Preferential Engagement and What Can We Learn from Online Chess?
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Preferential Engagement and What Can We Learn from Online Chess? Vadim Kulikov1,2 Received: 27 October 2020 / Accepted: 3 November 2020 © The Author(s) 2020
Abstract An online game of chess against a human opponent appears to be indistinguishable from a game against a machine: both happen on the screen. Yet, people prefer to play chess against other people despite the fact that machines surpass people in skill. When the philosophers of 1970’s and 1980’s argued that computers will never surpass us in chess, perhaps their intuitions were rather saying “Computers will never be favored as opponents”? In this paper we analyse through the introduced concepts of psychological affordances and psychological interplay, what are the mechanisms that make a human-human (HH) interaction more meaningful than a human-computer (HC) interaction. We claim that an HH chess game consists of two intertwined, but independent simultaneous games—only one of which is retained in the HC game. To help with the analysis we introduce the thought experiment of a Preferential Engagement Test (PET) which is inspired by, but non-equivalent to, the Standard Turing Test. We also explore how the PET can illuminate, and be illuminated by, various philosophies of mind reading: Theory Theory, Simulation Theory and Mind Minding. We propose that our analysis along with the concept of PET could illuminate in a new way the conditions and challenges a machine (or its designers) must face before it can replace humans in a given occupation. Keywords Turing test · Chess · Mind reading · Affordances · Psychologicalinterplay · Theory theory · Simulation theory · Mind minding · Machine consciousness · Replacement of humans by machines
* Vadim Kulikov [email protected] 1
Faculty of Information Technology and Electrical Engineering, Center for Ubiquitous Computing, University of Oulu, Oulu, Finland
2
Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
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V. Kulikov
1 Introduction What are the conditions that a machine, or an artificial system must satisfy to replace humans in a particular occupation? Will computers ever replace humans in art, composing music, being mathematicians, or performing as rockstars? The general statement we want to defend in this paper is that there are situations in which computers cannot replace humans at all. This seems to be acute, because many thinkers today argue that the contrary is true. We do not claim that our defence is absolute, but we believe to have a novel point. This point might have other implications to philosophy of machine intelligence to be explored elsewhere. This novel point can be summarized as follows. Suppose a human H interacts with an entity X. The subjective situatedness of H depends on H’s knowledge of whether X is a human or not. If H knows that X is a human, this makes certain affordances available to H, which in turn enables H to exercise certain fine tuned skills which would not otherwise be used and remain idle. We will also show that acco
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