Advanced analytics can transform public-sector services, but US agencies are wary of the risk of biased outcomes. Sound risk management is the key to a wider adoption that will benefit all citizens. The solution may partially be found in better model risk management. By applying practices to minimize the risk of bias and other forms of unfair treatment, leaders can help empower their institutions to adopt mission-enhancing AI and ML approaches while increasing public confidence in the government’s use of analytics to improve outcomes for all.
Here, we outline a best-practice approach to developing and monitoring algorithms that can help public-sector agencies harness the power of advanced analytics to deliver better public services, while mitigating bias and other forms of unfair treatment, and offer six key actions that will help mitigate the risk of bias, along with other risks associated with advanced analytics models.
This article was originally published on McKinsey.com on July 16, 2021 and is reprinted here by permission.
