Algorithmic Black Swans
55 Pages Posted: 1 Mar 2023
Date Written: February 25, 2023
Abstract
From biased lending algorithms to chatbots that spew violent hate speech, AI systems already pose many risks to society. While policymakers have a responsibility to tackle pressing issues of algorithmic fairness, privacy, and accountability, they also have a responsibility to consider broader, longer-term risks from AI technologies. In public health, climate science, and financial markets, anticipating and addressing societal-scale risks is crucial. As the COVID-19 pandemic demonstrates, overlooking catastrophic tail events — or “black swans” — is costly. The prospect of automated systems manipulating our information environment, distorting societal values, and destabilizing political institutions is increasingly palpable. At present, it appears unlikely that market forces will address this class of risks. Organizations building AI systems do not bear the costs of diffuse societal harms and have limited incentive to install adequate safeguards. Meanwhile, regulatory proposals such as the White House AI Bill of Rights and the European Union AI Act primarily target the immediate risks from AI, rather than broader, longer-term risks. To fill this governance gap, this Article offers a roadmap for “algorithmic preparedness” — a set of five forward-looking principles to guide the development of regulations that confront the prospect of algorithmic black swans and mitigate the harms they pose to society.
Keywords: Artificial Intelligence, ChatGPT, Governance, Regulation, General Purpose Systems, Misuse, Systemic Risk, EU AI Act, NIST AI Risk Management Framework, White House AI Bill of Rights
JEL Classification: D18, K24, L86, O31, O33, O38
Suggested Citation: Suggested Citation
Noam Kolt (Contact Author)
University of Toronto
105 St George Street
Toronto, Ontario M5S 3G8
Canada
HOME PAGE: http://noamkolt.com/
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