Ihaka Lecture Series | Three | Algorithmic fairness: Examples from predictive models for criminal justice Event as iCalendar

27 March 2019

6:30pm

Venue: Lecture Theatre PLT1, Ground Floor, Building 303, 38 Princes Street, City Campus

Location: Please join us for refreshments from 6pm outside the lecture theatre

Host: Department of Statistics

Cost: Free - all welcome

Dr Kristian Lum, Human Rights Data Analysis Group (HRDAG) Ihaka Lecture Series 2019 speaker
Dr Kristian Lum

Predictive models are increasingly used in the criminal justice system to predict who will commit crime in the future and where crimes will occur.

Because decisions influenced by models in this setting impact individuals’ liberty, it is of the utmost importance that predictions generated by the models be ‘fair’.

Using examples from predictive policing and recidivism risk assessment, Dr Kristian Lum will demonstrate how – if considerations of fairness and bias are not explicitly accounted for – such models could perpetuate and, under some circumstances, amplify undesirable historical biases encoded in the data.

Dr Lum will then give a brief overview of several notions of fairness that have been proposed in the ‘algorithmic fairness’ literature as solutions to these problems. She will close with a discussion of the ways in which policy, rather than data science, influences the development of these models and some alternative non-algorithmic solutions to the underlying problems these models seek to address.

About the speaker

Dr Kristian Lum is Lead Statistician at the Human Rights Data Analysis Group (HRDAG), where she leads the HRDAG project on criminal justice in the United States.

Dr Lum’s research primarily focuses on examining the uses of machine learning in the criminal justice system and has concretely demonstrated the potential for machine learningbased predictive policing models to reinforce and, in some cases, amplify historical racial biases in law enforcement.

Read more about the Ihaka Lecture Series.

The New Zealand Statistical Association

Our thanks to The New Zealand Statistical Association who are our official sponsors for the 2019 Ihaka Lecture Series.