Chapter 7: A Machine for Jumping to Conclusions
“Jumping to conclusions is efficient if the conclusions are likely to be correct and the costs of an occasional mistake acceptable, and if the jump saves much time and effort.”
S1 can generate its own context in the absence of an explicit one, and when uncertain, it bets (guided by experience) on an answer.
Daniel Gilbert (“How Mental Systems Believe”)
- Understanding a statement must begin with an attempt to believe it.
- “When S2 is otherwise engaged, we will believe almost anything. S1 is gullible and biased to believe, S2 is in charge of doubting and unbelieving, but S2 is sometimes busy and often lazy.
Positive Test Strategy: a deliberate search for confirming evidence.
Exaggerated Emotional Coherence (Halo Effect)
- The tendency to like (or dislike) everything about a person, including things you have not observed.
- This is an example of suppressed ambiguity.
- Sequence matters (first impressions)
- To tame it: decorrelate error! (James Surowiecki, The Wisdom of Crowds)
What You See Is All There Is (WYSIATI)
- “An essential design feature of the associative machine is that it represents only activated ideas. Information that is not retrieved (even unconsciously) from memory might as well not exist.”
- S1 is radically insensitive to both the quality and the quantity of the information that gives rise to impressions and intuitions.”
- “It is the consistency of the information that matters for a good story, not its completeness.” (Gödel?)
- It facilitates the achievement of coherence and of the cognitive ease that causes us to accept a statement as true. It explains why we can think fast, and how we are able to make sense of partial information in a complex world.
Biases of Judgments and Choice
1. Overconfidence
2. Framing effects (different ways of presenting the same information often evoke different emotions.)
3. Base-rate neglect