Modelling Qualia with Physical Computers

Frank Jackson's knowledge argument claims that Mary, who knows all physical facts while living in a black-and-white world, learns something new when she sees red, which would refute physicalism. However, physicalism can be preserved even if the argument is accepted. Physical computer systems with a specific structure and complexity cannot predict their own sensory information, creating decision-related unpredictability for certain types of sensory data. This analysis offers a physicalist and computationalist explanation of qualia, taking a charitable view of the concept.

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Abstract

According to Frank Jacksonʼs knowledge argument, Mary, who lives in a black-and-white world, has all the physical knowledge about the world, yet she has new information when she sees a red apple. If we accept this, then physicalism – according to which the description of the world can be realised entirely with the help of physical theories – is false. However, even if Jacksonʼs argument about new information is true, we do not have to discard physicalism. Even exclusively physical computer systems are not capable of predicting their own sensory information if they are built using a specific structure and complexity. It can be shown that a specific type of computational system can lead to the creation of decision-related unpredictability of a specific type of sensory information. This investigation takes a charitable position towards the concept of qualia to provide it with a physicalist and computationalist explanation.