Longreads + Open Thread

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Longreads

• Jeffrey Flier on how GLP-1 drugs were being developed in the 80s, and were then abandoned for decades. It's always hard to know how to react to a piece like this, because in terms of quality-adjusted life years it's a bit like reading about someone who pressed the wrong button and detonated a nuclear weapon. Errors of omission are less dramatic, but they're still a big deal. The underlying reason for this actually made a certain amount of sense: Pfizer was worried that an injectable treatment for diabetes and obesity would be a hard sell, given that insulin had a similar delivery mechanism and was a well-established category. Everyone operates under conditions of uncertainty, and in pharmaceuticals there are high costs to determining whether or not a drug is viable. But at the time that this project was canceled, the US obesity rate was in the low 20s, and it's now in the low 40s—a great deal of suffering could have been avoided if Pfizer had made a different decision. (As with other retrospectives on why someone missed out on a major accomplishment, you should assume that there's another side to the story and that there might have been more defensible reasons for thinking, circa 1990, that GLP-1s were not going to be economically significant any time soon.)
• Timothy B. Lee on differential privacy, and how the US census claims a house has nine imaginary inhabitants. There's a data/privacy tradeoff that gets discussed a lot in the context of targeted ads, but that also matters with publicly-available data. Every ten years, the US counts up the number of people who live here at great expense and makes data about them widely available. But that information can be deanonymized, at least partially, and at some point the risk of deanonymization means that people are incentivized not to tell the truth. The compromise is to add a bit of randomness to the data, so the aggregates are still true but narrow slices are not (in ads, this can take the form of not allowing people to target audiences so narrow that they're clearly intended for a single person. Of course, that can't truly be avoided: visit an airport in Washington, D.C. and you'll walk past at least a few ads whose target audience is small enough to fit in a conference room. Specifically a conference room at the Pentagon where the topic being conferred upon is which missile to buy).
• In 1999, Paul Seabright wrote a negative review of Seeing Like a State, a book that's now part of the default tech canon and that's also a running theme in The Diff. (See, for example, Big Tech Sees Like a State.) The main argument against the book is that, while it's true that some attempts to systematize and organize the world go badly, the modern world is both a lot more legible to big government and big business and a whole lot wealthier and more pleasant than it otherwise would be. That's the central tension in lots of Seeing Like a State discourse: the fundamental ideology of the book is basically anarcho-reactionary—pining for decentralized, illegible systems like feudalism over boring organized ones like social democracy or free-market capitalism.
• In Harpers, Jasper Craven goes undercover as a security guard. This article is partly a history of the mostly low-stakes private security industry, where the security guard is closer to a scarecrow than to a Wagner Group fighter. But it's also a fun story of culture shock, where a well-educated writer spends a lot of quality time with The Median Voter, someone with strong but mostly uninformed opinions on a wide variety of topics, and a weak model of how the world actually works. So maybe the real takeaway is that being immune to conspiracy theories, or knowing that security guards are a light deterrent for shoplifters and not potential action movie heroes, is no obstacle to holding down a job and being a basically functional member of society.
• Grant Stoner in IGN tells the story of a series of very sympathetic disability advocates in video games who might all have been the fictional creations of someone else. In any environment where identities are cheap, it's cheap to try new ones out, and sometimes the same work output has a bigger impact when it has a more sympathetic backstory. The most unfortunate feature of this is that if that's true, it's true because audiences feel like they have a genuine relationship with the person they're reading, and it's doubly harmful to use that to take advantage of them.
• In this week's episode of The Riff, we talk about the tech canon, smart contracts, carry trades, and more. Listen with Twitter/Spotify/Apple/YouTube.
• And in Capital Gains, we cover buybacks, and why they're simply not that alarming either compared to other forms of capital return or to other things companies might do with their money.

Books

Barbarians at the Gate is justifiably considered a classic of business writing. It's the story of the 1988 fight to acquire RJR Nabisco, so at one level it's a series of business questions: how much cash flow does this particular food and tobacco conglomerate generate, how fast does that grow, and how much could you get away with borrowing against it? Those business questions end up functioning more as scenery and context for a broader story about human failings, miscommunications, petty drama, and the winner's curse.

A surprising number of the key plot points revolve around miscommunications: the drama starts when RJR's CEO, Ross Johnson, puts together a deal to take the company private at $75/share, after it had been trading in the 40s. This was a nice premium, but below what the stock could ultimately support. Henry Kravis at KKR had talked to Johnson about doing exactly this kind of transaction over the years, and was miffed that he hadn't been included in the deal. And, in the course of asking around about it, heard something that indicated to him that the RJR buyout team was being unusually aggressive, as if they thought their offer was cheap but wanted to box other bidders out of the deal. (Specifically: there were a handful of large banks that dominated the business of lending to LBOs, and these banks were happy to offer their services to multiple competing bidders. Kravis thought one of them indicated that his bank was under an exclusivity agreement, which turned out to be untrue—a bit of confusion that wasn't resolved until KKR put in its own bid at $90.)

The story goes through a number of meandering, Shakespearean turns, as different sides debate over whether they're opponents or ought to join forces. The latter comes close to happening, but in the end a joint KKR/management bid gets blown up over the ridiculously petty question of which investment bank gets its name placed most prominently in the deal announcement. Most of the time, having more specific terms that are open to negotiation means that it's easier for two sides to hammer out a deal, since each one probably values different things. But with enough egos involved, it's the opposite: more points to negotiate on means more opportunities for two sides to each insist on getting something only one of them can get. In this case, Salomon didn't want to do a bond offering if Drexel was listed as the lead underwriter, and Drexel didn't want to do an offering where it wasn't. As it turns out Salomon did not particularly need to worry about Drexel getting the better brand placement, given that within two years Drexel would be bankrupt.

As a general rule, you don't want to be the main character in someone's career-making book about business. There's just a lot more excitement in ultimately bad deals involving dysfunctional organizations and pointless infighting. It probably did make sense for RJR to spend some time outside of private markets: a tobacco executive's incentive is to acquire food stocks to make their stock less depressing to evaluate—when you're weighing cash flow against cancer, you tend to get to grim results. But the incentive for an owner is to just say that a cigarette company sells cigarettes, it makes a lot of money but it'll taint anything else it's involved in. That's the kind of cold-blooded calculation that leveraged buyouts are supposed to encourage, but they're executed by warm-blooded people who react to more than just net present value calculations.

Open Thread

• Drop in any links or comments of interest to Diff readers.
• What's new and interesting in the world of using AI as a better interface for messy, data-intensive real-world problems?

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