Trusting Intelligent Machines: Deepening Trust Within Socio-Technical Systems

Andras, Peter; Esterle, Lukas; Guckert, Michael; Anh Han, The; Lewis, Peter R.; Milanovic, Kristina; Payne, Terry; Perret, Cedric; Pitt, Jeremy; Powers, Simon T.; Urquhart, Neil; Wells, Simon

Abstract

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?

Citation

Andras, P., Esterle, L., Guckert, M., Anh Han, T., Lewis, P. R., Milanovic, K., …Wells, S. (2018). Trusting Intelligent Machines: Deepening Trust Within Socio-Technical Systems. IEEE technology & society magazine, 37(4), 76-83. https://doi.org/10.1109/MTS.2018.2876107

• Journal Article Type: Article
• Acceptance Date: Sep 27, 2018
• Online Publication Date: Dec 4, 2018
• Publication Date: 2018-12
• Deposit Date: Nov 12, 2018
• Publicly Available Date: Nov 13, 2018
• Journal: IEEE technology & society magazine
• Print ISSN: 0278-0097
• Electronic ISSN: 1937-416X
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 37
• Issue: 4
• Pages: 76-83
• DOI: https://doi.org/10.1109/MTS.2018.2876107
• Public URL: http://researchrepository.napier.ac.uk/Output/1308130