Experts analyze how procurement could improve AI—and how AI could improve procurement.
Government agencies around the world are increasingly finding opportunities to use artificial intelligence (AI) to automate and improve a variety of tasks, including adjudication and regulatory enforcement. Although AI tools promise to deliver improved accuracy, consistency, and efficiency in performing certain tasks, their use by governments has also raised a variety of concerns, such as about a potential lack of fairness and transparency.
As interest in using AI tools continues to grow across the public sector, the importance of ensuring that these tools are used responsibly only grows more pivotal. Yet regulating governmental uses of AI may be difficult because of the highly varied nature of these tools and the broad range of settings in which they can be deployed.
Nevertheless, because these tools will often be developed by outside contractors working for government agencies, some experts suggest that the public procurement process can be used as a meaningful way of governing the design and deployment of AI. Still other experts suggest that AI tools could be used to help improve procurement itself—whether for AI or any goods and services acquired by governments.
To explore the possibilities of using procurement standards and processes as a means of regulating AI use by government, as well as the possibility of using AI to improve procurement processes more generally, The Regulatory Review is pleased to gather together important insights from leading experts on artificial intelligence, procurement, and the law.
This series features contributions by: Lavi Ben Dor, Penn Program on Regulation; Ashley Casovan, Responsible AI Institute; Dan Chenok, IBM Center for Business and Government; Cary Coglianese, University of Pennsylvania; Tim Cooke, ASI Government; Carlos Ignacio Gutierrez, Future of Life Institute; Abigail Jacobs, University of Michigan; Joshua A. Kroll, Naval Postgraduate School; Deirdre K. Mulligan, University of California, Berkeley; David Rubenstein, Washburn University School of Law; Var Shankar, Responsible AI Institute; and Jessica Tillipman, The George Washington University Law School.
The Procurement Path to AI Governance
June 27, 2022 | Lavi Ben Dor and Cary Coglianese, University of Pennsylvania
Procurement standards could promote responsible use of artificial intelligence by government.
Retooling the Acquisition Gateway for Responsible AI
June 28, 2022 | David Rubenstein, Washburn University School of Law
For government to make the most of artificial intelligence, it needs changes throughout the procurement life cycle.
Using AI to Reduce Performance Risk in U.S. Procurement
June 29, 2022 | Jessica Tillipman, The George Washington University Law School
Advances in digital technology can help in managing the goals of federal acquisition.
How Can Governments Use AI to Improve Procurement?
June 30, 2022 | Dan Chenok, IBM Center for Business and Government
By using artificial intelligence, agencies can improve their procurement processes.
Responsible AI is a Management Problem, Not a Purchase
July 4, 2022 | Joshua A. Kroll, Naval Postgraduate School
Developing ongoing programs to monitor AI and sustain good outcomes is essential for ensuring AI accountability.
Procurement Officials Are Leading Federal AI Adoption
July 5, 2022 | Timothy W. Cooke, ASI Government
Contracting officials and agency leaders are key to the deployment of ethical AI processes.
Procurement as an AI Governance Change Agent
July 6, 2022 | Carlos Ignacio Gutierrez, Future of Life Institute
Soft law standards can promote responsible procurement of artificial intelligence systems.
The Hidden Governance in AI
July 7, 2022 | Abigail Z. Jacobs, University of Michigan, and Deirdre K. Mulligan, University of California, Berkeley
Measurement modeling could further the government’s understanding of AI policymaking tools.
A Risk-Based Approach to AI Procurement
July 11, 2022 | Ashley Casovan and Var Shankar, Responsible AI Institute
Organizations should tailor contract requirements for procured AI systems based on levels of risk.