Alice Parfett

Using History to Predict and Prevent Negative Outcomes of Population-Wide Racial Biometric Classification Systems

Project Summary

Classification systems can be witnessed in action throughout human history, as can their negative consequences. This project will focus on population-wide racial classification systems that use biometric data. A historical study into these systems over 3 periods throughout human history that coincide with great societal changes and racial movements will identify how these systems have changed:

-European colonialism of the New World (circa 1500)

-Foundation of the modern state (circa 1800)

-Digitisation (circa 2000)

This historical investigation will be combined with use of multi-modal AI tools to detect how negative outcomes have arisen from these systems over the 3 periods. This project will focus on population classification systems that use biometric data and have different outcomes for different people depending on their race. The aim being to better understand how these systems are defined and how their impacts have changed over time. With this, it is hoped the negative impacts can be predicted and prevented. As AI usage grows, the scale and speed of the impacts of these systems will be magnified. Hence, why this research needs to be conducted now, to identify what biometric classification systems are, how they impact people of different races and how to prevent humanity repeating its past mistakes.

Research Interests

‘Bias’ in AI.

AI and Privacy.

Historical Precedents.

Interdisciplinary Approaches.

Background

BSc Mathematical Sciences and History at University of Exeter, my dissertation was entitled ‘Artificial Intelligence and Slavery: the History and Mathematics of the Future’.

Supervisors

Prof Hilde Coffé

Dr Tom Fincham Haines