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Machine-Learnt Bias? Algorithmic Decision Making and Access to Criminal Justice

Overall Winner, Justis International Law & Technology Writing Competition 2020, by Malwina Anna Wojcik of the University of Bologna

Published online by Cambridge University Press:  16 September 2020

Malwina Anna Wojcik
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Extract

The pressure on the criminal justice system in England and Wales is mounting. Recent figures reveal that despite a rise in recorded crime, the number of defendants in court proceedings has been the lowest in 50 years. This indicates a crisis of access to criminal justice. Predictive policing and risk assessment programmes based on algorithmic decision making (ADM) offer a prospect of increasing efficiency of law enforcement, eliminating delays and cutting the costs. These technologies are already used in the UK for crime-mapping and facilitating decisions regarding prosecution of arrested individuals. In the US their deployment is much wider, covering also sentencing and parole applications.

Type
Shorter Articles
Information
Legal Information Management , Volume 20 , Issue 2 , June 2020 , pp. 99 - 100
Copyright
Copyright © The Author(s) 2020. Published by British and Irish Association of Law Librarians

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References

Footnotes

1 ‘Numbers dealt with in justice system at 50-year low’ (The Times, 15 November 2019), <https://www.thetimes.co.uk/article/numbers-dealt-with-in-justice-system-at-50-year-low-k5hnb50kd> accessed 15 November 2019.

2 For example: PredPol used by Kent Police between 2013 and 2018 or MapInfo used by West Midlands Police.

3 For example: Harm Assessment Risk Tool (HART). See: The Law Society Commission on the Use of Algorithms in the Justice System, Algorithms in the Criminal Justice System (June 2019) para 7.3.1.

4 For example: Correctional Offender Management Profiling for Alternative Sanctions (COMPAS). See: ‘Practitioner's Guide to COMPAS Core’ (Equivant 2019) < http://www.equivant.com/wp-content/uploads/Practitioners-Guide-to-COMPAS-Core-040419.pdf> accessed 15 November 2019.

5 J Kleinberg et al, ‘Human Decisions and Machine Predictions. (2018) Quarterly Journal of Economics 133, 237.

6 J Buolamwini, ‘Compassion through Computation: Fighting Algorithmic Bias’ (speech at the 2019 World Economic Forum in Davos) <https://www.youtube.com/watch?v=_sgji-Bladk> accessed 15 November 2019.

7 Chiao, V, ‘Fairness, Accountability and Transparency: Notes on Algorithmic Decision-making in Criminal Justice’ (2019) 15 International Journal of Law in Context 126CrossRefGoogle Scholar, 127.

8 J Angwin et al, 2016, ‘Machine Bias’ (ProPublica, 23 May 2016) <https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing> accessed 15 November 2019.

9 H Couchman, ‘Policing by Machine. Predictive Policing and the Threat to our Rights’ (Liberty, January 2019) 15.

10 Art. 5(1)(c) ECHR.

11 The European Parliament Research Service, Understanding algorithmic decision-making: Opportunities and challenges (March 2019) 46.

12 ibid 55.

13 Chiao (n 7) 129.

14 The Law Society Commission (n 3) para 8.4.

15 R Feloni, ‘An MIT Researcher who Analyzed Facial Recognition Software Found Eliminating Bias in AI is a Matter of Priorities’ (Business Insider, 23 January 2019) < https://www.businessinsider.sg/biases-ethics-facial-recognition-ai-mit-joy-buolamwini-2019-1/> accessed 15 November 2019.

16 The Law Society Commission (n 3) para 8.2, sub-recommendation 4.3.

17 ibid para 8.3, sub-recommendation 1.7.

18 ibid para 8.4, sub-recommendation 3.1.

19 ibid para 8.3, sub-recommendation 4.4.