Enjoying Toronto’s Bike Share in the summer

On Wednesday evening, I did a 55km bike ride: east from the U of T campus across the Don into the beaches area, down to the southern tip of Tommy Thomson Park, then along the waterfront for a picnic dinner at a Queen’s Quay grocery store, and up the hill to The Perch.

These animations show the ride in yellow as well as all my previous walks and rides since 2020 in green:

Taleb on the domain dependence of knowledge

I used to attend a health club in the middle of the day and chat with an interesting Eastern European fellow with two Ph.D. degrees, one in physics (statistical no less), the other in finance. He worked for a trading house and was obsessed with the anecdotal aspects of the markets. He once asked me doggedly what I thought the stock market would do that day. Clearly I gave him a social answer of the kind “I don’t know, perhaps lower”-quite possibly the opposite answer to what I would have given him had he asked me an hour earlier. The next day he showed great alarm upon seeing me. He went on and on discussing my credibility and wondering how I could be so wrong in my “predictions,” since the market went up subsequently. Now, if I went to the phone and called him and disguised my voice and said, “Hello, this is Doktorr Talebski from the Academy of Lodz and I have an interrresting prrroblem,” then presented the issue as a statistical puzzle, he would laugh at me. “Doktorr Talevski, did you get your degree in a fortune cookie?” Why is it so?

Clearly there are two problems. First, the quant did not use his statistical brain when making the inference, but a different one. Second, he made the mistake of overstating the importance of small samples (in this case just one single observation, the worst possible inferential mistake a person can make). Mathematicians tend to make egregious mathematical mistakes outside of their theoretical habitat. When Tversky and Kahneman sampled mathematical psychologists, some of whom were authors of statistical textbooks, they were puzzled by their errors. “Respondents put too much confidence in the result of small samples and their statistical judgments showed little sensitivity to sample size.” The puzzling aspect is that not only should they have known better, “they did know better.” And yet…

Taleb, Nassim Nicholas. The Black Swan: The Impact of the Highly Improbable. Random House, 2007. p. 194-5 (italics in original)

A broad-ranging talk with James Burke

As part of promoting a new Connections series on Curiosity Stream launching on Nov. 9, I got the chance to interview historian of science and technology, science communicator, and series host James Burke:

The more interview-intensive part begins at 3:10.

Reviewing an unreleased book and TV show

While it won’t help with my rent, I nonetheless have some very interesting work for the next few days.

I am doing a close read twice of Professor Peter Russell’s forthcoming memoirs, which has been a privelege because of the respect I have for him as a thinker and a person, and a joy because of their colour, humour, and personality.

I am also previewing a new series of James Burke’s TV show Connections, which previously ran in 1978, 1994, and 1997. I have seen those old shows many times, and I thought a lot about his book The Axemaker’s Gift back in high school. I have the chance to interview him from Monaco on Wednesday, so I am giving the new material a careful viewing and thinking through how to make the best use of the conversation. There is scarcely a person I can think of who has a more educated and wide-ranging understanding of the relationships between science, technology, and human society. Since human civilization is presently hurtling toward a brick wall which threatens to rather flatten us all, it may be invaluable to get Burke’s views on how a defensive strategy from here can be undertaken.

Related:

Libraries as sanctuaries

At least since elementary school, I have loved the combination of charms offered by libraries, perhaps chief among them the provision of a serene space for concentration and thought with the freedom indiscriminately granted to take an interest in anything from the collection. I remember at my elementary school library, at Cleveland Elementary School, there were wooden-drawered filing cabinets for index cards. I remember the age-yellowed peculiar tinge and feeling of the index cards, perhaps made by hand on a typewriter, and the feeling of avenues into knowledge being revealed through the process of beginning with any topic of interest and working from books to index to books to begin tracing paths on rivers of thought and language that exist to help us each understand the world.

The first massive library which I was free to explore was the colosseum-inspired Central Branch of the Vancouver Public Library, which was approved by referendum in 1990 and opened for public use in 1995. My friend Chevar and I were excused by our parents from school to attend the grand opening, which included a massive chocolate cake in the shape of the building’s unique form. For visitors to Vancouver, I strongly recommend going up to the appropriate floors to try the sky bridges and outer seating areas available on the far side of the central atrium. It’s a place where I read happily until I stopped being a Vancouver resident, and I can still remember the way the brand-new-library smell evolved into a stable characteristic odor with a hint of escalator oil and rubber as base notes.

Still Robarts-ing

After defending my dissertation in December and collecting my diploma in March, I have been watching my U of T benefits gets deactivated one by one. They cut off my dental insurance between when I defended and when I graduated. My campus wifi access was withdrawn several months ago. As of July, my T-card no longer provided access to Robarts or Gerstein libraries.

I feel it would be a shame to live in a city with a library system like U of T’s and be unable to access it. Luckily, as an alumnus I can get a borrower card for $70 per year. It comes with the very annoying restrictions of no campus wifi use, and no off-campus access to electronic databases — but it does provide access to all U of T libraries, allows you to withdraw fifty (50!) books, and allows access to services like research consultations. I now officially have permission to use U of T’s vast library resources to research anything of personal interest or importance. It’s also a great place to hide from summer heat if you don’t have AC at home.

Can a machine with no understanding be right, even when it happens to be correct?

We are using a lot of problematic and imprecise language where it comes to AI that writes, which is worsening our deep psychological tendency to assume that anything that shows glimmers of human-like traits ought to be imagined with a complex internal life and human-like thoughts, intentions, and behaviours.

We talk about ChatGPT and other large language models (LLMs) “being right” and “making mistakes” and “hallucinating things”.

The point I would raise is — if you have a system that sometimes gives correct answers, is it ever actually correct? Or does it just happen to give correct information in some cases, even though it has no ability to tell truth from falsehood, and even though it will just be random where it happens to be correct?

If you use a random number generator to pick a number from 1–10, and then ask that program over and over “What is 2+2?” you will eventually get a “4”. Is the 4 correct?

What is you have a program that always outputs “4” no matter what you ask it. Is it “correct” when you ask “What is 2+2?” and incorrect when you ask “What is 1+2?”?

Perhaps one way to lessen our collective confusion is to stick to AI-specific language. AI doesn’t write, get things correct, or make mistakes. It is a stochastic parrot with a huge reservoir of mostly garbage information from the internet, and it mindlessly uses known statistical associations between different language fragments to predict what ought to come next when parroting out some new text at random.

If you don’t like the idea that what you get from LLMs will be a mishmash of the internet’s collective wisdom and delusion, presided over by an utterly unintelligent word statistic expert, then you ought to be cautious about letting LLMs do your thinking for you, either as a writer or a reader.

Ologies on invisibility

Alie Ward’s marvellous science communication podcast has a new episode on invisibility: Invisible Photology (INVISIBILITY CLOAKS) with Dr. Greg Gbur.

I was just about bowled over during my exercise walk on the Beltline trail, when Alie and Dr. Gbur discussed my Hyperface Halloween costume, designed to confound facial recognition systems.

Tomorrow I will read Dr. Gbur’s latest book: Invisibility: The History and Science of How Not To Be Seen.