist exemplifies, the key here is a process discovered by the famous Alan Turing in 1953. Although Turing is mostly known for his role in deciphering the Enigma coding machine and the Turing Test, the impact of his ‘reaction-diffusion theory’ on biology might be even more spectacular. He predicted how patterns in space and time emerge as the result of only two molecular interactions – explaining for instance how a zebra gets its stripes, or how an embryo hand develops five fingers.
MinD and MinE
Such a Turing process also acts with proteins within a single cell, to regulate cell division. An E.coli cell uses two types of proteins, known as MinD and MinE, that bind and unbind again and again at the inner surface of the bacterium, thus oscillating back and forth from pole to pole within the bacterium every minute. “This results in a low average concentration of the protein in the middle and high concentrations at the ends, which drives the division machinery to the cell center”, says PhD-student Fabai Wu, who ran the experiments. “As our experiments show, the Turing patterns allow the bacterium to determine its symmetry axes and its center. This applies to many bacterial cell shapes that we custom-designed, such as squares, triangles and rectangles of many sizes. For fun, we even made ‘TUDelft’ and ‘TURING’ letters. Using computer simulations, we uncovered that the shape-sensing abilities are caused by simple Turing-type interactions between the proteins.”
Actual data for live E.coli bacteria that have been shaped into the letters TUDELFT. The red color shows the cytosol contents of the cell, while the green color shows the density of the Min proteins, representing a snapshot in time, as these proteins oscillate back and forth within the bacterium to determine the mid plane of the cell for cellular division. The letters are about 5 micron high. Image credit: ‘Fabai Wu, Cees Dekker lab at TU Delft’
Spatial control for building synthetic cells
“Discovering this process is not only vital for our understanding of bacterial cell division – which is important in developing new strategies for antibiotics. But the approach will likely also be fruitful to figuring out how cells distribute other vital systems within a cell, such as chromosomes”, says Cees Dekker. “The ultimate goal in our research is to be able to completely build a living cell from artificial components, as that is the only way to really understand how life works. Understanding cell division – both the process that actually pinches off the cell into two daughters and the part that spatially regulates that machinery – is a major part of that.”
This paper is behind a paywall but there does seem to be another link (in the excerpt below) which gives you a free preview via ReadCube Access (according to the TU Delft press release),
The DOI for this paper will be 10.1038/nnano.2015.126. Once the paper is published electronically, the DOI can be used to retrieve the abstract and full text by adding it to the following url: http://dx.doi.org/
In honour of International Women’s Day 2015, here are four items about women and science. The first features Canada’s Perimeter Institute (PI) and a tribute to pioneering women in physics, from a Feb. 26, 2015 PI news release,
They discovered pulsars, found the first evidence of dark matter, pioneered mathematics, radioactivity, nuclear fission, elasticity, and computer programming, and have even stopped light.
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It’s a fascinating group of women and these four provide a taste only.
The second item about women in science is also from the Perimeter Institute, which is hosting an ‘Inspiring Future Women in Science’ conference on Friday, May 6, 2015. From the PI program page,
Are you interested in turning your love of science into a career? Perimeter Institute is inviting female high school students to participate in an inspirational half day conference on Friday March 6, 2015. The goal is to bring together like minded young women with a strong interest in science and expose them to the rewards, challenges and possibilities of a career in science.
kEYNOTE ADDRESSES
Rima Brek – Rima is a Ubisoft veteran of 16 years and a founding team member of the Toronto studio. There, she was responsible for kick-starting the technology team and helping ship the critically-acclaimed Tom Clancy’s Splinter Cell Blacklist. She is a sought-after advisor whose guidance and leadership have directly helped Ubisoft Toronto grow to over 300 game developers in just five years.
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Dianna Cowern – Dianna is a science communicator and educator. She received her degree in physics from MIT and completed a post-baccalaureate fellowship in astrophysics at Harvard. She then worked on mobile applications as a software engineer at General Electric before beginning a position at the University of California, San Diego as a physics outreach coordinator. She is the primary content creator for her educational YouTube channel, Physics Girl.
Roslyn Bern – As president of the Leacross Foundation, Roslyn Bern has been creating opportunities for women and girls throughout Canada. She has worked on initiatives for over 20 years, as an educator, a business woman, and as a philanthropist. She has focused on developing scholarships and bursaries for girls in under-represented career fields. She has been instrumental on sending teenage girls to the Arctic and Antarctic with Students on Ice, and created a partnership with colleges and corporations to certify STEM women in Electrical engineering. …
By the time this piece is posted it will be too late to attend this year’s event but interested parties could plan for next year in Waterloo, Ontario, Canada.
The third item concerns an initiative from the Public Radio Exchange, PRX. Called Transistor; a STEM [science, technology, engineering, and mathematics] audio project. From the series page,
Transistor is a transformative STEM podcast, taking the electricity of a story and channeling it to listeners. Three scientist hosts — a biologist, an astrophysicist, and a neuroscientist — report on conundrums, curiosities, and current events in and beyond their fields. Sprinkled among their episodes are the winners of the STEM Story Project, a competition we held for unique science radio.
Much as the transistor radio was a new technical leap, this Transistor features new women voices and sounds from new science producers.
PRX presents Transistor, applying our storytelling and podcast experience to science. The Sloan Foundation powers Transistor with funding and support. And listeners complete the circuit.
PRX is thrilled to announce the launch of a new weekly podcast series Transistor (official press release). Three scientist hosts — a biologist, an astrophysicist, and a neuroscientist — report on conundrums, curiosities, and current events in and beyond their fields. Sprinkled among their episodes are the winners of the PRX STEM Story Project, a competition we held for unique science radio.
Just as the transistor radio was a new technical leap, this Transistor features new women voices and their science perspectives. We’ve launched with four episodes from our three scientist hosts:
Dr. Michelle Thaller, an astrophysicist at NASA’s Goddard Space Flight Center, who studies binary stars and the life cycles of the stars.
We Are Stardust: We’re closer than ever before to discovering if we’re not alone in the universe. Astrophysicist Michelle Thaller visits the NASA lab that discovered that comets contain some of the very same chemical elements that we contain. Then, Michelle talks to a Vatican planetary scientist about how science and religion can meet on the topic of life beyond Earth.
Dr. Christina Agapakis, a biologist and writer based in Los Angeles. Her research focuses on the intersection of microbiology and design, exploring the symbiosis among microbes and biology, technology, and culture.
Food, Meet Fungus: The microbiome — the trillions of bacteria, fungi, and viruses that live in and on our body — is hot right now. We explore what we do know in the face of so much hope and hype, starting with food.
Dr. Wendy Suzuki, a Professor of Neural Science and Psychology in the Center for Neural Science at New York University, whose research focuses on understanding how our brains form and retain new long-term memories and the effects of aerobic exercise on memory. Her book Healthy Brain, Happy Life will be published by Harper Collins in the Spring of 2015.
Totally Cerebral: Untangling the Mystery of Memory: Neuroscientist Wendy Suzuki introduces us to scientists who have uncovered some of the deepest secrets about our brains. She begins by talking with experimental psychologist Brenda Milner [interviewed in her office at McGill University, Montréal, Quebéc], who in the 1950s, completely changed our understanding of the parts of the brain important for forming new long-term memories.
Totally Cerebral: The Man Without a Memory: Imagine never being able to form a new long term memory after the age of 27. Welcome to the life of the famous amnesic patient “HM”. Neuroscientist Suzanne Corkin studied HM for almost half a century, and gives us a glimpse of what daily life was like for him, and his tremendous contribution to our understanding of how our memories work.
Subscribe to the show through iTunes or RSS, or you can stream it on PRX.org.
I listened to all four of the introductory programs which ranged in running time from about 16 mins. to 37 mins. All three hosts are obviously excited about sharing their science stories and I look forward to hearing more from them.
Science Goes to the Movies is a new program produced by the City University of New York and sponsored by the Alfred P. Sloan Foundation. … The hosts are Faith Salie, a journalist and host you might have heard before as a panelist on Wait Wait…Don’t Tell Me, and Dr. Heather Berlin, a neuroscientist whose research focuses on brain-body relationships and psychological disorders. (In what makes for a small world, Berlin is married to Canadian rap troubadour Baba Brinkman.) …
Hallucinations and black holes vie for the 2015 Oscar. Co-hosts Faith Salie and Dr. Heather Berlin are joined by AMNH astrophysicist Dr. Emily Rice for a look at the science in three of the top films of the year, Birdman, The Theory of Everything, and Interstellar.
Episode 102 featuring Into the Woods and the Imitation Game will première on March 20, 2015,
Science Goes to the Movies looks at The Imitation Game and Into the Woods. With special guest cryptologist Rosario Gennaro, we discuss pattern recognition in the work of both Alan Turing and Stephen Sondheim.
Science Goes to the Movies is made possible by generous support from the Alfred P. Sloan Foundation.
Kudos to the Alfred P. Sloan foundation for funding two exciting ventures: Transistors and Science Goes to the Movies.
Getting back to where I started: Happy International Women’s Day 2015!
A Feb. 6, 2015 news item on Azonano profiles some research from the Polish Academy of Sciences’ Institute of Physical Chemistry (IPC PAS),
In the world of single atoms and molecules governed by chaotic fluctuations, is the spontaneous formation of Turing patterns possible – the same ones that are responsible for the irregular yet periodic shapes of the stripes on zebras’ bodies? A Polish-Danish team of physicists has for the first time demonstrated that such a process can not only occur, but can also be used for potentially very interesting applications.
Everyone is familiar with a zebra’s stripes, but not everyone knows that these are the manifestations of chemical reactions taking place according to a process first described by the famous British mathematician Alan Turing, the creator of the basics of today’s computer science. Turing patterns, most commonly displayed in chemistry as periodic changes in the concentration of chemical substances, have hitherto only been observed in dimensions of microns or larger. It seemed that on a smaller scale – at the nanoscale, where random fluctuations rule the movement of single atoms and molecules – these patterns do not have the right to form spontaneously.
“So far, no-one has even studied the possibility of the formation of Turing patterns by single atoms or molecules. However, our results show that Turing nanostructures may exist. And since this is the case, we will be able to find very specific applications for them in nanotechnology and materials science,” says Dr. Bogdan Nowakowski from the Institute of Physical Chemistry of the Polish Academy of Sciences (IPC PAS) in Warsaw, one of the physicists in the Polish-Danish team that has recently conducted computer simulations and theoretical analyses on Turing nanostructures.
Turing patterns occur in dynamic systems far from a state of equilibrium. Under the appropriate conditions there may then be a feedback mechanism: chemical reactions taking place may influence the concentration of their own components, which in turn may change the course of the reaction itself. The process leads to the formation of periodic, but not necessarily monotonously regular patterns. In nature, these patterns play an important role, particularly in the formation of young organisms (morphogenesis). For example, in the initial phases of the development of vertebrate embryos, this is how periodic segments, somites, are formed in the dorsal mesoderm, which are later converted into, among others, vertebrae, components of the spine.
“In our studies we considered very simple reactions of two model substances with different rates of diffusion. Computer simulations carried out using molecular dynamics, in collaboration with Dr. Jesper Hansen from the Danish University of Roskilde, gave rise to a very interesting picture,” says Dr. Piotr Dziekan (IPC PAS).
Clear and permanent patterns formed spontaneously in the simulated systems (of nanometer dimensions) – periodic changes in the density of molecules, which remained stable despite the destructive influence of fluctuations. It turned out that one cycle of concentration changes within the Turing pattern could appear on a length of just 20 molecules.
For Turing nanostructures to be formed, chemical reactions satisfying certain conditions have to take place between the chemical substances. This requirement severely reduces the number of compounds that can participate in the process and, consequently, severely limits the potential applications. However, the simulations carried out by the Polish-Danish team suggest that Turing nanostructures can quite easily be transferred to other compounds, not participating directly in the main reaction.
“Turing nanostructures can only arise with carefully selected chemical substances. Fortunately, the pattern formed by them can be ‘imprinted’ in the concentration of other chemical compounds. For the pattern to be copied, these compounds must fulfill only two simple conditions: they must bind to one of the reactants of the main reaction and diffuse slowly,” explains Dr. Dziekan.
This work is theoretical as the final paragraph of the press release intimates,
The possibility of forming Turing patterns on nanometer distances opens the door to interesting applications, particularly in the field of surface modification of materials. By skillfully selecting the chemical composition of the reagents and the conditions in which the reaction occurs, it could be possible to form Turing patterns in two dimensions (on the same surface of the material), or three (also in the space adjacent to the surface). The formed patterns could then be fixed, e.g. by photopolymerisation, thereby obtaining a permanent, stable, extended surface with a complex, periodic structure.
Here’s a link to and a citation for the paper,
Nanoscale Turing structures by Piotr Dziekan. J. S. Hansen, and Bogdan Nowakowski. J. Chem. Phys. 141, 124106 (2014); http://dx.doi.org/10.1063/1.4895907
![While the metaphor that ideas appear “like light bulbs” is popular and appealing, new research shows that discovery metaphors influence our understanding of the scientific process and perceptions of the ability of inventors based on their gender. [downloaded from http://www.spsp.org/news-center/press-release/metaphors-bias-perception]](http://www.frogheart.ca/wp-content/uploads/2016/10/Metaphors_LightBulb.jpg)
