Turning Red for adults. It works.

Trite and predictable, with stilted animation, convoluted storytelling, and a general feeling of awkwardness that drowns the few good early scenes. We were re-watching Ratatouille for what feels like the 56th time last weekend and it is ridiculous how much better it is in every respect despite being 15 years older. Luck… will not be getting a re-watch.

To get yourself in the right frame of mind before reading this book, try watching a few optical illusion videos. There is no reason to think our visual cortex is any dumber than the rest of the brain — in fact, quite the opposite. That our inference can be so easily fooled in a domain which is supposedly our strong suit is humbling.

Our statistical inference is even worse, so a short book or two on statistical numeracy should be in everyone’s library. Gerd Gigerenzer’s Calculated Risks can be that book for most people. The assumption, easily defensible, is that “most people” will get more use out of understanding frequentist rather than Bayesian probability. After all, most probabilities people are bombarded with — your chance of dying from breast cancer with and without screening, the chance of your neighbor being the killer given a positive DNA match (you know, the day-to-day stuff) — is frequentist.¹

The only reservation to wholeheartedly recommending Calculated Risks to everyone is that it falls into the category of “blog post books”, if you believe that most non-fiction books should, in fact, have been just blog posts. Or, since blogs are out of vogue, a 15-minute YouTube video may do. Or perhaps a single sentence: use natural instead of relative frequencies (e.g. 1 in 10.000 instead of 0.01%). Let your faulty cortex fill in the rest.

A massively biased and, ultimately, underwhelming account of jobs that even people performing them think shouldn’t exist. It is biased because David Graeber’s sole source of information — beside his own flowering mind — were his Twitter followers. More precisely: his followers’ self-imolations in prose sparked by the short essay which popularized the term. So you get not only a self-selected sample of young middle-class professionals discontent with their jobs, but also the attempts of that sample to connect with their anarchist idol. A fun game to play while plodding through these accounts — accounts which, by the way, take a full half of the book — is to spot the embelishments. There are many, and some even Graeber marks as such.

As for underwhelming, well, the book’s purely descriptive nature wouldn’t be so bad if it weren’t skin-deep. Graeber comes frustratingly close to asking some interesting questions;¹ alas, that would have required too much research. Instead we got fan mail copypasta and cheap digs at the corporate culture. So it goes…

Cal Newport’s new book goes well with David Graber’s Bullshit Jobs (about which more to come). Newport may have in fact provide a good, if partial, answer to one of Graber’s main questions — why have jobs that workers themselves see as useless proliferated in the last 50 years? No, it isn’t just email, but rather this: supporting structures of large institutions (think IT, HR, accounting, etc) have taken a life of their own and behave as if their own performance metrics — rather than the instituion’s primary reason for being — are all that matters. Enter thousands of survey requests, daily updates, weekly newsletters, calls for feedback… from dozens of departments all shouting about their contribution to the “core mission”.

So one way to get out of email hell is to work at a smaller place, having anyone completely dedicated to human resources being a good surrogate for being too large. But even that won’t completely save you: as long as you work in a team there will be need for internal communication, and as long as the primary mode of that communication is via email, the hyperactive hivemind — Newport’s preferred phrase — will ensue. Much of the book talks about how this came to be, and how to avoid it. While none of it is revolutionary (some of it even covered on this very blog, twice!), it did point me to Asana, Trello, and other collaborative task/project management apps with file storage and messaging capabilities as good alternatives that I tended to disregard.

As for external communication, well, if the email is longer than five sentences, better make it into a call, preferably the old-fashioned kind.

A World Without Email could easily have fit into the blog post in book form category but for the need to persuade key people that too much email is in fact a bad thing, said people being ones with power to save their employees from email hell yet not being aware that their employees need saving, as they themselves tend to be protected form the onslaught with layers and layers of administrative assistants¹. Judging from the reception in the types of newspapers “key people” tend to read, he has their attention.

How times change. What in the 1990s was fluff about the importance of learning, thinking, free speech, and civility for America’s continued progress now bounces between prophetic and controversial.

Of course, it wasn’t fluff. It was as true then as it is now, only this time there is no background hum of optimism to drown out the warning sirens. The country, subsumed by ignorance left, right and center — each stupid in their own way — went from being haunted by Demons to being run by them. We are living through Carl Sagan’s nightmare, brains turned off, phones in hand, fingers at the ready. So it goes.

It is a good thing for intellectual humility — particularly in middle age into which yours truly has stepped a few years ago¹ — to open an undergraduate textbook for a field that is just outside one’s area of expertise. A series of reviews on gene regulatory networks led me down a rabbit hole of vector fields and attractor states that was interesting-yet-unscrutable enough to get me to Understanding Nonlinear Dynamics.

It is very much a textbook, info-boxes, end-of-chapter exercise, and all. It also presupposes a grasp of mathematics which I may have had just out of high school but have long since lost. This is fine: at Mortimer Adler’s suggestion I zipped past the equations and derivations, deciding to trust the authors that they are indeed correct, and went to the meat. Which, in nonlinear dynamics, as a nice bonus, also has pretty pictures of fractals and vector fields. Alas, not as artistic as Charles Waddington’s, but nevertheless striking.

What surprised me the most was how much of the field resulted from mathematicians fiddling around with parameters to see what happens. Going to a textbook to learn this was overkill — the Wikipedia article on experimental mathematics may serve the purpose just as well — but knowing the context does make it memorable. There is a pleasing symmetry here: mathematics is usually thought of as purely theoretical, yet its most interesting aspects, Lorenz attractors to Wolfram’s (not so) “new kind of science”, have relied on experimentation. Biology has been purely experimental ever since Watson and Crick, aborted attempts at theoretical biology notwithstanding, and was even a decade ago producing more data than it can handle. Would it not be neat if the answer to this biological data overload wasn’t machine learning but instead a framework for theoretical biology? If there was one, nonlinear dynamics would play a big part.

It was a brave move, to release a TV show/limited series set in the aftermath of a world-ending respiratory virus pandemic right at the tail end of covid. Good thing that the execution was flawless, from the dream-like cinematography,¹ through casting, to Satoshi Kon-like editing. Notes of Watchmen, too, in how the source material is to be taken seriously but not literally when converting a book into something else.

Importantly, Station Eleven is set in, but is not about, a post-apocalyptic Earth, in much the same way Titanic was set in, but was not about, a sinking ship. Less romantic love and more parent/guardian/child love/hate relationships here, which is why it takes 9+ hours instead of 3+ to tell the story; but a full, rich, meaningful story is told, and told well. Kudos.

Bao meets The Mitchells… to produce something less artistic then either, but at least fun to watch. Mid-March release sounds about right.

There is no clearer sign of us entering a new era than reading a book from 2010. Not so long ago, wide-eyed journalists still described the Internet — note the capitalization¹ — as a force for good, an incubator of ideas whose capacity to connect people will lead to an exponential growth of innovation and prosperity. If one was to build a case against journalisitc blindness to externalities, Where Good Ideas Come From would make for a good exhibit.

The case against journalistic ignorance of patent law, too. The author, Steven Johnson, describes patents as means of rewarding inventors — and surely we can find a better way to reward them than a device that restricts the all-important distribution of knowledge. Only, that is not why the patent system was introduced, as described clearly if not succinctly by Vannevar Bush. Why a science journalist would straw-man a crucial factor of western technological superiority before attacking it is beyond the scope of this brief review.

The third feather in Johnson’s cap of muddled thinking is his conflation of discoveries and inventions, putting both under the broad category of “ideas”. The problem with that is apparent in the last few chapters of the book, where a series of 2x2s of ideas distributed according to the number of people involved (individual versus networked) and whether the enterprise is commercial (market versus non-market) “proves” Johnson’s case that non-market networked operations are superior, and should be supported above others. After all, from the 1800s onwards, most of the dots have been in their quadrant!

But here is a random² sample of the 54 ideas listed in the non-market/networked quadrant: electron, RNA splicing, chloroform, cell differentiation, EKG, cosmic rays, universe accelerating, genes and chromosomes, atoms form molecules, radiocarbon dating. Only one of those ten, EKG, is now a physical product being sold and used. Two more, RNA splicing and radiocarbon dating, are methods that could be commercialized. Those three I would describe as inventions, and all three have a rather limited scope of use. Everything else are discoveries, telling us things about how the world works but not directly improving our lives in any meaningful way, other than satisfying our thirst for knowledge.

Now here are 7 ideas randomly selected from the 35 listed in the market/networked quadrant: contact lenses, washing machine, plastic, elevator, steel, television, radio. If Johnson’s quadrants prove anything, it is that having market forces involved is strongly associated with invention. We can, of course, discuss the direction of that particular arrow, and whether markets co-opt inventions they deem useful rather than actually developing them. The distinct lack of inventions in parts of the world where market forces aren’t in play hints at my preferred answer.

Having said that, there are some good ideas in this book about good ideas. One of them, the adjacent possible, a mental model for both discovery and invention, is also the name Johnson now uses for his (rather … good) newsletter. That is the concept that made me remember the book fondly after my initial reading, 10 years ago, and it is the newsletter that made me re-read it. And a good thing too — because even though the book is the same, both I and the world have changed enough to make it irrelevant. It won’t be in my re-read list.