Affiliation:
1. Imperial College London Department of Computing London United Kingdom
Abstract
Abstract
In this paper, I attempt to address a fundamental challenge for machine intelligence: to understand whether and how a machine’s internal states and external outputs can exhibit original non-derivative intentionality. This question has three aspects. First, what does it take for a machine to exhibit original de dicto intentionality? Second, what does it take to exhibit original de re intentionality? Third, what is required for the machine to defer to the external objective world by respecting the word-to-world direction of fit? I attempt to answer the first challenge by providing a constitutive counts-as understanding of de dicto intentionality. This analysis involves repurposing Kant’s vision of a self-legislating agent as a specification of a machine that reprograms itself. I attempt to answer the second and third challenges by extending Kant’s synchronic model of de dicto intentionality with Brandom’s interpretation of Hegel’s diachronic model of de re intentionality, using Hegel’s notion of recollection to provide an understanding of what is involved in achieving deference to the external world.