A Stark Warning From a Former AI Doomer

Tesla’s recent demo of a rocket-powered Roadster doing a kick-flick over a parked car touched a nerve in me. It seemed to epitomize changes to the tech sector in recent years that have been largely negative. In this short episode, I jump on the mic to explain some of my developing thoughts surrounding these ideas.

A lot of attention has been paid recently to examples of AI going “rogue.” What’s missing from this discussion, however, is a more detailed explanation of what specific types of systems are causing problems. Taking a closer look at this problem reveals an issue that’s much more narrow and much more avoidable than some of the frontier labs would like you to believe.

How do we stop from becoming so reliant on LLMs that we lose our ability to think. A new paper explores answers based on an unlikely source: rigorous mathematical models. In this episode, Cal explains the paper and its conclusions, arguing that once you cut through its complexity it yields a useful way of thinking about our current AI moment.

One of the more debilitating experiences in our current digital world is the sense of being trapped in relentless, reactive, busyness. This “whirlwind” can separate you from both ambition and presence, leaving you feeling flat and fried. In this episode, Cal discusses a simple trick he deploys when he finds himself in this state. It requires only a single sheet of paper.

The conversation around AI harms has become incredibly heated in recent weeks. But it's also incredibly confusing. In this short explainer episode, Cal walks through the three major categories of beliefs around AI in the current moment and helps explain who belongs where and how they all relate to each other. If you're trying to keep up with AI news you have need to learn this framework.