Making Government Procurement of AI More Democratic

A look at current efforts to develop new approaches to government tech procurement suitable for the age of AI.

The standard government agency procurement process was devised to eliminate graft and cronyism, reduce costs, and enable fair bidding opportunities. But some say those systems don’t cut it when it comes to government use of AI systems.  Whether used to automate responses to constituent letters, for taxation purposes, or in predictive policing risk assessments, by the very nature of their automated decision making, AI creates policy. This is why some are pushing for more democratic processes for AI procurement and partnerships.

RedTail’s Kate Kaye recently wrote about efforts from UC Berkeley law professors, AI Now Institute, Sunlight Foundation and others to guide new approaches to government procurement and use of AI.

Read it on IAPP.org.

About Kate Kaye

Kate Kaye is an award-winning multimedia journalist who has chronicled the evolution of digital media, data use and technology in her reporting for more than 20 years for outlets including Fast Company, MIT Technology Review, OneZero, CityLab, NPR and Advertising Age. One of the first journalists to track how political organizations use voter data and digital advertising (as early as 2002), she is the author of "Campaign '08: A Turning Point for Digital Media," a 2009 book covering the digital targeting efforts of the 2008 presidential campaigns.

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