Navigating the crazy AI world

There is an irresolvable tension between the practice of predicting human behavior and the belief in free will as part of our everyday life. A healthy degree of uncertainty about what is to come motivates us to want to do better, and it keeps possibilities open. The desire to leave no potential data point uncollected with the objective of mapping o... See more

I have elsewhere called these artificial intelligence systems “ looms ,” and I think they are best understood as external attention systems —just as writing can be called an external memory system. Recommendation engines, predictive feeds, and language models perform the various functions of attention: filtering, noticing, selecting what matters fr... See more

Productive friction has three main principles:

1. Immediate feedback: You understand when you've failed and can see why.


2. Cumulative learning: Each attempt builds your reference library.


3. Transferable principles: The specific teaches the general.

The most valuable resource isn’t algorithms, compute, or even just data. It’s context: the mosaic of real-time signals, history, recent mood shifts, stray calendar invites, and the live-wire pattern that is “you, right now.”

More than misinformation alone, chatbots adapt to individual users’ desires, building relational authority over time. Anthropomorphism, not intelligence, is AI’s killer feature.

To shape the inputs, and to evaluate outputs, you still need expertise.

Maps are built through curiosity and they shape our perception of the landscape through curation. But judgment helps apply them in ways that alter what an organization can perceive and act on.