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Non-Autonomous Artificial Intelligence Programs And Products Liability: How New Ai Products Challenge Existing Liability Models And Pose New Financial Burdens, Greg Swanson Apr 2019

Non-Autonomous Artificial Intelligence Programs And Products Liability: How New Ai Products Challenge Existing Liability Models And Pose New Financial Burdens, Greg Swanson

Seattle University Law Review

This Comment argues that the unique relationship between manufacturers, consumers, and their reinforcement learning AI systems challenges existing products liability law models. These traditional models inform how to identify and apportion liability between manufacturers and consumers while exposing litigants to low-dollar tort remedies with inherently high-dollar litigation costs.11 Rather than waiting for AI autonomy, the political and legal communities should be proactive and generate a liability model that recognizes how new AI programs have already redefined the relationship between manufacturer, consumer, and product while challenging the legal and financial burden of prospective consumer-plaintiffs and manufacturer-defendants.


Amoral Machines, Or: How Roboticists Can Learn To Stop Worrying And Love The Law, Bryan Casey Aug 2017

Amoral Machines, Or: How Roboticists Can Learn To Stop Worrying And Love The Law, Bryan Casey

Northwestern University Law Review

The media and academic dialogue surrounding high-stakes decisionmaking by robotics applications has been dominated by a focus on morality. But the tendency to do so while overlooking the role that legal incentives play in shaping the behavior of profit-maximizing firms risks marginalizing the field of robotics and rendering many of the deepest challenges facing today’s engineers utterly intractable. This Essay attempts to both halt this trend and offer a course correction. Invoking Justice Oliver Wendell Holmes’s canonical analogy of the “bad man . . . who cares nothing for . . . ethical rules,” it demonstrates why philosophical abstractions like …


Technological Opacity, Predictability, And Self-Driving Cars, Harry Surden, Mary-Anne Williams Jan 2016

Technological Opacity, Predictability, And Self-Driving Cars, Harry Surden, Mary-Anne Williams

Publications

Autonomous or “self-driving” cars are vehicles that drive themselves without human supervision or input. Because of safety benefits that they are expected to bring, autonomous vehicles are likely to become more common. Notably, for the first time, people will share a physical environment with computer-controlled machines that can both direct their own activities and that have considerable range of movement. This represents a distinct change from our current context. Today people share physical spaces either with machines that have free range of movement, but are controlled by people (e.g. automobiles) or with machines that are controlled by computers, but highly …