Law Commons^™

Optimizing Cybersecurity Risk In Medical Cyber-Physical Devices, Christopher S. Yoo, Bethany Lee

All Faculty Scholarship

Medical devices are increasingly connected, both to cyber networks and to sensors collecting data from physical stimuli. These cyber-physical systems pose a new host of deadly security risks that traditional notions of cybersecurity struggle to take into account. Previously, we could predict how algorithms would function as they drew on defined inputs. But cyber-physical systems draw on unbounded inputs from the real world. Moreover, with wide networks of cyber-physical medical devices, a single cybersecurity breach could pose lethal dangers to masses of patients.

The U.S. Food and Drug Administration (FDA) is tasked with regulating medical devices to ensure safety and …

Regulation Of Algorithmic Tools In The United States, Christopher S. Yoo, Alicia Lai

All Faculty Scholarship

Policymakers in the United States have just begun to address regulation of artificial intelligence technologies in recent years, gaining momentum through calls for additional research funding, piece-meal guidance, proposals, and legislation at all levels of government. This Article provides an overview of high-level federal initiatives for general artificial intelligence (AI) applications set forth by the U.S. president and responding agencies, early indications from the incoming Biden Administration, targeted federal initiatives for sector-specific AI applications, pending federal legislative proposals, and state and local initiatives. The regulation of the algorithmic ecosystem will continue to evolve as the United States continues to search …

Algorithms And Human Freedom, Richard Warner, Robert Sloan

All Faculty Scholarship

Predictive analytics such as data mining, machine learning, and artificial intelligence drive algorithmic decision making. Its "all-encompassing scope already reaches the very heart of a functioning society". Unfortunately, the legal system and its various tools developed around human decisionmakers cannot adequately administer accountability mechanisms for computer decision making. Antiquated approaches require modernization to bridge the gap between governing human decision making and new technologies. We divide the bridge-building task into three questions. First, what features of the use of predictive analytics significantly contribute to incorrect, unjustified, or unfair outcomes? Second, how should one regulate those features to make outcomes more …