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Responsibility & Machine Learning: Part of a Process

20 Pages Posted: 28 Oct 2016  

Jatinder Singh

University of Cambridge - Computer Laboratory

Ian Walden

Queen Mary University of London, School of Law

Jon Crowcroft

University of Cambridge

Jean Bacon

University of Cambridge - Computer Laboratory

Date Written: October 27, 2016

Abstract

As machine learning (ML) becomes increasingly prevalent, concerns are mounting over its use. This discussion paper explores notions of responsibility with regard to ML, focusing on transparency and control. We recognise that such concerns extend beyond the ML technology itself, to the workflows and processes in which the ML operates, i.e. its potential impact. As such, it is important to consider not only the nature of machine learning techniques, but also the data involved and its fit within a broader process. Each of these aspects relate to responsibility, as they represent points for choice and intervention.

Keywords: machine learning, law, responsibility, data, workflow, processes, human in-the-loop, audit, compliance, computer science, work

Suggested Citation

Singh, Jatinder and Walden, Ian and Crowcroft, Jon and Bacon, Jean, Responsibility & Machine Learning: Part of a Process (October 27, 2016). Available at SSRN: https://ssrn.com/abstract=2860048 or http://dx.doi.org/10.2139/ssrn.2860048

Jatinder Singh (Contact Author)

University of Cambridge - Computer Laboratory ( email )

15 JJ Thomson Avenue
William Gates Building
Cambridge, CB3 0FD
United Kingdom

Ian Walden

Queen Mary University of London, School of Law ( email )

Mile End Road
London, London E1 4NS
United Kingdom

Jon Crowcroft

University of Cambridge ( email )

Trinity Ln
Cambridge, CB2 1TN
United Kingdom

Jean Bacon

University of Cambridge - Computer Laboratory ( email )

15 JJ Thomson Avenue
William Gates Building
Cambridge, CB3 0FD
United Kingdom

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