Representationalists have routinely expressed skepticism about the idea that inflexible responses to stimuli are to be explained in representational terms. Representations are supposed to be more than just causal mediators in the chain of events stretching from stimulus to response, and it is difficult to see how the sensory states driving reflexes are doing more than playing the role of causal intermediaries. One popular strategy for distinguishing representations from mere causal mediators is to require that representations are decoupled from specific (...) stimulus conditions. I believe this requirement on representation is mistaken and at odds with explanatory practices in sensory ecology. Even when sensory states have the job of coordinating a specific output with a specific input, we can still find them doing the work of representations, carrying information needed for organisms to respond successfully to environmental conditions. We can uncover information at work by intervening specifically on the information conveyed by sensory states, leaving their causal role undisturbed. (shrink)

Proponents of the causal theory of perception have applied the theory to questions about which particular objects or events are perceived, which parts are perceived, and which properties are perceived. In each case they insist that successful perception is causally dependent on what is perceived. The causal theory rests on an important insight regarding the information-carrying role of perception. In order to succeed in this role, perception cannot be grounded in spurious correlations. But we can respect this insight without embracing (...) the idea that a successful percept must be causally dependent on what is perceived. A correlation in nature can also be genuine or lawful when it arises from a common cause. I show how successful perception is frequently achieved through correlation via a common cause. (shrink)

The received view holds that there is a significant divide between full-blown representational states and so called ‘detectors’, which are mechanisms set off by specific stimuli that trigger a particular effect. The main goal of this paper is to defend the idea that many detectors are genuine representations, a view that I call ‘Strong Liberal Representationalism’. More precisely, I argue that ascribing semantic properties to them contributes to an explanation of behavior, guides research in useful ways and can accommodate misrepresentation.