University of Oulu

Kulikov, V. Preferential Engagement and What Can We Learn from Online Chess?. Minds & Machines 30, 617–636 (2020). https://doi.org/10.1007/s11023-020-09550-7

Preferential engagement and what can we learn from online chess?

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Author: Kulikov, Vadim1,2
Organizations: 1Faculty of Information Technology and Electrical Engineering, Center for Ubiquitous Computing, University of Oulu, Oulu, Finland
2Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.1 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202102195383
Language: English
Published: Springer Nature, 2020
Publish Date: 2021-02-19
Description:

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.

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Series: Minds and machines
ISSN: 0924-6495
ISSN-E: 1572-8641
ISSN-L: 0924-6495
Volume: 30
Issue: 4; SI
Pages: 617 - 636
DOI: 10.1007/s11023-020-09550-7
OADOI: https://oadoi.org/10.1007/s11023-020-09550-7
Type of Publication: A1 Journal article – refereed
Field of Science: 111 Mathematics
Subjects:
Funding: This research has been partly supported by the PERCEPT project (322637) funded by the Academy of Finland and the HUMOR project (3656/31/2019) funded by Business Finland and industry.
Academy of Finland Grant Number: 322637
Detailed Information: 322637 (Academy of Finland Funding decision)
Copyright information: © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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