AI’s Risky Business: Embracing Ambiguity in Managing the Risks of AI

16 J. Bus. & Tech. L. 259 (2021), Available at: https://digitalcommons.law.umaryland.edu/jbtl/vol16/iss2/4

41 Pages Posted: 11 Nov 2021

See all articles by Ryan Budish

Ryan Budish

Harvard University - Berkman Klein Center for Internet & Society

Date Written: September 1, 2021

Abstract

There are over 160 different sets of artificial intelligence (AI) governance principles from public and private organizations alike. These principles aspire to enhance AI’s transformative potential and limit its negative consequences. Increasingly, these principles and strategies have invoked the language of “risk management” as a mechanism for articulating concrete guardrails around AI technologies. Unfortunately, what “risk management” means in practice is largely undefined and poorly understood. In fact, there are two very different approaches to how we measure risk. One approach emphasizes quantification and certainty. The other approach eschews the false certainty of quantification and instead embraces the inherently qualitative (and correspondingly imprecise) measures of risk expressed through social and political dialogue across stakeholders. This paper argues that the emerging field of AI governance should embrace a more responsive, inclusive, and qualitative approach that is better tailored to the inherent uncertainties and dynamism of AI technology and its societal impacts. And yet this paper also describes how doing so will be difficult because computer science and digital technologies (and, by extension, efforts to govern those technologies) inherently push toward certainty and the elimination of ambiguity. This paper draws upon experiences from other scientific fields that have long had to grapple with how best to manage the risks of new technologies to show how qualitative approaches to risk may be better tailored to the challenges of emerging technologies like AI, despite the potential tradeoffs of unpredictability and uncertainty.

Keywords: artificial intelligence, AI, governance, law, risk, technology

Suggested Citation

Budish, Ryan, AI’s Risky Business: Embracing Ambiguity in Managing the Risks of AI (September 1, 2021). 16 J. Bus. & Tech. L. 259 (2021), Available at: https://digitalcommons.law.umaryland.edu/jbtl/vol16/iss2/4, Available at SSRN: https://ssrn.com/abstract=3926321

Ryan Budish (Contact Author)

Harvard University - Berkman Klein Center for Internet & Society ( email )

Harvard Law School
23 Everett, 2nd Floor
Cambridge, MA 02138
United States

HOME PAGE: http://https://cyber.harvard.edu/people/rbudish

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
42
Abstract Views
217
PlumX Metrics