Help wanted: an examination of hiring algorithms, equity, and bias

The hiring process is a critical gateway to economic opportunity, determining who can access consistent work to support themselves and their families. Employers have long used digital technology to manage their hiring decisions, and now many are turning to new predictive hiring tools to inform each step of their hiring process. This report explores how predictive tools affect equity throughout the entire hiring process. We explore popular tools that many employers currently use, and offer recommendations for further scrutiny and reflection. We conclude that without active measures to mitigate them, bias will arise in predictive hiring tools by default.

In the first part of this report, we summarize some important background and key concepts: the history of hiring technologies since the 1990s, incentives driving employers to adopt hiring technologies, a conceptual framework for assessing equity (especially those beyond interpersonal biases), and basic US legal and regulatory context. Next, we outline the four stages of the classic hiring process: sourcing, screening, interviewing, and selection. We explore popular predictive technologies used at each stage, analyzing their promises and pitfalls. In closing, we offer reflections and recommendations.

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