Building Trust in Human-Machine Partnerships. Issue 39 (November 2020)

• Record Type: Journal Article
• Authors: Canal, Gerard; Borgo, Rita; Coles, Andrew; Drake, Archie; Huynh, Dong; Keller, Perry; Krivić, Senka; Luff, Paul; Mahesar, Quratul-ain; Moreau, Luc; Parsons, Simon; Patel, Menisha; Sklar, Elizabeth I
• Is Part Of: Computer law & security review. Issue 39(2020)
• Publication Date: 2020-11
• Subjects: Artificial intelligence -- explainable ai -- planning; Computers -- Law and legislation -- Periodicals; Computer security -- Law and legislation -- Periodicals; Electronic commerce -- Law and legislation -- Periodicals; Data protection -- Law and legislation -- Periodicals; Computer security -- Law and legislation; Computers -- Law and legislation; Data protection -- Law and legislation; Electronic commerce -- Law and legislation; Periodicals; 343.0999
• DOI: 10.1016/j.clsr.2020.105489
• Languages: English
• ISSNs: 2212-473X

Abstract

Abstract: Artificial intelligence (ai ) is bringing radical change to our lives. Fostering trust in this technology requires the technology to be transparent, and one route to transparency is to make the decisions that are reached by ai s explainable to the humans that interact with them. This paper lays out an exploratory approach to developing explainability and trust, describing the specific technologies that we are adopting, the social and organizational context in which we are working, and some of the challenges that we are addressing.