Open Access. Powered by Scholars. Published by Universities.®
- Publication
- Publication Type
Articles 1 - 4 of 4
Full-Text Articles in Law
Modeling Through, Ryan Calo
Modeling Through, Ryan Calo
Articles
Theorists of justice have long imagined a decision-maker capable of acting wisely in every circumstance. Policymakers seldom live up to this ideal. They face well-understood limits, including an inability to anticipate the societal impacts of state intervention along a range of dimensions and values. Policymakers cannot see around corners or address societal problems at their roots. When it comes to regulation and policy-setting, policymakers are often forced, in the memorable words of political economist Charles Lindblom, to “muddle through” as best they can.
Powerful new affordances, from supercomputing to artificial intelligence, have arisen in the decades since Lindblom’s 1959 article …
Terrified By Technology: How Systemic Bias Distorts U.S. Legal And Regulatory Responses To Emerging Technology, Steve Calandrillo, Nolan Kobuke Anderson
Terrified By Technology: How Systemic Bias Distorts U.S. Legal And Regulatory Responses To Emerging Technology, Steve Calandrillo, Nolan Kobuke Anderson
Articles
Americans are becoming increasingly aware of the systemic biases we possess and how those biases preclude us from collectively living out the true meaning of our national creed. But to fully understand systemic bias we must acknowledge that it is pervasive and extends beyond the contexts of race, privilege, and economic status. Understanding all forms of systemic bias helps us to better understand ourselves and our shortcomings. At first glance, a human bias against emerging technology caused by systemic risk misperception might seem uninteresting or unimportant. But this Article demonstrates how the presence of systemic bias anywhere, even in an …
Is Tricking A Robot Hacking?, Ryan Calo, Ivan Evtimov, Earlence Fernandes, Tadayoshi Kohno, David O'Hair
Is Tricking A Robot Hacking?, Ryan Calo, Ivan Evtimov, Earlence Fernandes, Tadayoshi Kohno, David O'Hair
Tech Policy Lab
The authors of this essay represent an interdisciplinary team of experts in machine learning, computer security, and law. Our aim is to introduce the law and policy community within and beyond academia to the ways adversarial machine learning (ML) alter the nature of hacking and with it the cybersecurity landscape. Using the Computer Fraud and Abuse Act of 1986—the paradigmatic federal anti-hacking law—as a case study, we mean to evidence the burgeoning disconnect between law and technical practice. And we hope to explain what is at stake should we fail to address the uncertainty that flows from the prospect that …
Artificial Intelligence Policy: A Primer And Roadmap, Ryan Calo
Artificial Intelligence Policy: A Primer And Roadmap, Ryan Calo
Articles
Talk of artificial intelligence is everywhere. People marvel at the capacity of machines to translate any language and master any game. Others condemn the use of secret algorithms to sentence criminal defendants or recoil at the prospect of machines gunning for blue, pink, and white-collar jobs. Some worry aloud that artificial intelligence will be humankind’s “final invention.” This essay, prepared in connection with UC Davis Law Review's 50th anniversary symposium, explains why AI is suddenly on everyone's mind and provides a roadmap to the major policy questions AI raises. The essay is designed to help policymakers, investors, technologists, scholars, and …