Big data and the reference class problem: what can we legitimately infer about individuals?

Greene, Catherine (2019) Big data and the reference class problem: what can we legitimately infer about individuals? In: Computer Ethics - Philosophical Enquiry (CEPE) Proceedings. Old Dominion University, Norfolk, VA.

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Abstract

Big data increasingly enables prediction of the behaviour and characteristics of individuals. This is ethically concerning on privacy grounds. However, this article discusses other reasons for concern. These predictions usually rely on generalisations about what certain sorts of people tend to do. Generalisations of this sort are often under scrutiny in legal cases, where, for example, lawyers argue that people with prior convictions are more likely to be guilty of the crime they are currently on trial for. This article applies criteria for distinguishing acceptable from unacceptable generalisations in legal cases to a number of big data examples. It argues that these criteria are helpful, and highlight three issues that should be taken into account when deciding whether predictions about individuals are ethical.

Item Type:	Book Section
Official URL:	https://digitalcommons.odu.edu/cepe_proceedings/
Additional Information:	© 2019 The Author
Divisions:	Philosophy, Logic and Scientific Method
Subjects:	B Philosophy. Psychology. Religion > BJ Ethics T Technology > T Technology (General) Q Science > QA Mathematics > QA76 Computer software
Date Deposited:	02 Aug 2019 13:15
Last Modified:	13 Sep 2024 23:34
URI:	http://eprints.lse.ac.uk/id/eprint/101290

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