Predictable Identities: 4 – Stereotypes

This entry is part 4 of 11 in the series Predictable Identities

How do we predict strangers?

Humans evolved in an environment where they rarely had to do this. Practically everyone a prehistoric human met was familiar and could be modeled individually based on their past interactions. But today, we deal with ever-stranger strangers on big city streets, in global markets, online…

We need to make quick predictions about people we’ve never met. We do it using stereotypes.

Early research on stereotypes focused on their affective aspect: we dislike strangers, but less so as we get to know them. But new studies have looked at the content of stereotypes, finding that groups are judged independently on the dimensions of warmth/competitiveness and status/competence. For example, Germans see Italians as high-warmth low-competence, i.e. lovable buffoons; Italians see Germans as the exact opposite, i.e. mercenary experts.

These dimensions are primarily about predicting someone’s behavior and capability. In game theory terms: Will that person cooperate? And can I safely defect on them or do I have to play nice?

Contrary to the well-meaning wishes of most stereotype researchers, there is robust empirical evidence on stereotype accuracy. The short of it is that people’s stereotypes are, in fact, quite accurate, especially stereotypes of gender and ethnicity. Whether stereotyping is good or bad, it cannot simply be wished “educated” away. It is universal because it’s very useful for prediction.

A smart person noted that problems arise from having too few stereotypes, not too many. If you have a single stereotype for “Jews” you’re doing a bad job of modeling Jewish people, and are likelier to mistreat them due to prejudice. If you have separate stereotypes for Hasidic Jews, Brooklyn conservative Zionists, liberal Jewish atheists, secular Israelis etc. you’re one step closer to treating (and modeling) unfamiliar Jews as individuals. Studying cultures is about acquiring many useful stereotypes.

Refactorings Roundup: 1/28/19 – 3/10/19

This entry is part 9 of 9 in the series Refactorings Roundups

It’s been nearly 6 weeks since the last time I did this roundup from our mastodon. It’s now a series, so you can navigate backwards to find good stuff.  Even with some automation (thanks Zach), generating a reasonable curated selection from the hive-mind of a community is not an easy task. Still, I find it’s worth doing for the sheer oddity of the things that get into the dragnet.

In other news, I’ve gotten really good at making omeletes with the Just Egg plant-based egg substitute, which is really good.

Unlike auteur-curated link roundups, which tend to have an impoverished sameness even with the best curators, a reasonable sized community that is sufficiently open tends to have weird shit on its mind if you periodically fMRI it. I’ve been trying to follow a bonsai-style curation approach, trying to reveal the natural tendencies of this firehose rather than filter by my own interests. We have a total of 16 posts from friends of ribbonfarm, and 27 links from around the web.

Among the new posts, I want to call out Chenoe Hart’s post Free Shipping (#1 on the New Posts list), Sarah Constantin’s posts on general intelligence (#7) and Ilia Gimelfarb’s post (#14).

Alright here we go.

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Weirding Diary: 5

This entry is part 5 of 8 in the series Weirding Diary

In the South Lake Union part of Seattle, where Amazon has its campus, there is a “community banana stand” where anyone can grab a banana for free. Each time I walk by, I read the sign as a philosophical suggestion for the Weirding. When the going gets weird, the weird go pro, but normies go bananas.

But there’s a deeper lesson in the banana stand.

Most people (including me) who grab a banana are not exactly needy, so to the extent “community” suggests a representative sample of Seattle, including the poor and homeless, the banana stand is in the wrong place. It’s a perk for tech-workers, and the service class surrounding it, with a bit of communitarian lipstick.

As elite hypocrisies go, this one is pretty benign, and I’m happy to participate in it. But why do we even need it? Why narrativize free bananas as a “community” perk.

I think the answer lies in the is-ought fallacy operating among elites to counter-program a self-awareness of their own mediocrity: “These free bananas, which we share out of noblesse oblige, demonstrate our exceptional nature!”

This is an elite rationalization, but the urge to deny rather than embrace a sense of mediocrity is a human universal. In fact, I would define normie as “somebody with an urge to deny their mediocrity.”

Mediocrity denial is using exceptional environments to “prove” your exceptional nature to yourself. It leads to bad theories of weird worlds.

The mediocrity-embracing solution, which is a necessary condition to go pro weird, is to resist the urge to ideologically narrativize bananas. Grab a free banana when you can, pay for your banana when you must.

Weirding and mediocrity are entangled in my head. I haven’t entirely sorted out how, but one dimension is certainly the is-ought fallacy in identity formation.

Infinite Machines: 1 – An Introduction

This entry is part 1 of 3 in the series Infinite Machine

Like the universe, technology, an extension of the self, is expanding fast.

The infinite machine is the idea that we’re becoming machine-like through the use of human-like machines. It is a phenomenon at the intersection of automation, labor, gratification, and human desire.

In this expansion of technology, I argue that we compromise aspects of our humanity in ways that are hard to see for some, and harder to associate meaning to for others. So the further we ‘progress’, the less we intrinsically understand why we choose to expand.

AI is still evolving (broadly completing narrow tasks) and has done a decent job mimicking human attributes: neural computation, analytical decision-making, and natural language processing to name a few. But despite the rudimentary functionality of AI today, the idea of an AI singularity sparks both fear and allure amongst the world’s top physicists and inventors.

This series explores contending identity attributes between the computer science of AI and spirit of humanity, through a few critical lenses:

  1. Growing emotional and psychological dissonance of laborers involved in the delivery of AI technologies.
  2. Unrealized tension that laborers experience in the process, which range from microaggressions to economic exploitation.
  3. Evolving perceptions of power and free will as AI technologies become more anthropomorphic.

A recurring challenge across these areas, which I’ll examine, is detangling the inherent value from its value proposition: Let’s connect you to the world in ways that you never imagined. For example, last week, I booked a taxi, confirmed a tinder date, and discovered a new music genre – all in three minutes. As the third minute passed, I realized I hadn’t pushed any buttons in the elevator which I was standing in.

I was doing ‘things,’ but going nowhere. This, of course, is a metaphor for the collective human identity.

Predictable Identities: 3 – Prisoner’s Dilemma

This entry is part 3 of 11 in the series Predictable Identities

Much of human interaction is shaped by the structure of the prisoner’s dilemma. We put in place institutions and norms to enforce cooperation. We tell shared stories to inspire it. We evolved moral emotions to achieve cooperation on an interpersonal level: empathy and gratitude to assure cooperators of our cooperation, anger and vengefulness to punish defectors, tribalism and loyalty to cooperate with those we know well.

But the crux of the prisoner’s dilemma is that defection is always better for the defector. We try to get others to cooperate with us, but we also try to defect as much as we can get away with. We want our peers to pay their taxes, admit mistakes, share credit, and stay faithful. We also fudge our taxes, shift blame, boast, and cheat.

There are many strategies for dealing with PD, and some of them can be formalized in code and entered in competitions with other strategies. The simple strategies are named and studied: tit-for-tat responds to each play in kind, tit-for-two-tats forgives one deception in case it was a mistake, Pavlov changes tacks after being defected against and so on and so forth. Which strategy works best?

It turns out that the success of each strategy depends almost entirely on the strategies played by opponents. Each approach can fail to reach cooperation with others or under-exploit opportunities to defect; even a strategy of always defecting is optimal if enough other players always cooperate. If you only knew what your opponent is playing, you could always choose the best option.

And this brings us back to predicting other humans. If we can model their strategies, if we know who will be forgiving and kind, who will be vengeful and dangerous, we can play optimally in any situation. Predicting well is the unbeatable strategy.

Mediocratopia: 3

This entry is part 3 of 5 in the series Mediocratopia

Mediocrity is, rather appropriately, under-theorized.  An upcoming book by David S. Milo, Good Enough (ht Keerthik), seems set to make it a little less undertheorized. The subtitle is inspiringly underwhelming: The tolerance of mediocrity in nature and society.  Reader Killian Butler sent me this post on being mediocre. Our movement is really slouching along now.

There is a paradox at the heart of mediocrity studies: excellence is not actually exceptional. If you see an excellent behavior or thing, it’s likely to be a middling instance at its level. The perception of exceptionalism is an illusion caused by inappropriate comparisons: you think it is a 99 percentile example of Level 3 performance, but it’s really a median example of Level 4 performance.

Changing levels of performance is self-disruption. The moment you hit, say, the 60% performance point on the current S-curve of learning, you start looking for ways to level up. This is the basic point in Daniel F. Chambliss’ classic paper, The Mundanity of ExcellencePeople who rise through the levels of a competitive sport do so by making discrete qualitative changes to level up before they hit diminishing returns from the current level. This process of leveling up, has less to do with striving for excellence in the sense of exceptional performance, and more to do with repeatedly growing past limits. The visibly excellent are never at a local optimum.

In Age of Speed, skier Vince Poscente claims he won primarily by practicing his skills at a level above the one he was competing at. So during actual competition, he could win with less than 100% effort.

Making winning a habit is about making sure you’re always operating at a level where you have slack; where you are in fact mediocre. If you’re being pushed towards excellence, it’s time to find a new level.

Worlding Raga: 2 – What is a World?

This entry is part 2 of 6 in the series Worlding Raga

Hi, I’m Ian Cheng. I’m an artist. Over the last six years, I’ve been creating a series of simulations that explore an agent’s capacity to deal with an ever-changing environment. These works culminated in the Emissaries trilogy, which introduced a narrative agent — the emissary — whose motivation to enact a story was set into conflict with the open-ended chaos of a simulation. In the process, I began to see the edges of a new layer of artistic activity. One that could organize my base ingredients — deterministic stories and open-ended simulations — into something more than the sum of its parts. Something meaningful yet alive, bounded yet transforming. I’ve been calling this activity Worlding.

At Venkat’s invitation, I’m contributing to Worlding Raga with the hope of further developing a literacy around Worlding. As a tourist of this part of the blogosphere, I’ve been drawn to the spiritual dimension of Ribbonfarm again and again. It is the side of Ribbonfarm that is hungry to identify phenomena in the wild that don’t seem to die, and to name them so that they are enduring tools for others to see and act anew. This voluntary desire to surf chaos, metabolize it into new order, and then do it all over again, is sometimes called “walking with god.” Maybe it’s more like slouching with god around here. Either way, it is a spirit I resonate with and one that I believe is highly suited to Worlding.

First things first. What is a World?

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Domestic Cozy: 1

This entry is part 1 of 5 in the series Domestic Cozy

I made a prediction on Twitter on February 6th: If Millennials (b. 1980 – 2000) were the premium mediocre generation, Gen Z (b. 2000 – 2020) is going to be the domestic cozy generation.

I was waiting for the perfect image to start blogging the idea, and last week supplied one: the Celestial Buddies plush toy that rode on the Crew Dragon test flight. The symbolism is perfect: an oddly satisfying little squeezable nugget of comfort within the disorienting, weird domesticity of a spaceship.

Domestic cozy is in an attitude, emerging socioeconomic posture, and aesthetic, that is in many ways the antithesis of premium mediocrity. Unsurprisingly, it takes its cues from the marginal shadow behaviors of premium mediocrity.

It finds its best expression in privacy, among friends, rather than in public, among strangers. It prioritizes the needs of the actor rather than the expectations of the spectator. It seeks to predictably control a small, closed environment rather than gamble in a large, open one. It presents a WYSIWYG facade to those granted access rather than performing in a theater of optics.

Premium mediocre seeks to control its narrative. Domestic cozy is indifferent both to being misunderstood and being ignored.

Instagram, Tinder, kale salads, and Urban Outfitters are premium mediocre. Minecraft, YouTube, cooking at home, and knitting are domestic cozy. Steve Jobs represented the premium that premium mediocrity aspired towards. Elon Musk represents the relaxed-playfulness-amidst-weirdness at the heart of domestic cozy.

Premium mediocre looks outward with a salesman affect, edgy anxiety bubbling just below the surface. Domestic cozy looks inward with a relaxed affect. A preternaturally relaxed affect bordering on creepy. One best embodied by the rise of the ASMR-like sensory modality (which even the NYT has noticed) that has come to be known as oddly satisfying.

Premium mediocrity is the same everywhere, every patch of domestic cozy is domestic cozy in its own way.

Premium mediocrity expends enormous energy preserving the illusion of normalcy. Domestic cozy slouches into the weirdness and simply ignores it, preferring to construct sources of comfort rather than trying to make sense of the weirdness in the environment.

Premium mediocrity strains to pretend it understands what is going on. Domestic cozy openly acknowledges it has no clue, and simply seeks to preserve equanimity, if not sanity. Premium mediocrity is edgily neurotic. Domestic cozy is blissfully psychotic.

As an aesthetic, domestic cozy superficially resembles the hipster aesthetic. There is a focus on craft and production, and it can appear artisan-like due to the focus on small, individual scale. The key differences are that the locus of the aesthetic is domestic rather than public, and it has no particular affection for retro traditionalism. Both knitting and Minecraft can be domestic cozy.

The key is that the activity must be conducive to an oddly satisfying state of mind within the weirding.

The oldest Z’s are just about enter adulthood. Unlike premium mediocrity, which I called at its peak, I’m calling domestic cozy just as it is getting started. So I’ll track it as a blogchain.

Markets Are Eating The World

For the last hundred years, individuals have worked for firms, and, by historical standards, large ones.

That many of us live in suburbs and drive our cars into the city to go to work at a large office building is so normal that it seems like it has always been this way. Of course, it hasn’t. In 1870, almost 50 percent of the U.S. population was employed in agriculture.[1] As of 2008, less than 2 percent of the population is directly employed in agriculture, but many people worked for these relatively new things called “corporations.”[2]

Many internet pioneers in the 90’s believed that the internet would start to break up corporations by letting people communicate and organize over a vast, open network. This reality has sort-of played out: the “gig economy” and rise in freelancing are persistent, if not explosive, trends. With the re-emergence of blockchain technology, talk of “the death of the firm” has returned. Is there reason to think this time will be different?

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Predictable Identities: 2 – Active Inference

This entry is part 2 of 11 in the series Predictable Identities

One sentence recap of Part I: our brains are constantly trying to make true predictions about the world. We do it in two ways:

  1. Assembling good models that make accurate predictions.
  2. Changing the world to match our predictions.

When Apple released a buggy version of Maps, The Onion joked that “Apple is fixing glitches in Maps by rearranging Earth’s geography”. That’s exactly what our brains do.

Actions are driven by predictions propagating across different levels. We shoot a basketball by forecasting the flight of the ball, which leads to predicting that we will lift the ball and push it, culminating in precise anticipations of the required tension in the arm muscles. We are satisfied when the ball flies according to our projection and upset when it doesn’t

That’s why predicting well is so important to our evolved brains – when we predict well we know how to act to achieve our goals. A predictable environment is an exploitable environment.

Of course, basketballs are not a big component of our milieu, and our ability to predict them isn’t crucial. What is vital for us to model above all else are people, from faraway strangers to neighbors and friends. Also ourselves: prediction happens at different parts of the brain simultaneously, and each module has to predict what the others would do, now and in the future.

Predictive processing expert Sun Tzu observed:

If you know the enemy and know yourself, you need not fear the result of a hundred battles.

We observe other minds, interrogate them, and push them to conform to our models of them as best we can – all to maximize our predictive power and capacity to act effectively. This is a powerful lens through which to observe how we interact with others, and how we build our own predictable identities.