Forecasting

When too much experience is bad

There’s a stable, robust relationship between the patterns you’ve seen before and what you encounter today. But if you’re a stockbroker or political forecaster, the events of the past don’t have reliable implications for the present. However, experience helps physicists, accountants, insurance analysts, and chess masters—they all work in fields where cause-and-effect relationships are fairly consistent. But admissions officers, court judges, intelligence analysts, psychiatrists, and stockbrokers don’t benefit much from experience.

Skilled intuition

Intuition from an "expert" may be valid or not, depending on the situation available to create it. intuition cannot be trusted in the absence of stable regularities in the environment. There must be:

  • an environment that is sufficiently regular to be predictable
  • an opportunity to learn these regularities through prolonged practice

examples

  • Regular environment
    • chess, doctor, athletes, firefighters
  • Irrregluar environment
    • stock pickers, political scientists, therapists

Whether professionals have a chance to develop intuitive expertise depends essentially on the quality and speed of feedback

An experienced psychotherapist knows that she is skilled in working out what is going on in her patient’s mind and that she has good intuitions about what the patient will say next. It is tempting for her to conclude that she can also anticipate how well the patient will do next year, but this conclusion is not equally justified. Short-term anticipation and long-term forecasting are different tasks, and the therapist has had adequate opportunity to learn one but not the other.

Assessing impact of new technologies

when a new technology emerges we either grossly overestimate or underestimate its impact

  • ex. bell labs satellite dish discovery of big bang
  • ex. discovery of penicillin
  • ex. discovery of evolution

rarely do these discoveries have massive imapct that we might think they'd have. the takeaway is that when we see a new innovation that we might think would have such a massive impact, odds are against that outcome. its more likely that the impact wont be nearly as big (or in the case of something like the iphone, much bigger than we originally thought)

  • this goes to show that even if a new technology has come out (or is in the process of being developed), we still cannot predict them. they are properly black swan events in that sense