Review into bias in algorithmic decision-making

Interim Report by the Centre for Data Ethics and Innovation (UK): The use of algorithms has the potential to improve the quality of decision- making by increasing the speed and accuracy with which decisions are made. If designed well, they can reduce human bias in decision-making processes. However, as the volume and variety of data used to inform decisions increases, and the algorithms used to interpret the data become more complex, concerns are growing that without proper oversight, algorithms risk entrenching and potentially worsening bias.

The way in which decisions are made, the potential biases which they are subject to and the impact these decisions have on individuals are highly context dependent. Our Review focuses on exploring bias in four key sectors: policing, financial services, recruitment and local government. These have been selected because they all involve significant decisions being made about individuals, there is evidence of the growing uptake of machine learning algorithms in the sectors and there is evidence of historic bias in decision-making within these sectors. This Review seeks to answer three sets of questions:

  1. Data: Do organisations and regulators have access to the data they require to adequately identify and mitigate bias?
  2. Tools and techniques: What statistical and technical solutions are available now or will be required in future to identify and mitigate bias and which represent best practice?
  3. Governance: Who should be responsible for governing, auditing and assuring these algorithmic decision-making systems?

Our work to date has led to some emerging insights that respond to these three sets of questions and will guide our subsequent work….(More)”.