Longreads + Open Thread

Longreads

• Against Sloppypasta. When technology changes, social norms have to change, too, and one of the reasons that's hard is that there's typically a debate between maximalists, who are sure that some new technology will revolutionize everything and ought to be adopted for any conceivable use case, and luddites who think it's all a scam. What you need for norms to change is disagreeable moderates, who acknowledge a place for technology but also agree that it shouldn't be everywhere. This piece tries to demarcate that territory, mostly by noting that AI breaks the social contract where word count is a rough proxy for how much effort someone went to in their communication with you.
• McKay Coppins once got a call from a man who claimed he'd been kidnapped by drug cartels and forced to compete in an intra-cartel athletic competition where the losing team in each tournament bracket was summarily executed. A fun piece I won't spoil except to say that it could lead to a movie deal but probably should lead to two movie deals, for movies that are fun in different ways and marketed to completely different audiences.
• Harvey Lederman asks about what purpose we'll have if AI automates away intellectual labor. If your conception of yourself is that you figure things out, what do you do when machines are better at that than you'll ever be? If we have access to more knowledge than ever, but the most important concepts are beyond our comprehension, where does that leave us? In a sense, it leaves us right where we started: pre-scientific people had, by necessity, lots of local knowledge (which berries are delicious and which ones will kill you, for example), but didn't have much spare bandwidth for gathering data in order to test broad theories about why. Maybe the world where you can learn a lot, but might be able to contribute to the sum of human knowledge, is just a brief interruption to the confusing and incomprehensible default.
• Tyler Cowen interviews Harvey Mansfield, who has spent many decades being a curmudgeonly academic and has gotten really good at it. Mansfield is a Straussian scholar who's written extensively on Machiavelli (his work heavily informs The Diff's Discourses on Big Tech), which means he has very particular ideas about how to read the great books. Specifically, he applies a reading where the text is inerrant, but the message is deliberately obscure. This is a great way to get a lot out of a book, but is also a way to get out of the book more than what was really in it. He also notes that one of the strengths of Strauss's worldview is how textual it is, and how defined it is by particular texts. If all of the Straussians retire and die off, and there's a Straussless generation, as long as the writings are preserved, nothing prevents a Straussian revival. (I've noted before that highbrow progressivism is a live, continuous tradition, but highbrow conservatism is being continuously reinvented by either bookish people who grew up in a conservative milieu or by progressives who grew disenchanted.)
• Anna Weiner on love in the time of AI companions. It's a grim piece, but parasocial relationships have existed for a long time; there were probably people who had a similar relationship with fictional characters from TV, movies, and books in the past, but who didn't bother to vocalize what they'd say to these characters. Now that the characters can respond, in character, it's possible to write about the external signs of that inner experience. There's a certain kind of journalism that's tricky to pull off, where someone who's a status winner (e.g. they get to write for The New Yorker) writes about a status loser (someone who is in a love triangle with her husband and an AI character modeled on Geralt of Rivia). It's hard to write this without being condescending, but it's also hard to ignore the fact that some people spend the bulk of their leisure time cultivating relationships with bots.
• This week in Capital Gains, a look at what people get right and wrong about the collapse of Long-Term Capital Management. They were ahead of their time in many ways, including risk management. It's just very hard to predict the future, and especially hard when your own actions shape the correlations you're basing things on.
• A Read.Haus reader asks: "Say that an archeological expedition uncovers a tablet with rent rates for every Ley line on earth, payable whenever the cosmic empire of Spacemerica shows up to collect. The tablet is very convincing, everyone starts saving to pay the rent and will do so forever. How would the economic effects of Spacemerica actually existing and eventually collecting the rent and Spacemerica never showing up because they aren't real differ?" I confess, this is not a scenario I'd considered before. What this scenario basically works out to is an increase in real rates: if we're being taxed by aliens, they're getting currency that can be exchanged for goods and services, so we need less competition for current goods and services, and more production capacity for future goods and services. In fact, what this is really equivalent to is the current economic impact of a capital-intensive boom that bets on broad applications of some technology that doesn't currently have many uses. We'd redirect some money today from consumption to investment, and then reach an equilibrium where overall output is higher because we've accumulated more capital. If the rent never gets collected, we come out ahead.

Books

Cool: How Air Conditioning Changed Everything: Microhistories around a single product or invention can be hit or miss; The Prize is great for reframing the twentieth century as a history of oil, Paper had enough general-history errors to make its paper-specific claims questionable. Cool is on the very good end of that spectrum: it's the story of efforts to control air temperature, mostly from the late 19th century through the widespread deployment of modern AC.

The author appears to have read basically every primary source that either mentioned attempts to cool the air or the consequences of not doing so. This leads to some evocative images: many important events in the history of statecraft and the arts took place in poorly-ventilated rooms with lots of people; the Globe theater and the House of Representatives were both incredibly unpleasant places to be when the weather got warm. Sometimes, needlessly so: the House of Lords once installed a cooling system based on very hazy notions of hot air rising, causing air to circulate, which they implemented by installing ovens under the floor. It must have seemed like a good idea at the time, but it makes you feel for the unfortunate Lords who were being rotisseried in the service of cooling their building.

The book also has a story that's sure to warm the hearts of anarcho-capitalists everywhere: for a while in the late 19th century, the way newspapers reported on weather was that they checked a giant thermometer in front of a soda shop downtown. Using intellectual property without paying for it and a business that provided a public service entirely so it could sell more soda? It's like something out of a David Friedman thought experiment.

There were two related reasons that climate control took a while to get going. First, people didn't seriously consider the possibility that they could artificially lower the temperature, even though they were used to raising it during winter. Or, rather, different people in different places had come up with ways to make heat more tolerable, but couldn't imagine that you could impose mild autumn weather at will. And second, the richest and most technologically advanced countries in the early days of AC were also countries that had strong social norms against complaining about discomfort. If you weren't miserably boiling in your suit all summer, where would you draw the line? (In fact, many of the early ads for air conditioning and its predecessor technologies frame them as a solution to a different Victorian buggaboo: they were tools for getting pure air, with the cooling only incidental.)

So adoption of good AC was halting, and weird: it started being applied to some specialized industry use cases, like controlling the temperature of beer during the brewing process, or keeping cadavers nice and cool in medical schools (Cornell Medical College used to hold its graduation ceremony in the same room where students dissected corpses). It was big in theaters, where it made a play called Hazel Kirke one of the most popular in America in the 1880s (the plot of that play was so thin that when it was turned into a movie twice, one of the movies decided to change which love interest the heroine chose). It expanded into movie theaters and spread rapidly through trains in the 1930s. These public-facing early adopters seem a little odd, but it all makes sense when you realize that these are businesses that charge for admission rather than charging for a product as customers are leaving. They're the ones who can measure whether or not customers value air conditioning by seeing if they'll pay for it.

The rest of the deployment story is a classic general-purpose technology story: it started out being bought by specialized industrial users and rich, decadent hobbyists, but every iteration got cheaper, especially relative to other purchases it was associated with—in the postwar period, an AC system could be 20% of the cost of a new home, but systems got smaller and cheaper.

The air conditioner is a surprisingly consequential invention. It enhances the convexity of expertise if you can practice your craft year-round; it globalizes labor markets if every big city has the same climate once you're indoors. Cities like Dubai and Singapore are inconceivable without AC, and Austin and Atlanta would be a lot smaller in an AC-free world. Many people who would have died during heat waves got a few more years. All this should be a reminder of how much unmeasured wealth we have today. History was a sweatier, smellier, less comfortable environment than the one in which we live. Lucky us!

Open Thread

• Drop in any links or comments of interest to Diff readers.
• What are some good histories of particular product categories like this? This kind of book is very helpful because you'll go into it already having some preconceptions about the time period in question, and may well get the answer to a mystery that's been slightly bugging you since you read some historical anecdote.

Diff Jobs

Companies in the Diff network are actively looking for talent. See a sampling of current open roles below:

• High-growth startup building dev tools that help highly technical organizations autonomously test and debug complex codebases is looking for forward deployed engineers who want  to dive into customers’ complex software systems, find pressing business needs and deploy a cutting edge platform to help thoroughly test mission-critical applications. Experience with fuzzing or property-based testing a plus! (SF, London, D.C.)
• YC-backed, ex-Jane Street founder building the travel-agent for frequent-flyers that actually works (understands everything about you and automatically arranges your trip for you) is looking for a senior engineer to join as CTO. If you have shipped real, working applications and are passionate about using LLMs to solve for the nuanced, idiosyncratic travel preferences that current search tools can't handle, please reach out. (SF)
• A leading AI transformation & PE investment firm (think private equity meets Palantir) that’s been focused on investing in and transforming businesses with AI long before ChatGPT (100+ successful portfolio company AI transformations since 2019) is hiring experienced forward deployed AI engineers to design, implement, test, and maintain cutting edge AI products that solve complex problems in a variety of sector areas. If you have 3+ years of experience across the development lifecycle and enjoy working with clients to solve concrete problems please reach out. Experience managing engineering teams is a plus. (Remote)
• Series A startup that powers 2 of the 3 frontier labs’ coding agents with the highest quality SFT and RLVR data pipelines is looking for growth/ops folks to help customers improve the underlying intelligence and usefulness of their models by scaling data quality and quantity. If you read axRiv, but also love playing strategy games, this one is for you. (SF)
• Ex-Bridgewater, Worldcoin founders using LLMs to generate investment signals, systematize fundamental analysis, and power the superintelligence for investing are looking for machine learning and full-stack software engineers (Typescript/React + Python) who want to build highly-scalable infrastructure that enables previously impossible machine learning results. Experience with large scale data pipelines, applied machine learning, etc. preferred. If you’re a sharp generalist with strong technical skills, please reach out. (SF, NYC)

Even if you don't see an exact match for your skills and interests right now, we're happy to talk early so we can let you know if a good opportunity comes up.

If you’re at a company that's looking for talent, we should talk! Diff Jobs works with companies across fintech, hard tech, consumer software, enterprise software, and other areas—any company where finding unusually effective people is a top priority.