Building The Race and AI Toolkit

If you are reading this, you have been asked to help contribute to, or test this Race and AI Toolkit. Thank you for taking up the mission! Key facts This Toolkit will be available for free globally as an online resource, and will have other types of elements added, such as: An interactive section similar […]

Racist Robots? How AI bias may put financial firms at risk

Through a case study of mortgage applications, this article shows how bias might be introduced to AI systems by either bias within historical data, and/or inherent biases of AI programmers and employers. This article gives reasons why this presents a risk to businesses in terms of missing out on customers (refusing credit to creditworthy people) […]

Black Loans Matter: fighting bias for AI fairness in lending

A detailed summary of research by Mark Weber, Mikhail Yurochkin, Sherif Botros and Vanio Markov, breaking down the lack of racial justice in the current US financial system which leads to the loss of the right to financial security, along with examination of solutions.

Unmasking Facial Recognition | WebRoots Democracy Festival

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This video is an in depth panel discussion of the issues uncovered in the ‘Unmasking Facial Recognition’ report from WebRootsDemocracy. This report found that facial recognition technology use is likely to exacerbate racist outcomes in policing and revealed that London’s Metropolitan Police failed to carry out an Equality Impact Assessment before trialling the technology at […]

Algorithms and bias: What lenders need to know

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Explains (from a US perspective) how the development of machine learning and algorithms has left financial services at risk of exacerbating biases. Using the example of lending, the article explains how algorithms incorporate biases into our systems, and what organisations can do to limit risk, particularly from a legal perspective.