Remedies for Robots

108 Pages Posted: 31 Jul 2018 Last revised: 9 Mar 2019

See all articles by Mark A. Lemley

Mark A. Lemley

Stanford Law School

Bryan Casey

Stanford Law School

Date Written: July 31, 2018

Abstract

What happens when artificially intelligent robots misbehave? The question is not just hypothetical. As robotics and artificial intelligence (AI) systems increasingly integrate into our society, they will do bad things. They have already killed people.

These new technologies present a number of interesting substantive law questions, from predictability, to transparency, to liability for high stakes decision making in complex computational systems. Our focus here is different. We seek to explore what remedies the law can and should provide once a robot has caused harm.

Where substantive law defines who wins legal disputes, remedies law asks, “What do I get when I win?” Remedies are sometimes designed to make plaintiffs whole by restoring them to the condition they would have been in “but for” the wrong. But they can also contain elements of moral judgment, punishment, and deterrence. For instance, the law will often act to deprive a defendant of its gains even if the result is a windfall to the plaintiff, because we think it is unfair to let defendants keep those gains. In other instances, the law may order defendants to do (or stop doing) something unlawful or harmful.

Each of these goals of remedies law, however, runs into difficulties when the bad actor in question is neither a person nor a corporation but a robot. We might order a robot—or, more realistically, the designer or owner of the robot—to pay for the damages it causes. (Though, as we will see, even that presents some surprisingly thorny problems.) But it turns out to be much harder for a judge to “order” a robot, rather than a human, to engage in or refrain from certain conduct . Robots can’t directly obey court orders not written in computer code. And bridging the translation gap between natural language and code is often harder than we might expect. This is particularly true of modern AI techniques that empower machines to learn and modify their decision making over time. If we don’t know how the robot “thinks,” we won’t know how to tell it to behave in a way likely to cause it to do what we actually want it to do.

Moreover, if the ultimate goal of a legal remedy is to encourage good behavior or discourage bad behavior, punishing owners or designers for the behavior of their robots may not always make sense—if only for the simple reason that their owners didn’t act wrongfully in any meaningful way. The same problem affects injunctive relief. Courts are used to ordering people and companies to do (or stop doing) certain things, with a penalty of contempt of court for noncompliance. But ordering a robot to abstain from certain behavior won’t be trivial in many cases. And ordering it to take affirmative acts may prove even more problematic.

In this paper, we begin to think about how we might design a system of remedies for robots. It may, for example, make sense to focus less of our doctrinal attention on moral guilt and more of it on no-fault liability systems (or at least ones that define fault differently) to compensate plaintiffs. But addressing payments for injury solves only part of the problem. Often we want to compel defendants to do (or not do) something in order to prevent injury. Injunctions, punitive damages, and even remedies like disgorgement are all aimed, directly or indirectly, at modifying or deterring behavior. But deterring robot misbehavior too is going to look very different than deterring humans. Our existing doctrines often take advantage of “irrational” human behavior like cognitive biases and risk aversion. Courts, for instance, can rely on the fact that most of us don’t want to go to jail, so we tend to avoid conduct that might lead to that result. But robots will be deterred only to the extent that their algorithms are modified to include sanctions as part of the risk-reward calculus. These limitations may even require us to institute a “robot death penalty” as a sort of specific deterrence against certain bad behaviors. Today, speculation of this sort may sound far-fetched. But the field already includes examples of misbehaving robots being taken offline permanently—a trend which only appears likely to increase in the years ahead.

Finally, remedies law also has an expressive component that will be complicated by robots. We sometimes grant punitive damages—or disgorge ill-gotten gains—to show our displeasure with you. If our goal is just to feel better about ourselves, perhaps we might also punish robots simply for the sake of punishing them. But if our goal is to send a slightly more nuanced signal than that through the threat of punishment, robots will require us to rethink many of our current doctrines. It also offers important insights into the law of remedies we already apply to people and corporations.

Suggested Citation

Lemley, Mark A. and Casey, Bryan, Remedies for Robots (July 31, 2018). University of Chicago Law Review, 2019; Stanford Law and Economics Olin Working Paper No. 523. Available at SSRN: https://ssrn.com/abstract=3223621 or http://dx.doi.org/10.2139/ssrn.3223621

Mark A. Lemley (Contact Author)

Stanford Law School ( email )

559 Nathan Abbott Way
Stanford, CA 94305-8610
United States

Bryan Casey

Stanford Law School ( email )

559 Nathan Abbott Way
Stanford, CA 94305-8610
United States

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