Saturday, February 6, 2021

Jacob Feldman, Bayesian inference and “truth”: a comment on Hoffman, Singh, and Prakash.

   

Jacob Feldman:  “On that narrow question, it seems to me that Hoffman et al.’s position cannot be disputed: evolution favors fitness, not truth, beauty, or anything else except insofar as it is correlated with fitness. 

This is literally tautological in the context of Darwinian evolution, as it is essentially a restatement of what is meant by “fitness”—that which is favored by adaptive pressure. …”

©2020 Peter Miesler - ashes to ashes, dust to dust


Jacob Feldman,  Professor of Psychology and Cognitive Science at Rutgers, focuses on Hoffman's “truth,” and it sure seems like he's agreeing with my layperson assessment that Hoffman's "truth" in ITP is a deception.  I encourage you to see if you agree with my assessment of Feldman's short paper “Bayesian inference and “truth”: a comment on Hoffman, Singh, and Prakash,” the original comes in at 1800 words, and here I’ve trimmed it to 500 words worth of highlights that I hope encourage you to read Professor Heldman's entire paper.


Bayesian inference and “truth”: a comment on Hoffman, Singh, and Prakash

volume 22, pages 1523–1525 (2015),  September 18, 2015



Abstract

Hoffman, Singh, and Prakash (in press) argue that veridicality is neither required nor achieved by the visual system, and propose a new framework in which the literal truth of perceptual inferences plays no role. In this brief comment, I concur with and advocate their basic position, though I go on to argue that Bayesian inference already embodies a similar epistemological stance.

That “vision usually provides us with a veridical representation of the world” is a cliche so hoary that we vision scientists hardly stop to think about whether it is actually true. 

Hoffman et al. (in press) ask us to consider it a bit more carefully. Could such a truism actually be wrong?

It’s worse than wrong—it’s meaningless.

… Certainly, as Hoffman et al. would agree, the visual system does an exemplary job at resolving the ambiguity. But does it do so by giving us something true, or simply something useful? Or is this a distinction without a difference?

On that narrow question, it seems to me that Hoffman et al.’s position cannot be disputed: evolution favors fitness, not truth, beauty, or anything else except insofar as it is correlated with fitness. 

This is literally tautological in the context of Darwinian evolution, as it is essentially a restatement of what is meant by “fitness”—that which is favored by adaptive pressure. So Hoffman et al.’s basic conclusion is inescapable: evolution optimizes fitness, by definition.

The more difficult question is whether true beliefs tend to facilitate fitness. 

Hoffman et al. give somewhat short shrift to this question, setting up artificial games in which truth and fitness are decorrelated. The result—inevitably—is that fitness wins. Truth is irrelevant. …


Footnotes

1 … As scientists, we must ask whether the presumption of veridicality can be defended in more rigorous terms.

In my view, there is no scientific basis for it, and moreover it does not, by itself, really mean anything. To see why, notice that the idea of veridical perception hinges on a presupposition that perceptual judgments per se have truth values—that is, that they can literally match, or fail to match, real-world measurements. But what exactly does this mean?

2 … (see Feldman, 2014). The “truth” of the models (whatever that even means) never enters into it.

3 None of the hypotheses under consideration needs to be literally true for the process of Bayesian inference to be useful or coherent, … In other words, Bayesian inference does not require—nor, indeed, in any way involve—the literal truth of any hypotheses. All that is needed is that selection of hypotheses guide action “effectively.” 

And effectiveness, as Hoffman et al. argue, really means fitness. 

Veridicality is a red herring.


  • 1.
    ..evolutionary fitness is proportional to payoff, which Geisler and Diehl (2002) assume in their simulations.

    2.
    … see Feldman (2013).

    3.
    From Box and Tiao (1973) (p24): “The only realistic expectation from a statistical analysis is that the conclusions will provide a good enough approximation to the truth.” Good enough, that is, to guide action effectively.

(Link to the complete paper here.)

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