Tacit Representations and Artificial Intelligence: Hidden Lessons from an Embodied Perspective on Cognition

In Vincent Müller (ed.), Fundamental Issues of Artificial Intelligence. Springer. pp. 425-441 (2016)

Authors
Elena Spitzer
University of Wisconsin, Madison
Abstract
In this paper, I explore how an embodied perspective on cognition might inform research on artificial intelligence. Many embodied cognition theorists object to the central role that representations play on the traditional view of cognition. Based on these objections, it may seem that the lesson from embodied cognition is that AI should abandon representation as a central component of intelligence. However, I argue that the lesson from embodied cognition is actually that AI research should shift its focus from how to utilize explicit representations to how to create and use tacit representations. To develop this suggestion, I provide an overview of the commitments of the classical view and distinguish three critiques of the role that representations play in that view. I provide further exploration and defense of Daniel Dennett’s distinction between explicit and tacit representations. I argue that we should understand the embodied cognition approach using a framework that includes tacit representations. Given this perspective, I will explore some AI research areas that may be recommended by an embodied perspective on cognition.
Keywords embodied cognition  artificial intelligence  ai  representation
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Intelligence Without Representation.Rodney Brooks - 1991 - Artificial Intelligence 47 (1--3):139-159.
Semantic Conceptions of Information.Luciano Floridi - 2008 - Stanford Encyclopedia of Philosophy.
Reasons, Robots and the Extended Mind.Andy Clark - 2001 - Mind and Language 16 (2):121-145.

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