MJD 59,459

This entry is part 19 of 21 in the series Captain's Log

In 2018, historian Michael McCormick nominated 536 AD as the worst year to be alive. There was a bit of fun coverage of the claim. This sort of thing is what I think of as “little history.” It’s the opposite of Big History.

Big History is stuff like Yuval Noah Harari’s Sapiens, Jared Diamond’s Guns, Germs, and Steel, or David Graeber’s Debt. I was a fan of that kind of sweeping, interpretive history when I was younger, but frankly, I really dislike it now. Historiographic constructs get really dubious and sketchy when stretched out across the scaffolding of millennia of raw events. Questions that are “too big to succeed” in a sense, like “why did Europe pull ahead of China,” tend to produce ideologies rather than histories. It’s good for spitballing and first-pass sense-making (and I’ve done my share of it on this blog) but not good as a foundation for any deeper thinking. Even if you want to stay close to the raw events, you get sucked into is-ought historicist conceits, and dangerously reified notions like “progress.” Yes, I’m also a big skeptic of notions like Progress Studies. To the extent that the arc of the moral universe has any coherent shape at all, to proceed on the assumption that it has an intelligible shape (whether desired or undesired), is to systematically blind yourself to the strong possibility that the geometry of history is, if not random, at least fundamentally amoral.

About the only Big History notion I have any affection for is Francis Fukuyama’s notion that in an important sense, Big History has ended (and I’m apparently the last holdout, given that Fukuyama himself has sort of walked back the idea).

Little histories though, are another matter. Truly little histories are little in both space and time, and much of history is intrinsically little in that sense, and fundamentally limited in the amount of inductive or abductive generalization it supports once you let go of overly ambitious historicist conceits and too-big-to-succeed notions like “Progress.” But some little histories are, to borrow a phrase from Laura Spinney’s book about the Spanish Flu, Pale Rider, “broad in space, shallow in time.” They allow you to enjoy most of the pleasures afforded by Big Histories, without the pitfalls.

Whether or not the specific year 536 was in fact the worst year, and whether or not the question of a “worst year” is well-posed, the year was definitely “broad in space, shallow in time” due to the eruption of an Icelandic volcano that created extreme weather world-wide. The list of phenomena capable of creating that kind of globalized entanglement of local histories is extremely short: pandemics, correlated extreme weather, and the creation or destruction of important technological couplings.

The subset of little histories that are “broad in space, shallow in time” — call them BISSIT years (or weeks, or days) — serve as synchronization points for the collective human experience. Most historical eras feature both “good” and “bad” from a million perspectives. Sampling perspectives from around the world at a random time, and adjusting for things like class and wealth, you would probably get a mixed bag of gloomy and cheery perspectives that are not all gloomy or cheery in the same way. But it is reasonable to suppose that at these synchronization points, systematic deviations from the pattern would emerge. Notions of good and bad align. Many of us would probably agree that 2020 sucked more than most years, and would even agree on the cause (the pandemic), and key features of the suckage (limitations on travel and socialization). Even if there were positive aspects to it, and much needed systemic changes ensue in future years, for those of us alive today, who are living through this little history, the actual experience of it kinda sucks.

The general question of whether the human condition is progressing or declining to me is both ill-posed and uninteresting. You get into tedious and sophomoric debates about material prosperity versus perceived relative deprivation. You have people aiming gotchas at each other (“aha, the Great Depression was actually more materially prosperous than optimistic Gilded Age 1890s!” or “there was a lot of progress during the Dark Ages!”).

The specific question of whether a single BISSIT year should be tagged with positive or negative valence though, is much more interesting, since the normal variety of “good” and “bad” perspectives temporarily narrows sharply. Certainly, BISSIT years have a sharply defined character given by their systematic deviations, and sharp boundaries in time. They are “things” in the sense of being ontologically well-posed historiographic primitives that are larger than raw events, but aren’t reified and suspect constructs like “Progress” or “Enlightenment.” There is a certain humility to asking whether these specific temporal things are good or bad, as opposed to the entire arc of history. Two such things need not be good or bad in the same way. History viewed as a string of such BISSIT beads need not have a single character. Perhaps there are red, green, and blue beads punctuating substrings of grey beads, and in your view, red and green beads are good, while blue beads are bad, and so on. We don’t have to have a futile debate about Big History that’s really about ideological tastes. But we can argue about whether specific beads are red or blue. You can ask about the colors of historical things. We can take note of the relative frequencies of colored versus grey beads. And if you’re inclined to think about Big History at all, you can approach it as the narrative of a string of beads that need not have an overall morally significant character. Perhaps, like space, time can be locally “flat” (good or bad as experienced by the people within BISSIT epochs) but have no moral valence globally. Perhaps we live in curved historical event-time, with no consistent “up” everywhere.

MJD 59,436

This entry is part 18 of 21 in the series Captain's Log

A week ago, for the first time in decades, I spent several days in a row doing many hours of hands-on engineering work in a CAD tool (for my rover project), and noticed that I had particularly vivid dreams on those nights. My sleep data from my Whoop strap confirmed that I’d had higher REM sleep on those nights.

These were dreams that lacked narrative and emotional texture, but involved a lot of logistics. For example, one dream I took note of involved coordinating a trip with multiple people, with flights randomly canceled. When I shared this on Twitter, several people replied to say that they too had similar dreams after days of intense but relatively routine information work. A couple of people mentioned dreaming of Tetris after playing a lot, something I too have experienced. High-REM dreaming sleep seems to be involved in integrating cognitive skill memories. This paper by Erik Hoel, The Overfitted Brain: Dreams evolved to assist generalization, pointed out by @nosilver, argues that dreaming is about mitigating overfitting of learning experiences, a problem also encountered in deep learning. This tracks for me. It sounds reasonable that my “logistics” dreams were attempts to generalize some CAD skills to other problems with similar reasoning needs. REM sleep is like the model training phase of deep learning.

Dreams 2×2

This got me interested in the idea of tapping into the unconscious towards pragmatic ends. For example, using the type of dreams you have to do feedback regulation of the work you do during the day. I made up a half-assed hypothesis: the type of dream you have at night depends on 2 variables relating to the corresponding daytime activity — the level of conflict in the activity (low/high) and whether or not the learning loop length is longer or shorter than 24 hours. If it is shorter, you can complete multiple loops in a day and the night-time dream will need to generalize from multiple examples. If it’s less than a complete loop, there is no immediate resolution, so instead you get more dreams that integrate experiences in an open-loop way, using narrative-based explanations. If there’s no conflict and no closed loops, you get low dreaming. There’s nothing to integrate, and you didn’t do much thinking that day (which for me tends to translate to poor sleep). I made up the 2×2 above for this idea.

I have no idea whether this particular 2×2 makes any sense, but it is interesting that such phenomenology lends itself to apprehension in such frameworks at all. I rarely remember dreams, but I think even I could maintain a dream journal based on this scheme, and try to modulate my days based on my nights.

This also helps explain why people in similar situations might have similar dreams (such as all the “corona dreams” that many of us were having during early lockdown months). It also lends substance to the narrative conceits of stories like H. P. Lovecraft’s Call of Cthulhu, which begins with people having widespread similar dreams (where it turns into science fiction is in the specificity of the shared motifs and symbols that appear).

You don’t need to buy into dubious Jungian or Freudian theories of individual and collective dreaming to think about this stuff in robust ways. The development of deep learning, in particular, offers us a much more robust handle on this phenomenology. Dreams are perhaps our journeys into our private latent spaces, undertaken for entirely practical purposes like cleaning up our messy daytime learning (there’s other theories of dreaming too of course, like David Eagleman’s theory that we dream to prevent the visual centers from getting colonized by other parts of the brain at night, but we’re only hypothesizing contributing causes, not determinative theories).

Mediocratopia: 10

This entry is part 10 of 12 in the series Mediocratopia

I once read a good definition of aptitude. Aptitude is how long it takes you to learn something. The idea is that everybody can learn anything, but if it takes you 200 years, you essentially have no aptitude for it. Useful aptitudes are in the <10 years range. You have aptitude for a thing if the learning curve is short and steep for you. You don’t have aptitude if the learning curve is gentle and long for you.

How do you measure your aptitude though? Things like standardized aptitude tests only cover narrow aspects of a few things. One way to measure it is in terms of the speed at which you can do a complete loop of production. Your aptitude is the rate at which this cycle speed increases. This can’t increase linearly though, or you’d be superhuman in no time. There’s a half life to it. Your first short story takes 10 days to write. The next one 5 days, the next one 2.5 days, the next one 1.25 days. Then 0.625 days, at which point you’re probably hitting raw typing speed limits. In practice, improvement curves have more of a staircase quality to them. Rather than fix the obvious next bottleneck of typing speed (who cares if it took you 3 hours instead of 6 to write a story; the marginal value of more speed is low at that point), you might level up and decide to (say) write stories with better developed characters. Or illustrations. So you’re back at 10 days, but on a new level. This is the mundanity of excellence effect I discussed in part 3, and this is an essential part of mediocratization. Ironically, people like Olympic athletes get where they get by mediocratizing rather than optimizing what they do. Excellence lies in avoiding the naive excellence trap.

This kind of improvement replaces quantitative improvement (optimization) with qualitative leveling up, or dimensionality increase. Each time you hit diminishing returns, you open up a new front. You’re never on the slow endzone of a learning curve. You self-disrupt before you get stuck. So you get a learning curve that looks something like this (yes, it’s basically the stack of intersecting S-curves effect, with the lower halves of the S curves omitted)

The interesting effect is that even though any individual smooth learning effort is an exponential with a half-life, since you keep skipping levels, you can have a roughly linear rate of progress, but on a changing problem. You’re never getting superhuman on any vector because you keep changing tack to keep progressing. The y-axis is a stack of different measures of performance, normalized as percentages of an ideal maximal performance level, estimated as the limit of the Zeno’s paradox race at each level.

Now we have a slightly better way to measure aptitude. Aptitude is the rate at which you level up, by changing the nature of the problem you’re solving (and therefore how you measure “improvement”). The interesting thing is, this is not purely a function not of raw prowess or innate talent, but of imagination and taste. Can you sense diminishing returns and open up a new front so you can keep progressing? How early or late do you do that? The limiting factor here is the imaginative level shift that keeps you moving. Being stuck is being caught in the diminishing returns part of a locally optimal learning curve because you can’t see the next curve to jump to.

Your natural wavelength is the rate at which you level up (so your natural frequency is the inverse of that). Two numbers characterize your aptitude: the half-life within a level, and the number of typical iterations you put in before you change levels (which is also — how deep you get into the diminishing returns part of the curve before you level up).

The Retiree

This entry is part 6 of 8 in the series Fiction

The media storm the publicists had been bracing for never occurred. There was no damage to control. The attention they had been instructed to deflect from the Baikal Trust never materialized.

And it was not because Ozy Khan was the thirty-seventh billionaire to launch himself boringly into space, in a space mansion of his own design. The thirty-fifth and thirty-sixth billionaires to do so, after all, had endured nearly as much press, both hostile and adulatory, as the first few had, decades earlier. The public, it seemed, never lost its appetite for the spectacle of great wealth ascending to extra-terrestrial heights. And the billionaires too, had perfected the art of image management in space. There had already been at least three short-lived, but successful reality shows from orbiting mansions.

Nor could the lack of a media storm be attributed to Ozy Khan being an obscure Central Asian oligarch rather than a prominent American or Chinese one. More obscure billionaires had managed to inspire large spikes of interest by ascending to vacations in luridly ostentatious space mansions, and been rewarded with notoriety around the world for their extended departures from it. A space mansion was a reliable ticket onto the center stage of global affairs.

Space after all, as one much-quoted wag had remarked in the 2020s, was the new Davos.

Even the fact that Ozy Khan would not be coming back was not without precedent. The seventh and eleventh billionaires, each terminally ill and with less than a year to live, had both launched themselves on one way trips into space with much funereal solemnity. Both had duly died in space with cosmic gravitas, and been forgotten. Only old people made hope-he-doesn’t-come-back jokes anymore.

Perhaps the lack of drama could be attributed, one commentator suggested, to the fact that Khan had been such a dull presence on earth, it was was hard to craft a story around his departure from it. His sprawling renewables and sequestration technologies empire lacked charisma. It embodied no daring technological vision, only powerful political connections, a lot of imitation and luck, and plodding, sound financial management. His official biography offered little of interest to the story-minded. His career suggested no more than the usual amount of tedious politicking, grift, and geopolitical murkiness.

There really was very little to say about Ozy Khan’s time on earth before he decided to leave it.

[Read more…]

MJD 59,396

This entry is part 17 of 21 in the series Captain's Log

I’ve developed two obsessions through the pandemic that I think will persist long past the end of it, probably to the end of my life: tinkering and story-telling.

On the tinkering front, I’ve built out a nice little science-and-engineering workshop over the last year and acquired more skills in less time than I expected to, since I don’t have a high opinion of my own hands-on abilities. As I’ve mentioned before, this is still hard to write about because while the doing is fun, getting to interesting things to show off and talk about will take some time. It’s good enough fodder for tweeting though, and I’ve been maintaining several fun ongoing threads about electronics experiments, my rover project, and 3d printing. At some point, I hope I’ll be able to write essays about this stuff, but right now it’s only coming together at Twitter level. Overall, tinkering has been the easier journey, I guess because I’m an engineer by training, so I am not really starting from scratch. Though all my old knowledge feels rusty, I think I did hit the ground running when I started around August last year.

Storytelling has been the tougher journey. In many ways, it’s very like tinkering, except with machines that run inside human brains. It is very unlike nonfiction writing. I’ve made more progress on exploring storytelling theory than in actually telling stories. But one of my breakthroughs was realizing that storytelling as a skill is orthogonal to writing skill, and the latter even gets in the way. One way to short-circuit the writer brain is to use cartoons, and I’ve done 2 comic-format stories so far this year: Space Luck and Comet Bob. I’ve also managed one prose story, Non-Contact, though it’s more a world-building design study of an idea than a fully developed story, kinda like the design study prototype I built for my rover early on. I am not yet sure what my storytelling medium is — words or pictures.

Together, these two obsessions are driving what I think is the biggest pivot not just in the life of this blog, but in my own adult life. It’s a lifestyle shift, and I’m still coming to grips with the cascading effects on other aspects of my life. Storytelling tinkerers, I am discovering, must necessarily live a different kind of life than essayist-consultant-observers. So I’ve unwittingly set up a certain narrative tension in my life that’s going to resolve itself one way or another. It’s a different headspace, as lived from the inside, and presents a different picture when viewed from the outside. Switching between nonfiction and fiction modes, or between management consulting and maker-tinkerer modes, is very disorienting, but not in an unpleasant way.

One interesting thing about both is that they are behaviors that can get you put in more of a box than the sorts of thing I’m better known for. Storytelling and tinkering are both play-like behaviors that have a lot more disruptive potential than most “serious” behaviors, but they look harmless and are easy to put in a box and ignore. They are the quintessential mostly-harmless human activities. The median tinkering project or story is entirely inconsequential. Net likelihood of impact, zero. You either enjoy the safe, marginalized obscurity of the boxes you get put in, or you’re playing for the one-in-a-million shot at making history. I’m not sure what I’m aiming at with either activity. Probably both outcomes in proportion to their actual probabilities.

At any rate, it’s nice to have some obsessions going. It makes me feel strangely young again. Obsessiveness is naturally a young person’s mode of being. To discover it again in middle age, in a somewhat mellowed form, is something of an unexpected gift, even if the precipitating event of a pandemic makes it something of a gift from the devil.

Storytelling — Matthew Dicks

This entry is part 4 of 10 in the series Narrativium

I recently finished, Storyworthy by Matthew Dicks, a quintessentially American storyteller in the Mark Twain tradition. It is perhaps the most unique book on narrative structure and theory I’ve read, after Keith Johnstone’s Impro.

Dicks appears to have lived a very colorful, eventful life that supplies all the raw material you might ever want, to tell lots of outrageous, extreme stories. A very American life. I have friends like that, whose lives seem to be a string of outrageous and improbable events that make for naturally good stories. Only the manner of telling needs work. Dicks insists, however, that you do not need to live a colorful life in order to tell colorful stories. That’s good news for me.

[Read more…]

Storytelling — Mamet’s Conflict Airing Theory

This entry is part 3 of 10 in the series Narrativium

One of the big questions to which I have yet to find a satisfying answer is what stories are, in the set of things that includes various other kinds of speech. David Mamet has what I think is a partial answer in Three Uses of a Knife, a short, stream-of-consciousness meditation on storytelling which I recently finished (ht: Sachin Benny).

I like plays, but not enough to be an avid theater-goer, so my only real exposure to Mamet’s work is the movie version of Glengarry Glen Ross, which lives up to its reputation, and a few episodes of The Unit, which I didn’t quite get into. But his storytelling chops are clearly strong enough for his theorizing to be interesting. His practical advice certainly is — here is a memo he sent to the staff of the Unit (ht Steve Hely), with plenty of gems in it.

But this post is about Mamet’s philosophy of storytelling, not his bag of tricks.

Mamet opens Three Uses of a Knife with a discussion of our tendency to dramatize entirely mundane everyday events, like a bus being late, or the state of the weather, into proto-stories. His opening example is:

“Great. It’s raining. Just when I’m blue. Isn’t that just like life?:

His exegesis:

[Read more…]


This entry is part 7 of 8 in the series Fiction

Perhaps it was some sort of strange precognitive cultural memory of the future, but the cliches, it turned out, were all true. Well, almost all true. The aliens did come in large flying saucers that could hover silently and move silently at physics-defying speeds. They did make mysterious crop circles and abduct and probe hundreds of unfortunates — except this time, they were taken from and returned to (disoriented and with memory gaps, but otherwise unharmed) busy public areas, in broad daylight, in full view of hundreds of smartphones. Those who had been taken in previous years and decades, from deserted highways or remote farms, were at once ecstatic and depressed. Now everybody agreed they’d been telling the truth all along, but nobody thought they were special, or even uniquely insane, anymore.

[Read more…]

Space Luck

This entry is part 5 of 8 in the series Fiction
[Read more…]

MJD 59,354

This entry is part 16 of 21 in the series Captain's Log

Peter Turchin’s concept of elite overproduction has been on my mind increasingly lately. It refers to historical conditions during which there are more people aspiring to elite roles in society than power structures can absorb. In 2021, to a first approximation, this is people with college degrees in fields with low market demand. A good measure of the degree of overproduction is the intensity and rancor around STEM vs. humanities type debates, and “do you want fries with that?” jokes about art history degrees. The idea of elite overproduction is descriptive, not normative. It does not matter who wins Twitter debates about the “true” cultural value of various elite roles and aspirations. What matters is the actual distribution of unemployed human elite overstocks. When large masses of people fail to find economic means to sustain the elite social roles they’ve been conditioned to expect, and trained and enculturated to occupy, you have elite overproduction going on. The prevailing default perception of the specifics of the distribution of surplus elites is correct in broad strokes, even if there are weird exceptions and corner cases. It is probably true right now that the average STEM degree is less likely to make you part of the elite overstock than a humanities degrees.

The jokes about do-you-want-fries-with-that are particularly fraught this year. Service industries struggle to hire workers, but are wary of letting wages inflate even as various other price levels succumb. Unlike commodity prices, which can go up and down with supply and demand, wages are something of a sociopolitical one-way door. They’re harder to push back down once they manage to creep up. There is revolutionary fervor in the air as well, around everything from student-loan forgiveness and stimulus economics to policing and urban blight. The optics around great wealth are much uglier today than 10 years ago, when they were last in the spotlight to this degree. Gen X has joined the Boomers on the villains side of the aisle. Younger generations struggle, while older generations sit on top of record savings.

One reason to take elite overproduction theory seriously as a lens right now is that Turchin has been unusually right lately in his calls about the timing of historical crisis points. He anticipated that 2020 would be a year of crisis, and it was. He didn’t predict Covid afaik, but the pandemic was merely a cherry on top of the dire basic scenario he foresaw.

Thirteen years ago, the Global Financial Crisis led to a generation of disaffected and underemployed young graduates turning their online-native skills to culture-warring. Ten years ago, that reached a flashpoint with the Occupy movement, and led to far right and far left movements making inroads into mainstream politics and shaping the next decade. That whole story was primarily an elite overproduction story. To the extent there was non-elite energy in the movements, it was there because it had been co-opted by wannabe-elite actors in service of their own frustrations. In the US, urban black political issues turned into white wannabe-elite causes, rural and small-town rust-belt blue collar issues turned into white wannabe-elite causes as well. For a few years, all political roads led to elite overstocks, often being transformed unrecognizably in the process. The result was the volatile mix of genuine and imagined grievances, insincere co-option of non-elite causes, and outright grift, that gave us the Great Weirding.

It’s commencement season and we can expect to see a new crop of commencement speeches soon. The global Class of 2021 will probably be much smaller than normal, and have to make do with curtailed or online ceremonies. Despite the small size of the cohort though, I suspect, most of this year’s crop of fresh graduates will still struggle to find jobs and careers, and be in a worse situation than the Class of 2008. I wonder what the commencement speakers will say. I’d have nothing much inspiring to say if challenged to give such a speech. It is hard for privileged older generations to say useful things to younger generations entering adulthood under much worse conditions.

Conditions today are far more fraught than in 2008. Freshly minted Zoomer wannabe-elites today are likely more disaffected than the Millennials who came of age through the GFC, more skilled at channeling that disaffection into elite overstock unrest, and have more history to learn from. On the plus side (such as it is) they have only every known fraught times, and have never known hope in the sense Millennials did. Will that make them more or less energized? I don’t know.

But in the meantime, on the demand side, elite roles have become even more scarce, non-elite under-the-API roles are under even greater stress, and there has been essentially no political or economic movement on the issues of 2011. The far right has, to some extent, shot its shot, but the far left has yet to do so. All-in-all it’s a much bigger powder keg than 2011.

Unless something exceptionally big and positive happens soon, as the emergency civic discipline of Covid loosens its grip on populations around the world, we can expect the 2020s to get even more explosively weird than the 2010s.

Here we go again. Fasten your seatbelts.