Risk-Adjusted Return

The Editors

What are we afraid of?

Risk has always been a preoccupation of ours. (It is, literally, in our name.) Our first editorial observed that our lives were “getting stranger and harder to predict by the minute." Three years later, things don't exactly look more predictable. Unfortunately, we live in interesting times. 

Asterisk readers are already extremely well-informed, so we don't need to contribute to your regular doomscroll on escalating AI capabilities or the war with Iran. Instead, we wanted to take a step back and look at the concept of risk itself — where it comes from, how we think about it, and what it's like to live with it. 

It was in the 18th century that mathematicians began to quantify and calculate risk. Prussian military officers were quick to put this work to a very important purpose: games. Jon Peterson, an authority on all things wargaming, walks us from the first Kriegsspiel to the RAND's Cold War diplomacy simulations to the birth of Dungeons & Dragons. 

There exists a long history of using wargames to model the effects of new technology. Ajeya Cotra and Timothy B. Lee take on the question directly: How long do we have until AI systems are materially self-sufficient? Ajeya thinks we're likely to see fully automated AI supply chains within a decade. Tim is skeptical. (We saw them debate the issue on Twitter and knew it needed about 5,000 more words.)

Other pieces take a more personal approach to risk. You may have heard that Zoomers are the most risk-averse generation on record, too afraid to date or even leave their bedrooms — unless they're compulsive gamblers whose nihilism and disregard for the future drives them to risk it all on sports betting and crypto. We enlisted the distressingly youthful editors of The New Critic to consider the situation. 

Have you or a loved one experimented with unlicensed research peptides? Elizabeth Van Nostrand thinks you're not crazy after all. She reached out to the health hackers to understand how they think about using themselves as test subjects, and found more empiricism and a lot less YOLOing than popular peptide coverage might lead you to believe.

Our resident rat-whisperer Ozy Brennan talked to a group with a much less sanguine outlook on their personal well-being: AI doomers. The people who believe that our species only has a few years left to live are — for the most part — surprisingly well-adjusted. What helps them stay sane? 

A spoiler: For some, it's trying to make better predictions about how the technology will evolve.  Can markets help? For decades, prediction market advocates have promised that real money — and lots of it — was the key to accurate forecasts. Now real-money markets are here, — but has all that cash made them better at predicting the questions we care about? Dan Schwarz, an industry veteran, crunches the numbers to find out. 

Meanwhile, inveterate blogger Dynomight investigates a risk you almost certainly have in your medicine cabinet, historian Dan Bouk explains the political battles that shaped how engineers forecast certain lives, and Lennart Finke takes aim at the RCT in favor of observational data. 

Other dangers pose more profound measurement problems. Today, the number of armed conflicts is the highest it has been since World War II. Josh Martin argues that this violence is not inevitable: With new empirical tools, we can start to understand what causes conflict to erupt, and the most cost-effective methods to prevent it. 

Finally, Leah Libresco looks at financial risk – or rather, the ways that financial markets conceal risk from us and why we should thank them for it. 

We won’t conceal any risk from you at Asterisk, but nor are we in the game of trying to make you panic. (We have better ways of holding your attention). Stay calm, and keep reading,

– Clara & Angela