How does AI change the balance of power in content moderation & communication?

I wrote something on this (pre-OpenAI) with a simple prediction:

1. Where the ground truth is human judgment, AI favors defense.
2. Where the ground truth is facts in the world, AI favors offense.

A new post: On Deriving Things

(about the time spent back and forth between clipboard whiteboard blackboard & keyboard)

tecunningham.github.io/posts/2020-1...

When too much good news is bad news:

1. If an AB test shows an effect of +2% (±1%) it’s very persuasive, but if it shows a an effect of +50% (±1%) then the experiment was probably misconfigured, and it’s not at all persuasive.

New post: Thinking about tradeoffs? Draw an ellipse.

With applications to (1) experiment launch rules; (2) ranking weights in a recommender; and (3) allocating headcount in a company.

My daughter and I have an arrangement: She does whatever I ask her to do. In return I only ask her to do things that I know she's going to do anyway.

A long and partisan note about experiment interpretation based on experience at Meta and Twitter.

The common thread is that people are pretty good intuitive Bayesian reasoners, so just summarize the relevant evidence and let a human be the judge:

tecunningham.github.io/posts/2023-0...

I wrote a long blog post working through the different ways in which an AI trained to *imitate* humans could *outperform* humans: tecunningham.github.io/posts/2023-0...