Fairness in Ranking under Uncertainty

Understand

Fairness has emerged as an important consideration in algorithmic decision-making.

• Unfairness occurs when an agent with higher merit obtains a worse outcome than an agent with lower merit.
• Our central point is that a primary cause of unfairness is uncertainty.
• A principal or algorithm making decisions never has access to the agents' true merit, and instead uses proxy features that only imperfectly predict merit (e.g., GPA, star ratings, recommendation letters).