Tag Archives: Douglas Coupland

Should AI algorithms get patents for their inventions and is anyone talking about copyright for texts written by AI algorithms?

A couple of Australian academics have written a comment for the journal Nature, which bears the intriguing subtitle: “The patent system assumes that inventors are human. Inventions devised by machines require their own intellectual property law and an international treaty.” (For the curious, I’ve linked to a few of my previous posts touching on intellectual property [IP], specifically the patent’s fraternal twin, copyright at the end of this piece.)

Before linking to the comment, here’s the May 27, 2022 University of New South Wales (UNCSW) press release (also on EurekAlert but published May 30, 2022) which provides an overview of their thinking on the subject, Note: Links have been removed,

It’s not surprising these days to see new inventions that either incorporate or have benefitted from artificial intelligence (AI) in some way, but what about inventions dreamt up by AI – do we award a patent to a machine?

This is the quandary facing lawmakers around the world with a live test case in the works that its supporters say is the first true example of an AI system named as the sole inventor.

In commentary published in the journal Nature, two leading academics from UNSW Sydney examine the implications of patents being awarded to an AI entity.

Intellectual Property (IP) law specialist Associate Professor Alexandra George and AI expert, Laureate Fellow and Scientia Professor Toby Walsh argue that patent law as it stands is inadequate to deal with such cases and requires legislators to amend laws around IP and patents – laws that have been operating under the same assumptions for hundreds of years.

The case in question revolves around a machine called DABUS (Device for the Autonomous Bootstrapping of Unified Sentience) created by Dr Stephen Thaler, who is president and chief executive of US-based AI firm Imagination Engines. Dr Thaler has named DABUS as the inventor of two products – a food container with a fractal surface that helps with insulation and stacking, and a flashing light for attracting attention in emergencies.

For a short time in Australia, DABUS looked like it might be recognised as the inventor because, in late July 2021, a trial judge accepted Dr Thaler’s appeal against IP Australia’s rejection of the patent application five months earlier. But after the Commissioner of Patents appealed the decision to the Full Court of the Federal Court of Australia, the five-judge panel upheld the appeal, agreeing with the Commissioner that an AI system couldn’t be named the inventor.

A/Prof. George says the attempt to have DABUS awarded a patent for the two inventions instantly creates challenges for existing laws which has only ever considered humans or entities comprised of humans as inventors and patent-holders.

“Even if we do accept that an AI system is the true inventor, the first big problem is ownership. How do you work out who the owner is? An owner needs to be a legal person, and an AI is not recognised as a legal person,” she says.

Ownership is crucial to IP law. Without it there would be little incentive for others to invest in the new inventions to make them a reality.

“Another problem with ownership when it comes to AI-conceived inventions, is even if you could transfer ownership from the AI inventor to a person: is it the original software writer of the AI? Is it a person who has bought the AI and trained it for their own purposes? Or is it the people whose copyrighted material has been fed into the AI to give it all that information?” asks A/Prof. George.

For obvious reasons

Prof. Walsh says what makes AI systems so different to humans is their capacity to learn and store so much more information than an expert ever could. One of the requirements of inventions and patents is that the product or idea is novel, not obvious and is useful.

“There are certain assumptions built into the law that an invention should not be obvious to a knowledgeable person in the field,” Prof. Walsh says.

“Well, what might be obvious to an AI won’t be obvious to a human because AI might have ingested all the human knowledge on this topic, way more than a human could, so the nature of what is obvious changes.”

Prof. Walsh says this isn’t the first time that AI has been instrumental in coming up with new inventions. In the area of drug development, a new antibiotic was created in 2019 – Halicin – that used deep learning to find a chemical compound that was effective against drug-resistant strains of bacteria.

“Halicin was originally meant to treat diabetes, but its effectiveness as an antibiotic was only discovered by AI that was directed to examine a vast catalogue of drugs that could be repurposed as antibiotics. So there’s a mixture of human and machine coming into this discovery.”

Prof. Walsh says in the case of DABUS, it’s not entirely clear whether the system is truly responsible for the inventions.

“There’s lots of involvement of Dr Thaler in these inventions, first in setting up the problem, then guiding the search for the solution to the problem, and then interpreting the result,” Prof. Walsh says.

“But it’s certainly the case that without the system, you wouldn’t have come up with the inventions.”

Change the laws

Either way, both authors argue that governing bodies around the world will need to modernise the legal structures that determine whether or not AI systems can be awarded IP protection. They recommend the introduction of a new ‘sui generis’ form of IP law – which they’ve dubbed ‘AI-IP’ – that would be specifically tailored to the circumstances of AI-generated inventiveness. This, they argue, would be more effective than trying to retrofit and shoehorn AI-inventiveness into existing patent laws.

Looking forward, after examining the legal questions around AI and patent law, the authors are currently working on answering the technical question of how AI is going to be inventing in the future.

Dr Thaler has sought ‘special leave to appeal’ the case concerning DABUS to the High Court of Australia. It remains to be seen whether the High Court will agree to hear it. Meanwhile, the case continues to be fought in multiple other jurisdictions around the world.

Here’s a link to and a citation for the paper,

Artificial intelligence is breaking patent law by Alexandra George & Toby Walsh. Nature (Nature) COMMENT ISSN 1476-4687 (online) 24 May 2022 ISSN 0028-0836 (print) Vol 605 26 May 2022 pp. 616-18 DOI: 10.1038/d41586-022-01391-x

This paper appears to be open access.

The Journey

DABIUS has gotten a patent in one jurisdiction, from an August 8, 2021 article on brandedequity.com,

The patent application listing DABUS as the inventor was filed in patent offices around the world, including the US, Europe, Australia, and South Afica. But only South Africa granted the patent (Australia followed suit a few days later after a court judgment gave the go-ahard [and rejected it several months later]).

Natural person?

This September 27, 2021 article by Miguel Bibe for Inventa covers some of the same ground adding some some discussion of the ‘natural person’ problem,

The patent is for “a food container based on fractal geometry”, and was accepted by the CIPC [Companies and Intellectual Property Commission] on June 24, 2021. The notice of issuance was published in the July 2021 “Patent Journal”.  

South Africa does not have a substantive patent examination system and, instead, requires applicants to merely complete a filing for their inventions. This means that South Africa patent laws do not provide a definition for “inventor” and the office only proceeds with a formal examination in order to confirm if the paperwork was filled correctly.

… according to a press release issued by the University of Surrey: “While patent law in many jurisdictions is very specific in how it defines an inventor, the DABUS team is arguing that the status quo is not fit for purpose in the Fourth Industrial Revolution.”

On the other hand, this may not be considered as a victory for the DABUS team since several doubts and questions remain as to who should be considered the inventor of the patent. Current IP laws in many jurisdictions follow the traditional term of “inventor” as being a “natural person”, and there is no legal precedent in the world for inventions created by a machine.

August 2022 update

Mike Masnick in an August 15, 2022 posting on Techdirt provides the latest information on Stephen Thaler’s efforts to have patents and copyrights awarded to his AI entity, DABUS,

Stephen Thaler is a man on a mission. It’s not a very good mission, but it’s a mission. He created something called DABUS (Device for the Autonomous Bootstrapping of Unified Sentience) and claims that it’s creating things, for which he has tried to file for patents and copyrights around the globe, with his mission being to have DABUS named as the inventor or author. This is dumb for many reasons. The purpose of copyright and patents are to incentivize the creation of these things, by providing to the inventor or author a limited time monopoly, allowing them to, in theory, use that monopoly to make some money, thereby making the entire inventing/authoring process worthwhile. An AI doesn’t need such an incentive. And this is why patents and copyright only are given to persons and not animals or AI.

… Thaler’s somewhat quixotic quest continues to fail. The EU Patent Office rejected his application. The Australian patent office similarly rejected his request. In that case, a court sided with Thaler after he sued the Australian patent office, and said that his AI could be named as an inventor, but thankfully an appeals court set aside that ruling a few months ago. In the US, Thaler/DABUS keeps on losing as well. Last fall, he lost in court as he tried to overturn the USPTO ruling, and then earlier this year, the US Copyright Office also rejected his copyright attempt (something it has done a few times before). In June, he sued the Copyright Office over this, which seems like a long shot.

And now, he’s also lost his appeal of the ruling in the patent case. CAFC, the Court of Appeals for the Federal Circuit — the appeals court that handles all patent appeals — has rejected Thaler’s request just like basically every other patent and copyright office, and nearly all courts.

If you have the time, the August 15, 2022 posting is an interesting read.

Consciousness and ethical AI

Just to make things more fraught, an engineer at Google has claimed that one of their AI chatbots has consciousness. From a June 16, 2022 article (in Canada’s National Post [previewed on epaper]) by Patrick McGee,

Google has ignited a social media firestorm on the the nature of consciousness after placing an engineer on paid leave with his belief that the tech group’s chatbot has become “sentient.”

Blake Lemoine, a senior software engineer in Google’s Responsible AI unit, did not receive much attention when he wrote a Medium post saying he “may be fired soon for doing AI ethics work.”

But a Saturday [June 11, 2022] profile in the Washington Post characterized Lemoine as “the Google engineer who thinks “the company’s AI has come to life.”

This is not the first time that Google has run into a problem with ethics and AI. Famously, Timnit Gebru who co-led (with Margaret Mitchell) Google’s ethics and AI unit departed in 2020. Gebru said (and maintains to this day) she was fired. They said she was ?, they never did make a final statement although after an investigation Gebru did receive an apology. You *can* read more about Gebru and the issues she brought to light in her Wikipedia entry. Coincidentally (or not), Margaret Mitchell was terminated/fired in February 2021 from Google after criticizing the company for Gebru’s ‘firing’. See a February 19, 2021 article by Megan Rose Dickey for TechCrunch for details about what the company has admitted is a firing or Margaret Mitchell’s termination from the company.

Getting back intellectual property and AI.

What about copyright?

There are no mentions of copyright in the earliest material I have here about the ‘creative’ arts and artificial intelligence is this, “Writing and AI or is a robot writing this blog?” posted July 16, 2014. More recently, there’s “Beer and wine reviews, the American Chemical Society’s (ACS) AI editors, and the Turing Test” posted May 20, 2022. The type of writing featured is not literary or typically considered creative writing.

On the more creative front, there’s “True love with AI (artificial intelligence): The Nature of Things explores emotional and creative AI (long read)” posted on December 3, 2021. The literary/creative portion of the post can be found under the ‘AI and creativity’ subhead approximately 30% of the way down and where I mention Douglas Coupland. Again, there’s no mention of copyright.

It’s with the visual arts that copyright gets mentioned. The first one I can find here is “Robot artists—should they get copyright protection” posted on July 10, 2017.

Fun fact: Andres Guadamuz who was mentioned in my posting took to his own blog where he gave my blog a shout out while implying that I wasn’t thoughtful. The gist of his August 8, 2017 posting was that he was misunderstood by many people, which led to the title for his post, “Should academics try to engage the public?” Thankfully, he soldiers on trying to educate us with his TechnoLama blog.

Lastly, there’s this August 16, 2019 posting “AI (artificial intelligence) artist got a show at a New York City art gallery” where you can scroll down to the ‘What about intellectual property?’ subhead about 80% of the way.

You look like a thing …

i am recommending a book for anyone who’d like to learn a little more about how artificial intelligence (AI) works, “You look like a thing and I love you; How Artificial Intelligence Works and Why It’s Making the World a Weirder Place” by Janelle Shane (2019).

It does not require an understanding of programming/coding/algorithms/etc.; Shane makes the subject as accessible as possible and gives you insight into why the term ‘artificial stupidity’ is more applicable than you might think. You can find Shane’s website here and you can find her 10 minute TED talk here.

*’can’ added to sentence on May 12, 2023.

True love with AI (artificial intelligence): The Nature of Things explores emotional and creative AI (long read)

The Canadian Broadcasting Corporation’s (CBC) science television series,The Nature of Things, which has been broadcast since November 1960, explored the world of emotional, empathic and creative artificial intelligence (AI) in a Friday, November 19, 2021 telecast titled, The Machine That Feels,

The Machine That Feels explores how artificial intelligence (AI) is catching up to us in ways once thought to be uniquely human: empathy, emotional intelligence and creativity.

As AI moves closer to replicating humans, it has the potential to reshape every aspect of our world – but most of us are unaware of what looms on the horizon.

Scientists see AI technology as an opportunity to address inequities and make a better, more connected world. But it also has the capacity to do the opposite: to stoke division and inequality and disconnect us from fellow humans. The Machine That Feels, from The Nature of Things, shows viewers what they need to know about a field that is advancing at a dizzying pace, often away from the public eye.

What does it mean when AI makes art? Can AI interpret and understand human emotions? How is it possible that AI creates sophisticated neural networks that mimic the human brain? The Machine That Feels investigates these questions, and more.

In Vienna, composer Walter Werzowa has — with the help of AI — completed Beethoven’s previously unfinished 10th symphony. By feeding data about Beethoven, his music, his style and the original scribbles on the 10th symphony into an algorithm, AI has created an entirely new piece of art.

In Atlanta, Dr. Ayanna Howard and her robotics lab at Georgia Tech are teaching robots how to interpret human emotions. Where others see problems, Howard sees opportunity: how AI can help fill gaps in education and health care systems. She believes we need a fundamental shift in how we perceive robots: let’s get humans and robots to work together to help others.

At Tufts University in Boston, a new type of biological robot has been created: the xenobot. The size of a grain of sand, xenobots are grown from frog heart and skin cells, and combined with the “mind” of a computer. Programmed with a specific task, they can move together to complete it. In the future, they could be used for environmental cleanup, digesting microplastics and targeted drug delivery (like releasing chemotherapy compounds directly into tumours).

The film includes interviews with global leaders, commentators and innovators from the AI field, including Geoff Hinton, Yoshua Bengio, Ray Kurzweil and Douglas Coupland, who highlight some of the innovative and cutting-edge AI technologies that are changing our world.

The Machine That Feels focuses on one central question: in the flourishing age of artificial intelligence, what does it mean to be human?

I’ll get back to that last bit, “… what does it mean to be human?” later.

There’s a lot to appreciate in this 44 min. programme. As you’d expect, there was a significant chunk of time devoted to research being done in the US but Poland and Japan also featured and Canadian content was substantive. A number of tricky topics were covered and transitions from one topic to the next were smooth.

In the end credits, I counted over 40 source materials from Getty Images, Google Canada, Gatebox, amongst others. It would have been interesting to find out which segments were produced by CBC.

David Suzuki’s (programme host) script was well written and his narration was enjoyable, engaging, and non-intrusive. That last quality is not always true of CBC hosts who can fall into the trap of overdramatizing the text.

Drilling down

I have followed artificial intelligence stories in a passive way (i.e., I don’t seek them out) for many years. Even so, there was a lot of material in the programme that was new to me.

For example, there was this love story (from the ‘I love her and see her as a real woman.’ Meet a man who ‘married’ an artificial intelligence hologram webpage on the CBC),

In the The Machine That Feels, a documentary from The Nature of Things, we meet Kondo Akihiko, a Tokyo resident who “married” a hologram of virtual pop singer Hatsune Miku using a certificate issued by Gatebox (the marriage isn’t recognized by the state, and Gatebox acknowledges the union goes “beyond dimensions”).

I found Akihiko to be quite moving when he described his relationship, which is not unique. It seems some 4,000 men have ‘wed’ their digital companions, you can read about that and more on the ‘I love her and see her as a real woman.’ Meet a man who ‘married’ an artificial intelligence hologram webpage.

What does it mean to be human?

Overall, this Nature of Things episode embraces certainty, which means the question of what it means to human is referenced rather than seriously discussed. An unanswerable philosophical question, the programme is ill-equipped to address it, especially since none of the commentators are philosophers or seem inclined to philosophize.

The programme presents AI as a juggernaut. Briefly mentioned is the notion that we need to make some decisions about how our juggernaut is developed and utilized. No one discusses how we go about making changes to systems that are already making critical decisions for us. (For more about AI and decision-making, see my February 28, 2017 posting and scroll down to the ‘Algorithms and big data’ subhead for Cathy O’Neil’s description of how important decisions that affect us are being made by AI systems. She is the author of the 2016 book, ‘Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy’; still a timely read.)

In fact, the programme’s tone is mostly one of breathless excitement. A few misgivings are expressed, e.g,, one woman who has an artificial ‘texting friend’ (Replika; a chatbot app) noted that it can ‘get into your head’ when she had a chat where her ‘friend’ told her that all of a woman’s worth is based on her body; she pushed back but intimated that someone more vulnerable could find that messaging difficult to deal with.

The sequence featuring Akihiko and his hologram ‘wife’ is followed by one suggesting that people might become more isolated and emotionally stunted as they interact with artificial friends. It should be noted, Akihiko’s wife is described as ‘perfect’. I gather perfection means that you are always understanding and have no needs of your own. She also seems to be about 18″ high.

Akihiko has obviously been asked about his ‘wife’ before as his answers are ready. They boil down to “there are many types of relationships” and there’s nothing wrong with that. It’s an intriguing thought which is not explored.

Also unexplored, these relationships could be said to resemble slavery. After all, you pay for these friends over which you have control. But perhaps that’s alright since AI friends don’t have consciousness. Or do they? In addition to not being able to answer the question, “what is it to be human?” we still can’t answer the question, “what is consciousness?”

AI and creativity

The Nature of Things team works fast. ‘Beethoven X – The AI Project’ had its first performance on October 9, 2021. (See my October 1, 2021 post ‘Finishing Beethoven’s unfinished 10th Symphony’ for more information from Ahmed Elgammal’s (Director of the Art & AI Lab at Rutgers University) technical perspective on the project.

Briefly, Beethoven died before completing his 10th symphony and a number of computer scientists, musicologists, AI, and musicians collaborated to finish the symphony.)

The one listener (Felix Mayer, music professor at the Technical University Munich) in the hall during a performance doesn’t consider the work to be a piece of music. He does have a point. Beethoven left some notes but this ’10th’ is at least partly mathematical guesswork. A set of probabilities where an algorithm chooses which note comes next based on probability.

There was another artist also represented in the programme. Puzzlingly, it was the still living Douglas Coupland. In my opinion, he’s better known as a visual artist than a writer (his Wikipedia entry lists him as a novelist first) but he has succeeded greatly in both fields.

What makes his inclusion in the Nature of Things ‘The Machine That Feels’ programme puzzling, is that it’s not clear how he worked with artificial intelligence in a collaborative fashion. Here’s a description of Coupland’s ‘AI’ project from a June 29, 2021 posting by Chris Henry on the Google Outreach blog (Note: Links have been removed),

… when the opportunity presented itself to explore how artificial intelligence (AI) inspires artistic expression — with the help of internationally renowned Canadian artist Douglas Coupland — the Google Research team jumped on it. This collaboration, with the support of Google Arts & Culture, culminated in a project called Slogans for the Class of 2030, which spotlights the experiences of the first generation of young people whose lives are fully intertwined with the existence of AI. 

This collaboration was brought to life by first introducing Coupland’s written work to a machine learning language model. Machine learning is a form of AI that provides computer systems the ability to automatically learn from data. In this case, Google research scientists tuned a machine learning algorithm with Coupland’s 30-year body of written work — more than a million words — so it would familiarize itself with the author’s unique style of writing. From there, curated general-public social media posts on selected topics were added to teach the algorithm how to craft short-form, topical statements. [emphases mine]

Once the algorithm was trained, the next step was to process and reassemble suggestions of text for Coupland to use as inspiration to create twenty-five Slogans for the Class of 2030. [emphasis mine]

I would comb through ‘data dumps’ where characters from one novel were speaking with those in other novels in ways that they might actually do. It felt like I was encountering a parallel universe Doug,” Coupland says. “And from these outputs, the statements you see here in this project appeared like gems. Did I write them? Yes. No. Could they have existed without me? No.” [emphases mine]

So, the algorithms crunched through Coupland’s word and social media texts to produce slogans, which Coupland then ‘combed through’ to pick out 25 slogans for the ‘Slogans For The Class of 2030’ project. (Note: In the programme, he says that he started a sentence and then the AI system completed that sentence with material gleaned from his own writings, which brings to Exquisite Corpse, a collaborative game for writers originated by the Surrealists, possibly as early as 1918.)

The ‘slogans’ project also reminds me of William S. Burroughs and the cut-up technique used in his work. From the William S. Burroughs Cut-up technique webpage on the Language is a Virus website (Thank you to Lake Rain Vajra for a very interesting website),

The cutup is a mechanical method of juxtaposition in which Burroughs literally cuts up passages of prose by himself and other writers and then pastes them back together at random. This literary version of the collage technique is also supplemented by literary use of other media. Burroughs transcribes taped cutups (several tapes spliced into each other), film cutups (montage), and mixed media experiments (results of combining tapes with television, movies, or actual events). Thus Burroughs’s use of cutups develops his juxtaposition technique to its logical conclusion as an experimental prose method, and he also makes use of all contemporary media, expanding his use of popular culture.

[Burroughs says] “All writing is in fact cut-ups. A collage of words read heard overheard. What else? Use of scissors renders the process explicit and subject to extension and variation. Clear classical prose can be composed entirely of rearranged cut-ups. Cutting and rearranging a page of written words introduces a new dimension into writing enabling the writer to turn images in cinematic variation. Images shift sense under the scissors smell images to sound sight to sound to kinesthetic. This is where Rimbaud was going with his color of vowels. And his “systematic derangement of the senses.” The place of mescaline hallucination: seeing colors tasting sounds smelling forms.

“The cut-ups can be applied to other fields than writing. Dr Neumann [emphasis mine] in his Theory of Games and Economic behavior introduces the cut-up method of random action into game and military strategy: assume that the worst has happened and act accordingly. … The cut-up method could be used to advantage in processing scientific data. [emphasis mine] How many discoveries have been made by accident? We cannot produce accidents to order. The cut-ups could add new dimension to films. Cut gambling scene in with a thousand gambling scenes all times and places. Cut back. Cut streets of the world. Cut and rearrange the word and image in films. There is no reason to accept a second-rate product when you can have the best. And the best is there for all. Poetry is for everyone . . .”

First, John von Neumann (1902 – 57) is a very important figure in the history of computing. From a February 25, 2017 John von Neumann and Modern Computer Architecture essay on the ncLab website, “… he invented the computer architecture that we use today.”

Here’s Burroughs on the history of writers and cutups (thank you to QUEDEAR for posting this clip),

You can hear Burroughs talk about the technique and how he started using it in 1959.

There is no explanation from Coupland as to how his project differs substantively from Burroughs’ cut-ups or a session of Exquisite Corpse. The use of a computer programme to crunch through data and give output doesn’t seem all that exciting. *(More about computers and chatbots at end of posting).* It’s hard to know if this was an interview situation where he wasn’t asked the question or if the editors decided against including it.

Kazuo Ishiguro?

Given that Ishiguro’s 2021 book (Klara and the Sun) is focused on an artificial friend and raises the question of ‘what does it mean to be human’, as well as the related question, ‘what is the nature of consciousness’, it would have been interesting to hear from him. He spent a fair amount of time looking into research on machine learning in preparation for his book. Maybe he was too busy?

AI and emotions

The work being done by Georgia Tech’s Dr. Ayanna Howard and her robotics lab is fascinating. They are teaching robots how to interpret human emotions. The segment which features researchers teaching and interacting with robots, Pepper and Salt, also touches on AI and bias.

Watching two African American researchers talk about the ways in which AI is unable to read emotions on ‘black’ faces as accurately as ‘white’ faces is quite compelling. It also reinforces the uneasiness you might feel after the ‘Replika’ segment where an artificial friend informs a woman that her only worth is her body.

(Interestingly, Pepper and Salt are produced by Softbank Robotics, part of Softbank, a multinational Japanese conglomerate, [see a June 28, 2021 article by Ian Carlos Campbell for The Verge] whose entire management team is male according to their About page.)

While Howard is very hopeful about the possibilities of a machine that can read emotions, she doesn’t explore (on camera) any means for pushing back against bias other than training AI by using more black faces to help them learn. Perhaps more representative management and coding teams in technology companies?

While the programme largely focused on AI as an algorithm on a computer, robots can be enabled by AI (as can be seen in the segment with Dr. Howard).

My February 14, 2019 posting features research with a completely different approach to emotions and machines,

“I’ve always felt that robots shouldn’t just be modeled after humans [emphasis mine] or be copies of humans,” he [Guy Hoffman, assistant professor at Cornell University)] said. “We have a lot of interesting relationships with other species. Robots could be thought of as one of those ‘other species,’ not trying to copy what we do but interacting with us with their own language, tapping into our own instincts.”

[from a July 16, 2018 Cornell University news release on EurekAlert]

This brings the question back to, what is consciousness?

What scientists aren’t taught

Dr. Howard notes that scientists are not taught to consider the implications of their work. Her comment reminded me of a question I was asked many years ago after a presentation, it concerned whether or not science had any morality. (I said, no.)

My reply angered an audience member (a visual artist who was working with scientists at the time) as she took it personally and started defending scientists as good people who care and have morals and values. She failed to understand that the way in which we teach science conforms to a notion that somewhere there are scientific facts which are neutral and objective. Society and its values are irrelevant in the face of the larger ‘scientific truth’ and, as a consequence, you don’t need to teach or discuss how your values or morals affect that truth or what the social implications of your work might be.

Science is practiced without much if any thought to values. By contrast, there is the medical injunction, “Do no harm,” which suggests to me that someone recognized competing values. E.g., If your important and worthwhile research is harming people, you should ‘do no harm’.

The experts, the connections, and the Canadian content

It’s been a while since I’ve seen Ray Kurzweil mentioned but he seems to be getting more attention these days. (See this November 16, 2021 posting by Jonny Thomson titled, “The Singularity: When will we all become super-humans? Are we really only a moment away from “The Singularity,” a technological epoch that will usher in a new era in human evolution?” on The Big Think for more). Note: I will have a little more about evolution later in this post.

Interestingly, Kurzweil is employed by Google these days (see his Wikipedia entry, the column to the right). So is Geoffrey Hinton, another one of the experts in the programme (see Hinton’s Wikipedia entry, the column to the right, under Institutions).

I’m not sure about Yoshu Bengio’s relationship with Google but he’s a professor at the Université de Montréal, and he’s the Scientific Director for Mila ((Quebec’s Artificial Intelligence research institute)) & IVADO (Institut de valorisation des données), Note: IVADO is not particularly relevant to what’s being discussed in this post.

As for Mila, the Canada Google blog in a November 21, 2016 posting notes a $4.5M grant to the institution,

Google invests $4.5 Million in Montreal AI Research

A new grant from Google for the Montreal Institute for Learning Algorithms (MILA) will fund seven faculty across a number of Montreal institutions and will help tackle some of the biggest challenges in machine learning and AI, including applications in the realm of systems that can understand and generate natural language. In other words, better understand a fan’s enthusiasm for Les Canadien [sic].

Google is expanding its academic support of deep learning at MILA, renewing Yoshua Bengio’s Focused Research Award and offering Focused Research Awards to MILA faculty at University of Montreal and McGill University:

Google reaffirmed their commitment to Mila in 2020 with a grant worth almost $4M (from a November 13, 2020 posting on the Mila website, Note: A link has been removed),

Google Canada announced today [November 13, 2020] that it will be renewing its funding of Mila – Quebec Artificial Intelligence Institute, with a generous pledge of nearly $4M over a three-year period. Google previously invested $4.5M US in 2016, enabling Mila to grow from 25 to 519 researchers.

In a piece written for Google’s Official Canada Blog, Yoshua Bengio, Mila Scientific Director, says that this year marked a “watershed moment for the Canadian AI community,” as the COVID-19 pandemic created unprecedented challenges that demanded rapid innovation and increased interdisciplinary collaboration between researchers in Canada and around the world.

COVID-19 has changed the world forever and many industries, from healthcare to retail, will need to adapt to thrive in our ‘new normal.’ As we look to the future and how priorities will shift, it is clear that AI is no longer an emerging technology but a useful tool that can serve to solve world problems. Google Canada recognizes not only this opportunity but the important task at hand and I’m thrilled they have reconfirmed their support of Mila with an additional $3,95 million funding grant until 22.

– Yoshua Bengio, for Google’s Official Canada Blog

Interesting, eh? Of course, Douglas Coupland is working with Google, presumably for money, and that would connect over 50% of the Canadian content (Douglas Coupland, Yoshua Bengio, and Geoffrey Hinton; Kurzweil is an American) in the programme to Google.

My hat’s off to Google’s marketing communications and public relations teams.

Anthony Morgan of Science Everywhere also provided some Canadian content. His LinkedIn profile indicates that he’s working on a PhD in molecular science, which is described this way, “My work explores the characteristics of learning environments, that support critical thinking and the relationship between critical thinking and wisdom.”

Morgan is also the founder and creative director of Science Everywhere, from his LinkedIn profile, “An events & media company supporting knowledge mobilization, community engagement, entrepreneurship and critical thinking. We build social tools for better thinking.”

There is this from his LinkedIn profile,

I develop, create and host engaging live experiences & media to foster critical thinking.

I’ve spent my 15+ years studying and working in psychology and science communication, thinking deeply about the most common individual and societal barriers to critical thinking. As an entrepreneur, I lead a team to create, develop and deploy cultural tools designed to address those barriers. As a researcher I study what we can do to reduce polarization around science.

There’s a lot more to Morgan (do look him up; he has connections to the CBC and other media outlets). The difficulty is: why was he chosen to talk about artificial intelligence and emotions and creativity when he doesn’t seem to know much about the topic? He does mention GPT-3, an AI programming language. He seems to be acting as an advocate for AI although he offers this bit of almost cautionary wisdom, “… algorithms are sets of instructions.” (You can can find out more about it in my April 27, 2021 posting. There’s also this November 26, 2021 posting [The Inherent Limitations of GPT-3] by Andrey Kurenkov, a PhD student with the Stanford [University] Vision and Learning Lab.)

Most of the cautionary commentary comes from Luke Stark, assistant professor at Western [Ontario] University’s Faculty of Information and Media Studies. He’s the one who mentions stunted emotional growth.

Before moving on, there is another set of connections through the Pan-Canadian Artificial Intelligence Strategy, a Canadian government science funding initiative announced in the 2017 federal budget. The funds allocated to the strategy are administered by the Canadian Institute for Advanced Research (CIFAR). Yoshua Bengio through Mila is associated with the strategy and CIFAR, as is Geoffrey Hinton through his position as Chief Scientific Advisor for the Vector Institute.


Getting back to “The Singularity: When will we all become super-humans? Are we really only a moment away from “The Singularity,” a technological epoch that will usher in a new era in human evolution?” Xenobots point in a disconcerting (for some of us) evolutionary direction.

I featured the work, which is being done at Tufts University in the US, in my June 21, 2021 posting, which includes an embedded video,

From a March 31, 2021 news item on ScienceDaily,

Last year, a team of biologists and computer scientists from Tufts University and the University of Vermont (UVM) created novel, tiny self-healing biological machines from frog cells called “Xenobots” that could move around, push a payload, and even exhibit collective behavior in the presence of a swarm of other Xenobots.

Get ready for Xenobots 2.0.

Also from an excerpt in the posting, the team has “created life forms that self-assemble a body from single cells, do not require muscle cells to move, and even demonstrate the capability of recordable memory.”

Memory is key to intelligence and this work introduces the notion of ‘living’ robots which leads to questioning what constitutes life. ‘The Machine That Feels’ is already grappling with far too many questions to address this development but introducing the research here might have laid the groundwork for the next episode, The New Human, telecast on November 26, 2021,

While no one can be certain what will happen, evolutionary biologists and statisticians are observing trends that could mean our future feet only have four toes (so long, pinky toe) or our faces may have new combinations of features. The new humans might be much taller than their parents or grandparents, or have darker hair and eyes.

And while evolution takes a lot of time, we might not have to wait too long for a new version of ourselves.

Technology is redesigning the way we look and function — at a much faster pace than evolution. We are merging with technology more than ever before: our bodies may now have implanted chips, smart limbs, exoskeletons and 3D-printed organs. A revolutionary gene editing technique has given us the power to take evolution into our own hands and alter our own DNA. How long will it be before we are designing our children?

As the story about the xenobots doesn’t say, we could also take the evolution of another species into our hands.

David Suzuki, where are you?

Our programme host, David Suzuki surprised me. I thought that as an environmentalist he’d point out that the huge amounts of computing power needed for artificial intelligence as mentioned in the programme, constitutes an environmental issue. I also would have expected a geneticist like Suzuki might have some concerns with regard to xenobots but perhaps that’s being saved for the next episode (The New Human) of the Nature of Things.

Artificial stupidity

Thanks to Will Knight for introducing me to the term ‘artificial stupidity’. Knight, a senior writer covers artificial intelligence for WIRED magazine. According to its Wikipedia entry,

Artificial stupidity is commonly used as a humorous opposite of the term artificial intelligence (AI), often as a derogatory reference to the inability of AI technology to adequately perform its tasks.[1] However, within the field of computer science, artificial stupidity is also used to refer to a technique of “dumbing down” computer programs in order to deliberately introduce errors in their responses.

Knight was using the term in its humorous, derogatory form.


The episode certainly got me thinking if not quite in the way producers might have hoped. ‘The Machine That Feels’ is a glossy, pretty well researched piece of infotainment.

To be blunt, I like and have no problems with infotainment but it can be seductive. I found it easier to remember the artificial friends, wife, xenobots, and symphony than the critiques and concerns.

Hopefully, ‘The Machine That Feels’ stimulates more interest in some very important topics. If you missed the telecast, you can catch the episode here.

For anyone curious about predictive policing, which was mentioned in the Ayanna Howard segment, see my November 23, 2017 posting about Vancouver’s plunge into AI and car theft.

*ETA December 6, 2021: One of the first ‘chatterbots’ was ELIZA, a computer programme developed from1964 to 1966. The most famous ELIZA script was DOCTOR, where the programme simulated a therapist. Many early users believed ELIZA understood and could respond as a human would despite Joseph Weizenbaum’s (creator of the programme) insistence otherwise.