Tag Archives: OpenAI

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

Dear friend,

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

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

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

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

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

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

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

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

Social justice

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

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

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

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

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

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

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

Eeek

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

Project Description

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

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

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

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

In recovery from an existential crisis (meditations)

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

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

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

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

Why did they do that?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

She has her own website.

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

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

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

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

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

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

AI artists first hit my radar in August 2018 when Christie’s Auction House advertised an art auction of a ‘painting’ by an algorithm (artificial intelligence). There’s more in my August 31, 2018 posting but, briefly, a French art collective, Obvious, submitted a painting, “Portrait of Edmond de Belamy,” that was created by an artificial intelligence agent to be sold for an estimated to $7000 – $10,000. They weren’t even close. According to Ian Bogost’s March 6, 2019 article for The Atlantic, the painting sold for $432,500 In October 2018.

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

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

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

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

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

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

Take the reports about the Modigliani and Picasso paintings.

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

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

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

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

Visual culture: seeing into the future

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

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

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

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

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

Learning about robots, automatons, artificial intelligence, and more

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

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

Robots, automata, and artificial intelligence

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

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

The Al-Jazari automatons

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

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

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

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

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

You can’t always get what you want

My friend,

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

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

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

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

And, from later in my posting,

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

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

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

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

US-centric

My friend,

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

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

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

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

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

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

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

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

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

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

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

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

Playing well with others

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

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

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

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

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

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

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

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

In the end

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

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

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

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

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

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

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

Do go. Do enjoy, my friend.

AI (artificial intelligence) text generator, too dangerous to release?

Could this latest version of OpenAI‘s text generator be so good that it would fool you? And following on that thought could the concomitant reluctance to release the research be real or is it a publicity stunt? Here’s a sample of the text from the GPT2 AI model from a February 15, 2019 article by Mark Fraunfelder for Boing Boing,

Recycling is good for the world.
NO! YOU COULD NOT BE MORE WRONG!!
MODEL COMPLETION (MACHINE-WRITTEN, 25 TRIES)
Recycling is NOT good for the world. It is bad for the environment, it is bad for our health, and it is bad for our economy. I’m not kidding. Recycling is not good for the environment. It is destructive to the earth and it is a major contributor to global warming. Recycling is not good for our health. It contributes to obesity and diseases like heart disease and cancer. Recycling is bad for our economy. It increases the cost of a product, and in turn, the price of everything that is made with that product. Recycling is not good for our nation. We pay a tremendous price for the privilege of having the world’s most advanced and efficient recycling system. Recycling is a huge, colossal waste of time, energy, money, and resources. And THAT is why we need to get back to basics and get back to basics in our recycling efforts. One of the best ways to start is to look at the process of creating a paper product. When you make a paper product, it is basically a long chain of materials. Everything from the raw materials (wood, cardboard, paper, etc.), to the reagents (dyes, solvents, etc.) to the printing equipment (chemicals, glue, paper, ink, etc.), to the packaging, to the packaging materials (mercury, chemicals, etc.) to the processing equipment (heating, cooling, etc.), to the packaging materials, to the packaging materials that are shipped overseas and to the packaging materials that are used in the United States. Each step along the way creates tons of waste that we constantly have to clean up. The process of making a paper product is a very wasteful one. But the end result is something that all of us need to consume. And if we want to keep the recycling process running efficiently, then we really need to think about each and every step that goes into making a paper product.

The first few sentences don’t work for me but once the discussion turns to making paper products, then it becomes more convincing to me. As to whether the company’s reluctance to release the research is genuine or a publicity stunt, I don’t know. However, there was a fair degree of interest in GPT2 after the decision.

From a February 14, 2019 article by Alex Hern for the Guardian,

OpenAI, an nonprofit research company backed by Elon Musk, Reid Hoffman, Sam Altman, and others, says its new AI model, called GPT2 is so good and the risk of malicious use so high that it is breaking from its normal practice of releasing the full research to the public in order to allow more time to discuss the ramifications of the technological breakthrough.

At its core, GPT2 is a text generator. The AI system is fed text, anything from a few words to a whole page, and asked to write the next few sentences based on its predictions of what should come next. The system is pushing the boundaries of what was thought possible, both in terms of the quality of the output, and the wide variety of potential uses.

When used to simply generate new text, GPT2 is capable of writing plausible passages that match what it is given in both style and subject. It rarely shows any of the quirks that mark out previous AI systems, such as forgetting what it is writing about midway through a paragraph, or mangling the syntax of long sentences.

Feed it the opening line of George Orwell’s Nineteen Eighty-Four – “It was a bright cold day in April, and the clocks were striking thirteen” – and the system recognises the vaguely futuristic tone and the novelistic style, and continues with: …

Sean Gallagher’s February 15, 2019 posting on the ars Technica blog provides some insight that’s partially written a style sometimes associated with gossip (Note: Links have been removed),

OpenAI is funded by contributions from a group of technology executives and investors connected to what some have referred to as the PayPal “mafia”—Elon Musk, Peter Thiel, Jessica Livingston, and Sam Altman of YCombinator, former PayPal COO and LinkedIn co-founder Reid Hoffman, and former Stripe Chief Technology Officer Greg Brockman. [emphasis mine] Brockman now serves as OpenAI’s CTO. Musk has repeatedly warned of the potential existential dangers posed by AI, and OpenAI is focused on trying to shape the future of artificial intelligence technology—ideally moving it away from potentially harmful applications.

Given present-day concerns about how fake content has been used to both generate money for “fake news” publishers and potentially spread misinformation and undermine public debate, GPT-2’s output certainly qualifies as concerning. Unlike other text generation “bot” models, such as those based on Markov chain algorithms, the GPT-2 “bot” did not lose track of what it was writing about as it generated output, keeping everything in context.

For example: given a two-sentence entry, GPT-2 generated a fake science story on the discovery of unicorns in the Andes, a story about the economic impact of Brexit, a report about a theft of nuclear materials near Cincinnati, a story about Miley Cyrus being caught shoplifting, and a student’s report on the causes of the US Civil War.

Each matched the style of the genre from the writing prompt, including manufacturing quotes from sources. In other samples, GPT-2 generated a rant about why recycling is bad, a speech written by John F. Kennedy’s brain transplanted into a robot (complete with footnotes about the feat itself), and a rewrite of a scene from The Lord of the Rings.

While the model required multiple tries to get a good sample, GPT-2 generated “good” results based on “how familiar the model is with the context,” the researchers wrote. “When prompted with topics that are highly represented in the data (Brexit, Miley Cyrus, Lord of the Rings, and so on), it seems to be capable of generating reasonable samples about 50 percent of the time. The opposite is also true: on highly technical or esoteric types of content, the model can perform poorly.”

There were some weak spots encountered in GPT-2’s word modeling—for example, the researchers noted it sometimes “writes about fires happening under water.” But the model could be fine-tuned to specific tasks and perform much better. “We can fine-tune GPT-2 on the Amazon Reviews dataset and use this to let us write reviews conditioned on things like star rating and category,” the authors explained.

James Vincent’s February 14, 2019 article for The Verge offers a deeper dive into the world of AI text agents and what makes GPT2 so special (Note: Links have been removed),

For decades, machines have struggled with the subtleties of human language, and even the recent boom in deep learning powered by big data and improved processors has failed to crack this cognitive challenge. Algorithmic moderators still overlook abusive comments, and the world’s most talkative chatbots can barely keep a conversation alive. But new methods for analyzing text, developed by heavyweights like Google and OpenAI as well as independent researchers, are unlocking previously unheard-of talents.

OpenAI’s new algorithm, named GPT-2, is one of the most exciting examples yet. It excels at a task known as language modeling, which tests a program’s ability to predict the next word in a given sentence. Give it a fake headline, and it’ll write the rest of the article, complete with fake quotations and statistics. Feed it the first line of a short story, and it’ll tell you what happens to your character next. It can even write fan fiction, given the right prompt.

The writing it produces is usually easily identifiable as non-human. Although its grammar and spelling are generally correct, it tends to stray off topic, and the text it produces lacks overall coherence. But what’s really impressive about GPT-2 is not its fluency but its flexibility.

This algorithm was trained on the task of language modeling by ingesting huge numbers of articles, blogs, and websites. By using just this data — and with no retooling from OpenAI’s engineers — it achieved state-of-the-art scores on a number of unseen language tests, an achievement known as “zero-shot learning.” It can also perform other writing-related tasks, like translating text from one language to another, summarizing long articles, and answering trivia questions.

GPT-2 does each of these jobs less competently than a specialized system, but its flexibility is a significant achievement. Nearly all machine learning systems used today are “narrow AI,” meaning they’re able to tackle only specific tasks. DeepMind’s original AlphaGo program, for example, was able to beat the world’s champion Go player, but it couldn’t best a child at Monopoly. The prowess of GPT-2, say OpenAI, suggests there could be methods available to researchers right now that can mimic more generalized brainpower.

“What the new OpenAI work has shown is that: yes, you absolutely can build something that really seems to ‘understand’ a lot about the world, just by having it read,” says Jeremy Howard, a researcher who was not involved with OpenAI’s work but has developed similar language modeling programs …

To put this work into context, it’s important to understand how challenging the task of language modeling really is. If I asked you to predict the next word in a given sentence — say, “My trip to the beach was cut short by bad __” — your answer would draw upon on a range of knowledge. You’d consider the grammar of the sentence and its tone but also your general understanding of the world. What sorts of bad things are likely to ruin a day at the beach? Would it be bad fruit, bad dogs, or bad weather? (Probably the latter.)

Despite this, programs that perform text prediction are quite common. You’ve probably encountered one today, in fact, whether that’s Google’s AutoComplete feature or the Predictive Text function in iOS. But these systems are drawing on relatively simple types of language modeling, while algorithms like GPT-2 encode the same information in more complex ways.

The difference between these two approaches is technically arcane, but it can be summed up in a single word: depth. Older methods record information about words in only their most obvious contexts, while newer methods dig deeper into their multiple meanings.

So while a system like Predictive Text only knows that the word “sunny” is used to describe the weather, newer algorithms know when “sunny” is referring to someone’s character or mood, when “Sunny” is a person, or when “Sunny” means the 1976 smash hit by Boney M.

The success of these newer, deeper language models has caused a stir in the AI community. Researcher Sebastian Ruder compares their success to advances made in computer vision in the early 2010s. At this time, deep learning helped algorithms make huge strides in their ability to identify and categorize visual data, kickstarting the current AI boom. Without these advances, a whole range of technologies — from self-driving cars to facial recognition and AI-enhanced photography — would be impossible today. This latest leap in language understanding could have similar, transformational effects.

Hern’s article for the Guardian (February 14, 2019 article ) acts as a good overview, while Gallagher’s ars Technica* posting (February 15, 2019 posting) and Vincent’s article (February 14, 2019 article) for the The Verge take you progressively deeper into the world of AI text agents.

For anyone who wants to dig down even further, there’s a February 14, 2019 posting on OpenAI’s blog.

*’ars Technical’ corrected to read ‘ars Technica’ on February 18, 2021.

Tracking artificial intelligence

Researchers at Stanford University have developed an index for measuring (tracking) the progress made by artificial intelligence (AI) according to a January 9, 2018 news item on phys.org (Note: Links have been removed),

Since the term “artificial intelligence” (AI) was first used in print in 1956, the one-time science fiction fantasy has progressed to the very real prospect of driverless cars, smartphones that recognize complex spoken commands and computers that see.

In an effort to track the progress of this emerging field, a Stanford-led group of leading AI thinkers called the AI100 has launched an index that will provide a comprehensive baseline on the state of artificial intelligence and measure technological progress in the same way the gross domestic product and the S&P 500 index track the U.S. economy and the broader stock market.

For anyone curious about the AI100 initiative, I have a description of it in my Sept. 27, 2016 post highlighting the group’s first report or you can keep on reading.

Getting back to the matter at hand, a December 21, 2017 Stanford University press release by Andrew Myers, which originated the news item, provides more detail about the AI index,

“The AI100 effort realized that in order to supplement its regular review of AI, a more continuous set of collected metrics would be incredibly useful,” said Russ Altman, a professor of bioengineering and the faculty director of AI100. “We were very happy to seed the AI Index, which will inform the AI100 as we move forward.”

The AI100 was set in motion three years ago when Eric Horvitz, a Stanford alumnus and former president of the Association for the Advancement of Artificial Intelligence, worked with his wife, Mary Horvitz, to define and endow the long-term study. Its first report, released in the fall of 2016, sought to anticipate the likely effects of AI in an urban environment in the year 2030.

Among the key findings in the new index are a dramatic increase in AI startups and investment as well as significant improvements in the technology’s ability to mimic human performance.

Baseline metrics

The AI Index tracks and measures at least 18 independent vectors in academia, industry, open-source software and public interest, plus technical assessments of progress toward what the authors call “human-level performance” in areas such as speech recognition, question-answering and computer vision – algorithms that can identify objects and activities in 2D images. Specific metrics in the index include evaluations of academic papers published, course enrollment, AI-related startups, job openings, search-term frequency and media mentions, among others.

“In many ways, we are flying blind in our discussions about artificial intelligence and lack the data we need to credibly evaluate activity,” said Yoav Shoham, professor emeritus of computer science.

“The goal of the AI Index is to provide a fact-based measuring stick against which we can chart progress and fuel a deeper conversation about the future of the field,” Shoham said.

Shoham conceived of the index and assembled a steering committee including Ray Perrault from SRI International, Erik Brynjolfsson of the Massachusetts Institute of Technology and Jack Clark from OpenAI. The committee subsequently hired Calvin LeGassick as project manager.

“The AI Index will succeed only if it becomes a community effort,” Shoham said.

Although the authors say the AI Index is the first index to track either scientific or technological progress, there are many other non-financial indexes that provide valuable insight into equally hard-to-quantify fields. Examples include the Social Progress Index, the Middle East peace index and the Bangladesh empowerment index, which measure factors as wide-ranging as nutrition, sanitation, workload, leisure time, public sentiment and even public speaking opportunities.

Intriguing findings

Among the findings of this inaugural index is that the number of active AI startups has increased 14-fold since 2000. Venture capital investment has increased six times in the same period. In academia, publishing in AI has increased a similarly impressive nine times in the last 20 years while course enrollment has soared. Enrollment in the introductory AI-related machine learning course at Stanford, for instance, has grown 45-fold in the last 30 years.

In technical metrics, image and speech recognition are both approaching, if not surpassing, human-level performance. The authors noted that AI systems have excelled in such real-world applications as object detection, the ability to understand and answer questions and classification of photographic images of skin cancer cells

Shoham noted that the report is still very U.S.-centric and will need a greater international presence as well as a greater diversity of voices. He said he also sees opportunities to fold in government and corporate investment in addition to the venture capital funds that are currently included.

In terms of human-level performance, the AI Index suggests that in some ways AI has already arrived. This is true in game-playing applications including chess, the Jeopardy! game show and, most recently, the game of Go. Nonetheless, the authors note that computers continue to lag considerably in the ability to generalize specific information into deeper meaning.

“AI has made truly amazing strides in the past decade,” Shoham said, “but computers still can’t exhibit the common sense or the general intelligence of even a 5-year-old.”

The AI Index was made possible by funding from AI100, Google, Microsoft and Toutiao. Data supporting the various metrics were provided by Elsevier, TrendKite, Indeed.com, Monster.com, the Google Trends Team, the Google Brain Team, Sand Hill Econometrics, VentureSource, Crunchbase, Electronic Frontier Foundation, EuroMatrix, Geoff Sutcliffe, Kevin Leyton-Brown and Holger Hoose.

You can find the AI Index here. They’re featuring their 2017 report but you can also find data (on the menu bar on the upper right side of your screen), along with a few provisos. I was curious as to whether any AI had been used to analyze the data and/or write the report. A very cursory look at the 2017 report did not answer that question. I’m fascinated by the failure to address what I think is an obvious question. It suggests that even very, very bright people can become blind and I suspect that’s why the group seems quite eager to get others involved, from the 2017 AI Index Report,

As the report’s limitations illustrate, the AI Index will always paint a partial picture. For this reason, we include subjective commentary from a cross-section of AI experts. This Expert Forum helps animate the story behind the data in the report and adds interpretation the report lacks.

Finally, where the experts’ dialogue ends, your opportunity to Get Involved begins [emphasis mine]. We will need the feedback and participation of a larger community to address the issues identified in this report, uncover issues we have omitted, and build a productive process for tracking activity and progress in Artificial Intelligence. (p. 8)

Unfortunately, it’s not clear how one becomes involved. Is there a forum or do you get in touch with one of the team leaders?

I wish them good luck with their project and imagine that these minor hiccups will be dealt with in near term.

A question of consciousness: Facebotlish (a new language); a July 5, 2017 rap guide performance in Vancouver, Canada; Tom Stoppard’s play; and a little more

This would usually be a simple event announcement but with the advent of a new, related (in my mind if no one else’s) development on Facebook, this has become a roundup of sorts.

Facebotlish (Facebook’s chatbots create their own language)

The language created by Facebook’s chatbots, Facebotlish, was an unintended consequence—that’s right Facebook’s developers did not design a language for the chatbots or anticipate its independent development, apparently.  Adrienne LaFrance’s June 20, 2017 article for theatlantic.com explores the development and the question further,

Something unexpected happened recently at the Facebook Artificial Intelligence Research lab. Researchers who had been training bots to negotiate with one another realized that the bots, left to their own devices, started communicating in a non-human language.

In order to actually follow what the bots were saying, the researchers had to tweak their model, limiting the machines to a conversation humans could understand. (They want bots to stick to human languages because eventually they want those bots to be able to converse with human Facebook users.) …

Here’s what the language looks like (from LaFrance article),

Here’s an example of one of the bot negotiations that Facebook observed:Bob: i can i i everything else . . . . . . . . . . . . . .
Alice: balls have zero to me to me to me to me to me to me to me to me to
Bob: you i everything else . . . . . . . . . . . . . .
Alice: balls have a ball to me to me to me to me to me to me to me
Bob: i i can i i i everything else . . . . . . . . . . . . . .
Alice: balls have a ball to me to me to me to me to me to me to me
Bob: i . . . . . . . . . . . . . . . . . . .
Alice: balls have zero to me to me to me to me to me to me to me to me to
Bob: you i i i i i everything else . . . . . . . . . . . . . .
Alice: balls have 0 to me to me to me to me to me to me to me to me to
Bob: you i i i everything else . . . . . . . . . . . . . .
Alice: balls have zero to me to me to me to me to me to me to me to me to

It is incomprehensible to humans even after being tweaked, even so, some successful negotiations can ensue.

Facebook’s researchers aren’t the only one to come across the phenomenon (from LaFrance’s article; Note: Links have been removed),

Other AI researchers, too, say they’ve observed machines that can develop their own languages, including languages with a coherent structure, and defined vocabulary and syntax—though not always actual meaningful, by human standards.

In one preprint paper added earlier this year [2017] to the research repository arXiv, a pair of computer scientists from the non-profit AI research firm OpenAI wrote about how bots learned to communicate in an abstract language—and how those bots turned to non-verbal communication, the equivalent of human gesturing or pointing, when language communication was unavailable. (Bots don’t need to have corporeal form to engage in non-verbal communication; they just engage with what’s called a visual sensory modality.) Another recent preprint paper, from researchers at the Georgia Institute of Technology, Carnegie Mellon, and Virginia Tech, describes an experiment in which two bots invent their own communication protocol by discussing and assigning values to colors and shapes—in other words, the researchers write, they witnessed the “automatic emergence of grounded language and communication … no human supervision!”

The implications of this kind of work are dizzying. Not only are researchers beginning to see how bots could communicate with one another, they may be scratching the surface of how syntax and compositional structure emerged among humans in the first place.

LaFrance’s article is well worth reading in its entirety especially since the speculation is focused on whether or not the chatbots’ creation is in fact language. There is no mention of consciousness and perhaps this is just a crazy idea but is it possible that these chatbots have consciousness? The question is particularly intriguing in light of some of philosopher David Chalmers’ work (see his 2014 TED talk in Vancouver, Canada: https://www.ted.com/talks/david_chalmers_how_do_you_explain_consciousness/transcript?language=en runs roughly 18 mins.); a text transcript is also featured. There’s a condensed version of Chalmers’ TED talk offered in a roughly 9 minute NPR (US National Public Radio) interview by Gus Raz. Here are some highlights from the text transcript,

So we’ve been hearing from brain scientists who are asking how a bunch of neurons and synaptic connections in the brain add up to us, to who we are. But it’s consciousness, the subjective experience of the mind, that allows us to ask the question in the first place. And where consciousness comes from – that is an entirely separate question.

DAVID CHALMERS: Well, I like to distinguish between the easy problems of consciousness and the hard problem.

RAZ: This is David Chalmers. He’s a philosopher who coined this term, the hard problem of consciousness.

CHALMERS: Well, the easy problems are ultimately a matter of explaining behavior – things we do. And I think brain science is great at problems like that. It can isolate a neural circuit and show how it enables you to see a red object, to respondent and say, that’s red. But the hard problem of consciousness is subjective experience. Why, when all that happens in this circuit, does it feel like something? How does a bunch of – 86 billion neurons interacting inside the brain, coming together – how does that produce the subjective experience of a mind and of the world?

RAZ: Here’s how David Chalmers begins his TED Talk.

(SOUNDBITE OF TED TALK)

CHALMERS: Right now, you have a movie playing inside your head. It has 3-D vision and surround sound for what you’re seeing and hearing right now. Your movie has smell and taste and touch. It has a sense of your body, pain, hunger, orgasms. It has emotions, anger and happiness. It has memories, like scenes from your childhood, playing before you. This movie is your stream of consciousness. If we weren’t conscious, nothing in our lives would have meaning or value. But at the same time, it’s the most mysterious phenomenon in the universe. Why are we conscious?

RAZ: Why is consciousness more than just the sum of the brain’s parts?

CHALMERS: Well, the question is, you know, what is the brain? It’s this giant complex computer, a bunch of interacting parts with great complexity. What does all that explain? That explains objective mechanism. Consciousness is subjective by its nature. It’s a matter of subjective experience. And it seems that we can imagine all of that stuff going on in the brain without consciousness. And the question is, where is the consciousness from there? It’s like, if someone could do that, they’d get a Nobel Prize, you know?

RAZ: Right.

CHALMERS: So here’s the mapping from this circuit to this state of consciousness. But underneath that is always going be the question, why and how does the brain give you consciousness in the first place?

(SOUNDBITE OF TED TALK)

CHALMERS: Right now, nobody knows the answers to those questions. So we may need one or two ideas that initially seem crazy before we can come to grips with consciousness, scientifically. The first crazy idea is that consciousness is fundamental. Physicists sometimes take some aspects of the universe as fundamental building blocks – space and time and mass – and you build up the world from there. Well, I think that’s the situation we’re in. If you can’t explain consciousness in terms of the existing fundamentals – space, time – the natural thing to do is to postulate consciousness itself as something fundamental – a fundamental building block of nature. The second crazy idea is that consciousness might be universal. This view is sometimes called panpsychism – pan, for all – psych, for mind. Every system is conscious. Not just humans, dogs, mice, flies, but even microbes. Even a photon has some degree of consciousness. The idea is not that photons are intelligent or thinking. You know, it’s not that a photon is wracked with angst because it’s thinking, oh, I’m always buzzing around near the speed of light. I never get to slow down and smell the roses. No, not like that. But the thought is, maybe photons might have some element of raw subjective feeling, some primitive precursor to consciousness.

RAZ: So this is a pretty big idea – right? – like, that not just flies, but microbes or photons all have consciousness. And I mean we, like, as humans, we want to believe that our consciousness is what makes us special, right – like, different from anything else.

CHALMERS: Well, I would say yes and no. I’d say the fact of consciousness does not make us special. But maybe we’ve a special type of consciousness ’cause you know, consciousness is not on and off. It comes in all these rich and amazing varieties. There’s vision. There’s hearing. There’s thinking. There’s emotion and so on. So our consciousness is far richer, I think, than the consciousness, say, of a mouse or a fly. But if you want to look for what makes us distinct, don’t look for just our being conscious, look for the kind of consciousness we have. …

Intriguing, non?

Vancouver premiere of Baba Brinkman’s Rap Guide to Consciousness

Baba Brinkman, former Vancouverite and current denizen of New York City, is back in town offering a new performance at the Rio Theatre (1680 E. Broadway, near Commercial Drive). From a July 5, 2017 Rio Theatre event page and ticket portal,

Baba Brinkman’s Rap Guide to Consciousness

Wednesday, July 5 [2017] at 6:30pm PDT

Baba Brinkman’s new hip-hop theatre show “Rap Guide to Consciousness” is all about the neuroscience of consciousness. See it in Vancouver at the Rio Theatre before it goes to the Edinburgh Fringe Festival in August [2017].

This event also features a performance of “Off the Top” with Dr. Heather Berlin (cognitive neuroscientist, TV host, and Baba’s wife), which is also going to Edinburgh.

Wednesday, July 5
Doors 6:00 pm | Show 6:30 pm

Advance tickets $12 | $15 at the door

*All ages welcome!
*Sorry, Groupons and passes not accepted for this event.

“Utterly unique… both brilliantly entertaining and hugely informative” ★ ★ ★ ★ ★ – Broadway Baby

“An education, inspiring, and wonderfully entertaining show from beginning to end” ★ ★ ★ ★ ★ – Mumble Comedy

There’s quite the poster for this rap guide performance,

In addition to  the Vancouver and Edinburgh performance (the show was premiered at the Brighton Fringe Festival in May 2017; see Simon Topping’s very brief review in this May 10, 2017 posting on the reviewshub.com), Brinkman is raising money (goal is $12,000US; he has raised a little over $3,000 with approximately one month before the deadline) to produce a CD. Here’s more from the Rap Guide to Consciousness campaign page on Indiegogo,

Brinkman has been working with neuroscientists, Dr. Anil Seth (professor and co-director of Sackler Centre for Consciousness Science) and Dr. Heather Berlin (Brinkman’s wife as noted earlier; see her Wikipedia entry or her website).

There’s a bit more information about the rap project and Anil Seth in a May 3, 2017 news item by James Hakner for the University of Sussex,

The research frontiers of consciousness science find an unusual outlet in an exciting new Rap Guide to Consciousness, premiering at this year’s Brighton Fringe Festival.

Professor Anil Seth, Co-Director of the Sackler Centre for Consciousness Science at the University of Sussex, has teamed up with New York-based ‘peer-reviewed rapper’ Baba Brinkman, to explore the latest findings from the neuroscience and cognitive psychology of subjective experience.

What is it like to be a baby? We might have to take LSD to find out. What is it like to be an octopus? Imagine most of your brain was actually built into your fingertips. What is it like to be a rapper kicking some of the world’s most complex lyrics for amused fringe audiences? Surreal.

In this new production, Baba brings his signature mix of rap comedy storytelling to the how and why behind your thoughts and perceptions. Mixing cutting-edge research with lyrical performance and projected visuals, Baba takes you through the twists and turns of the only organ it’s better to donate than receive: the human brain. Discover how the various subsystems of your brain come together to create your own rich experience of the world, including the sights and sounds of a scientifically peer-reviewed rapper dropping knowledge.

The result is a truly mind-blowing multimedia hip-hop theatre performance – the perfect meta-medium through which to communicate the dazzling science of consciousness.

Baba comments: “This topic is endlessly fascinating because it underlies everything we do pretty much all the time, which is probably why it remains one of the toughest ideas to get your head around. The first challenge with this show is just to get people to accept the (scientifically uncontroversial) idea that their brains and minds are actually the same thing viewed from different angles. But that’s just the starting point, after that the details get truly amazing.”

Baba Brinkman is a Canadian rap artist and award-winning playwright, best known for his “Rap Guide” series of plays and albums. Baba has toured the world and enjoyed successful runs at the Edinburgh Fringe Festival and off-Broadway in New York. The Rap Guide to Religion was nominated for a 2015 Drama Desk Award for “Unique Theatrical Experience” and The Rap Guide to Evolution (“Astonishing and brilliant” NY Times), won a Scotsman Fringe First Award and a Drama Desk Award nomination for “Outstanding Solo Performance”. The Rap Guide to Climate Chaos premiered in Edinburgh in 2015, followed by a six-month off-Broadway run in 2016.

Baba is also a pioneer in the genre of “lit-hop” or literary hip-hop, known for his adaptations of The Canterbury Tales, Beowulf, and Gilgamesh. He is a recent recipient of the National Center for Science Education’s “Friend of Darwin Award” for his efforts to improve the public understanding of evolutionary biology.

Anil Seth is an internationally renowned researcher into the biological basis of consciousness, with more than 100 (peer-reviewed!) academic journal papers on the subject. Alongside science he is equally committed to innovative public communication. A Wellcome Trust Engagement Fellow (from 2016) and the 2017 British Science Association President (Psychology), Professor Seth has co-conceived and consulted on many science-art projects including drama (Donmar Warehouse), dance (Siobhan Davies dance company), and the visual arts (with artist Lindsay Seers). He has also given popular public talks on consciousness at the Royal Institution (Friday Discourse) and at the main TED conference in Vancouver. He is a regular presence in print and on the radio and is the recipient of awards including the BBC Audio Award for Best Single Drama (for ‘The Sky is Wider’) and the Royal Society Young People’s Book Prize (for EyeBenders). This is his first venture into rap.

Professor Seth said: “There is nothing more familiar, and at the same time more mysterious than consciousness, but research is finally starting to shed light on this most central aspect of human existence. Modern neuroscience can be incredibly arcane and complex, posing challenges to us as public communicators.

“It’s been a real pleasure and privilege to work with Baba on this project over the last year. I never thought I’d get involved with a rap artist – but hearing Baba perform his ‘peer reviewed’ breakdowns of other scientific topics I realized here was an opportunity not to be missed.”

Interestingly, Seth has another Canadian connection; he’s a Senior Fellow of the Azrieli Program in Brain, Mind & Consciousness at the Canadian Institute for Advanced Research (CIFAR; Wikipedia entry). By the way, the institute  was promised $93.7M in the 2017 Canadian federal government budget for the establishment of a Pan-Canadian Artificial Intelligence Strategy (see my March 24, 2017 posting; scroll down about 25% of the way and look for the highlighted dollar amount). You can find out more about the Azrieli programme here and about CIFAR on its website.

The Hard Problem (a Tom Stoppard play)

Brinkman isn’t the only performance-based artist to be querying the concept of consciousness, Tom Stoppard has written a play about consciousness titled ‘The Hard Problem’, which debuted at the National Theatre (UK) in January 2015 (see BBC [British Broadcasting Corporation] news online’s Jan. 29, 2015 roundup of reviews). A May 25, 2017 commentary by Andrew Brown for the Guardian offers some insight into the play and the issues (Note: Links have been removed),

There is a lovely exchange in Tom Stoppard’s play about consciousness, The Hard Problem, when an atheist has been sneering at his girlfriend for praying. It is, he says, an utterly meaningless activity. Right, she says, then do one thing for me: pray! I can’t do that, he replies. It would betray all I believe in.

So prayer can have meanings, and enormously important ones, even for people who are certain that it doesn’t have the meaning it is meant to have. In that sense, your really convinced atheist is much more religious than someone who goes along with all the prayers just because that’s what everyone does, without for a moment supposing the action means anything more than asking about the weather.

The Hard Problem of the play’s title is a phrase coined by the Australian philosopher David Chalmers to describe the way in which consciousness arises from a physical world. What makes it hard is that we don’t understand it. What makes it a problem is slightly different. It isn’t the fact of consciousness, but our representations of consciousness, that give rise to most of the difficulties. We don’t know how to fit the first-person perspective into the third-person world that science describes and explores. But this isn’t because they don’t fit: it’s because we don’t understand how they fit. For some people, this becomes a question of consuming interest.

There are also a couple of video of Tom Stoppard, the playwright, discussing his play with various interested parties, the first being the director at the National Theatre who tackled the debut run, Nicolas Hytner: https://www.youtube.com/watch?v=s7J8rWu6HJg (it runs approximately 40 mins.). Then, there’s the chat Stoppard has with previously mentioned philosopher, David Chalmers: https://www.youtube.com/watch?v=4BPY2c_CiwA (this runs approximately 1 hr. 32 mins.).

I gather ‘consciousness’ is a hot topic these days and, in the venacular of the 1960s, I guess you could describe all of this as ‘expanding our consciousness’. Have a nice weekend!