Fred Dretske

(1932 - 2013)

This chapter separates cognition from perception by distinguishing between the percept—the product of pure perception which is conceptually untainted by cognitive ingredients—and a larger and more inclusive experience that is conceptually affected. It then criticizes Siegel’s view that higher-level properties are included in the content of perceptual experience, and the view that cognition affects the percept. The chapter uses a thought experiment, the ‘Goldilocks test’, to isolate cognitively unspoiled sensory core of perceptual experience. Application of the test to the perception of kinds yields the result that subjects who possess different concepts (expert and novice viewers) have the same percept. The chapter also applies the Goldilocks test to other visual cases, such as reversible figures.

It is a traditional empiricist doctrine that natural laws are universal truths. In order to overcome the obvious difficulties with this equation most empiricists qualify it by proposing to equate laws with universal truths that play a certain role, or have a certain function, within the larger scientific enterprise. This view is examined in detail and rejected; it fails to account for a variety of features that laws are acknowledged to have. An alternative view is advanced in which laws are expressed by singular statements of fact describing the relationship between universal properties and magnitudes.

Though one believes that P is true, one can have reasons for thinking it false. Yet, it seems that one cannot know that P is true and (still) have reasons for thinking it false. Why is this so? What feature of knowledge (or of reasons) precludes having reasons or evidence to believe (true) what you know to be false? If the connection between reasons (evidence) and what one believes is expressible as a probability relation, it would seem that the only satisfactory explanation of this fact is that when one knows that P is true, the reasons or evidence one has in support of P are such as to confer upon P the probability of 1. It is shown by an application of Bayes' Theorem that any value smaller than 1 would permit having reasons to believe what one knows to be false. Hence, it would seem that knowledge requires conclusive reasons to believe (if reasons or evidence is required at all)

Causal explanations of behavior must distinguish two kinds of cause. There are triggering causes, the events or conditions that come before the effect and are followed regularly by the effect, and structuring causes, events that cause a triggering cause to produce its effect. Moving the mouse is the triggering cause of cursor movement; hardware and programming conditions are the structuring causes of cursor movement. I use this distinction to show how representational facts can be structuring causes of behavior even though biological events trigger the behavior.