Bayesianism versus Critical Rationalism

Jayson_Virissimo

I have just rediscovered an article by Max Albert on my hard drive which I never got around to reading that might interest others on Less Wrong. You can find the article here. It is an argument against Bayesianism and for Critical Rationalism (of Karl Popper fame).

Abstract:

Economists claim that principles of rationality are normative principles. Nevertheless,
they go on to explain why it is in a person’s own interest to be rational. If this were true,
being rational itself would be a means to an end, and rationality could be interpreted in
a non-normative or naturalistic way. The alternative is not attractive: if the only argument
in favor of principles of rationality were their intrinsic appeal, a commitment to
rationality would be irrational, making the notion of rationality self-defeating. A comprehensive
conception of rationality should recommend itself: it should be rational to be
rational. Moreover, since rational action requires rational beliefs concerning means-ends
relations, a naturalistic conception of rationality has to cover rational belief formation including
the belief that it is rational to be rational. The paper considers four conceptions
of rationality and asks whether they can deliver the goods: Bayesianism, perfect rationality
(just in case that it differs from Bayesianism), ecological rationality (as a version of
bounded rationality), and critical rationality, the conception of rationality characterizing
critical rationalism.

Any thoughts?

Abstract:

Economists claim that principles of rationality are normative principles. Nevertheless,
they go on to explain why it is in a person’s own interest to be rational. If this were true,
being rational itself would be a means to an end, and rationality could be interpreted in
a non-normative or naturalistic way. The alternative is not attractive: if the only argument
in favor of principles of rationality were their intrinsic appeal, a commitment to
rationality would be irrational, making the notion of rationality self-defeating. A comprehensive
conception of rationality should recommend itself: it should be rational to be
rational. Moreover, since rational action requires rational beliefs concerning means-ends
relations, a naturalistic conception of rationality has to cover rational belief formation including
the belief that it is rational to be rational. The paper considers four conceptions
of rationality and asks whether they can deliver the goods: Bayesianism, perfect rationality
(just in case that it differs from Bayesianism), ecological rationality (as a version of
bounded rationality), and critical rationality, the conception of rationality characterizing
critical rationalism.

Any thoughts?

Because you are an empiricist, you relegate criticism to a minor role when in fact criticism is a major driving force in science.

Checking with the definition that apparently boils down to whether I think there is much innate knowledge. Humans have some innate knowledge, so I figure: probably not an empiricist.

I have no particular beef with criticism. Solomonoff induction is not given as a model of how humans actually do science. It is given as a formalisation of the maths of induction.

And how is the algorithm supposed to work anyway? If the theory is non-empirical, it can't be a compression of an empirical dataset.

Theories are constructed from datasets. Solomonoff induction is an abstract model of sequence prediction. Given a serial stream of sense data, it maintains models of it, and uses those models to predict future observations. The models embody theories about what it being observed - and smaller models are preferred.

Solomonoff Induction is empiricist because it assumes all knowledge comes from the data. Theories arising from Solomonoff Induction are, at most, only as reliable as the data and it can't come up with theories that make more precise predictions than the data or that contain more knowledge than the data. This is complicated by the fact that in real life applications it will have to deal with noise in the data and this is going to get deeply subjective very quickly.

Another problem is: how is the dataset itself constructed? You don't just go out and collect d... (read more)

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