Information Theory

Start with a prior; update with new evidence.

Small visible disorders signal that bigger ones will be tolerated.

Being visibly busy signals importance regardless of actual output.

Employers screen by school name, rewarding admission rather than developed skill.

Signals whose value depends on being expensive to fake.

Adding noise to data to protect individual privacy.

Systems tend toward disorder unless energy is invested to maintain order.

Average outcomes across the population differ from outcomes across time for one person.

Decisions optimize utility, not value.

Probability × payoff, summed across outcomes.

More homework signals rigor to parents but often produces burnout, not understanding.

Deliberately shaping how others perceive you — through behavior, signal, and context.

Without active design, incentives decay toward gameable proxies.

A pre-commitment to gatekeepers (curators, trusted reviewers, criteria) so the flood of content doesn't drown the signal.

Innovation programs designed to signal innovation, not to produce it.

Intuition is trustworthy only when the domain is regular, practice is plentiful, and feedback is fast.

As sample size grows, sample averages converge to expected values.

Insulation of neural pathways speeds signal transmission with practice.

The brain is a prediction engine; surprise is the signal to update.

We choose to minimize the regret we anticipate — not the expected value.

Maximizing the reward signal in unintended ways.

Preference for certain outcomes over uncertain ones of equal expected value.

The ratio of useful information to irrelevant information.

Costly actions that credibly communicate hard-to-observe traits.

Demand rises with price because the price itself signals status.

Source of dopamine signals projecting to reward and motivation circuits.

Buddhist-derived principle: applying the right amount of effort, neither forcing nor slacking — taught by Shauna Shapiro and Rick Hanson.

Prices & info guide attention