Friday, 12 November 2004
Ockham's Razor and the Highway to the Truth:
A Kinky Resolution of the Realism Debate
Kevin T. Kelly
Carnegie Mellon University
12:05 pm, 817R Cathedral of Learning
Abstract: Here is the crux of the debate concerning
scientific realism. When several, alternative theories fit the available
data, Ockham's razor enjoins you to choose the simplest. But how
could such a policy possibly help you find the truth? For Ockham's
razor is a fixed bias toward simplicity that can no more indicate
truth than a broken thermometer stuck on a particular reading can
indicate temperature. Standard responses either (1) beg the question
in favor of simplicity by assuming a prior probabilistic bias toward
simple worlds or (2) baitandswitch by substituting some extraneous
aim (e.g., testability, symmetry, predictive accuracy) for finding
the true theory.
The linchpin of the puzzle is the tacit premise
that Ockham's razor could only help you find the true theory by
indicating or pointing at it like a compass needle. But typical
advice for how to get somewhere isn't like that: it puts you on
the straightest (least kinky) route to your goal without necessarily
pointing at the goal. The best such advice may even point opposite
to the goal (e.g., if you have to backtrack a few blocks to get
on the freeway). I will argue that Ockham's advice works in a very
similar way. Indeed, I will prove that Ockham's razor is the unique
scientific strategy that minimizes contentlosing retractions or
scientific revolutions en route to the truth (in a precise, worstcase
sense). According to the demonstration, seeking simple theories
helps you find complex truths in much the same way that turning
away from your goal to get on the freeway helps you get there. So
Ockham's razor does help you find the truth in a strong and unique
sense, but it doesn't indicate the truth in the present since arbitrarily
many severe retractions may still await a retractionminimizing
scientist in the future (the problem of induction). This argument
vindicates both the realist's appeals to simplicity and the antirealist's
skeptical doubts. The approach is broadly applicable to statistical
model selection, to causal inference, to Goodman's riddle, and even
to purely formal problems in computability theory.
The talk is selfcontained and is aimed at a general
philosophical and scientific audience. Animated diagrams illustrate
the several novel concepts involved.
