Trusting Intelligent Machines: Deepening Trust Within Socio-Technical Systems


Intelligent machines have reached capabilities that go beyond a level that a human being can fully comprehend without sufficiently detailed understanding of the underlying mechanisms. The choice of moves in the game Go (generated by Deep Mind?s Alpha Go Zero [1]) are an impressive example of an artificial intelligence system calculating results that even a human expert for the game can hardly retrace [2]. But this is, quite literally, a toy example. In reality, intelligent algorithms are encroaching more and more into our everyday lives, be it through algorithms that recommend products for us to buy, or whole systems such as driverless vehicles. We are delegating ever more aspects of our daily routines to machines, and this trend looks set to continue in the future. Indeed, continued economic growth is set to depend on it. The nature of human-computer interaction in the world that the digital transformation is creating will require (mutual) trust between humans and intelligent, or seemingly intelligent, machines. But what does it mean to trust an intelligent machine? How can trust be established between human societies and intelligent machines?

Publication DOI:
Divisions: College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
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Publication ISSN: 0278-0097
Last Modified: 13 May 2024 07:22
Date Deposited: 07 Dec 2018 09:57
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Related URLs: https://ieeexpl ... cument/8558724/ (Publisher URL)
PURE Output Type: Article
Published Date: 2018-12-04
Published Online Date: 2018-11-30
Accepted Date: 2018-11-01
Authors: Andras, Peter
Esterle, Lukas (ORCID Profile 0000-0002-0248-1552)
Guckert, Michael
Han, The Anh
Lewis, Peter R. (ORCID Profile 0000-0003-4271-8611)
Milanovic, Kristina
Payne, Terry
Perret, Cedric
Pitt, Jeremy
Powers, Simon T.
Urquhart, Neil
Wells, Simon



Version: Accepted Version

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