Identifying bias when sensitive attribute data is unavailable: Geolocation in Mortgage Data

In our last post, we explored data on mortgage applicants from 2017 released in accordance with the Home Mortgage Disclosure Act (HMDA). We will use that data, which includes self-reported race of applicants, to test how well we can infer race using applicants’ geolocations in our effort to better understand methods to infer missing sensitive … Continue reading “Identifying bias when sensitive attribute data is unavailable: Geolocation in Mortgage Data”

Identifying bias when sensitive attribute data is unavailable: Exploring Data from the HMDA

To test their automated systems for possible bias across racial or gender lines, organizations may seek to know which individuals belong to each race and gender group. However, such information may not be easily accessible, and organizations may use techniques to infer such information in the absence of available data [1]. Here, we explore a … Continue reading “Identifying bias when sensitive attribute data is unavailable: Exploring Data from the HMDA”

Identifying bias when sensitive attribute data is unavailable: Techniques for inferring protected characteristics

To evaluate whether decisions in lending, health care, hiring and beyond are made equitably across race or gender groups, organizations must know which individuals belong to each race and gender group. However, as we explored in our last post, the sensitive attribute data needed to conduct analyses of bias and fairness may not always be … Continue reading “Identifying bias when sensitive attribute data is unavailable: Techniques for inferring protected characteristics”

Identifying bias when sensitive attribute data is unavailable

The perils of automated decision-making systems are becoming increasingly apparent, with racial and gender bias documented in algorithmic hiring decisions, health care provision, and beyond. Decisions made by algorithmic systems may reflect issues with the historical data used to build them, and understanding discriminatory patterns in these systems can be a challenging task [1]. Moreover, … Continue reading “Identifying bias when sensitive attribute data is unavailable”