"What We Can't Measure, We Can't Understand": Challenges to Demographic Data Procurement in the Pursuit of Fairness

Understand

As calls for fair and unbiased algorithmic systems increase, so too does the number of individuals working on algorithmic fairness in industry.

• However, these practitioners often do not have access to the demographic data they feel they need to detect bias in practice.
• Even with the growing variety of toolkits and strategies for working towards algorithmic fairness, they almost invariably require access to demographic attributes or proxies.
• We investigated this dilemma through semi-structured interviews with 38 practitioners and professionals either working in or adjacent to algorithmic fairness.