As robots and artificial intelligence (AI) increase their influence over society, policymakers are increasingly regulating them. But to regulate these technologies, we first need to know what they are. And here we come to a problem. No one has been able to offer a decent definition of robots and AI\u2014not even experts. What\u2019s more, technological advances make it harder and harder each day to tell people from robots and robots from \u201cdumb\u201d machines. We have already seen disastrous legal definitions written with one target in mind inadvertently affecting others. In fact, if you are reading this you are (probably) not a robot, but certain laws might already treat you as one.<\/p>\n\n\n\n
Definitional challenges like these aren\u2019t exclusive to robots and AI. But today, all signs indicate we are approaching an inflection point. Whether it is citywide bans of \u201crobot sex brothels\u201d or nationwide efforts to crack down on \u201cticket scalping bots,\u201d we are witnessing an explosion of interest in regulating robots, human enhancement technologies, and all things in between. And that, in turn, means that typological quandaries once confined to philosophy seminars can no longer be dismissed as academic. Want, for example, to crack down on foreign \u201cinfluence campaigns\u201d by regulating social media bots? Be careful not to define \u201cbot\u201d too broadly (like the California legislature recently did), or the supercomputer nestled in your pocket might just make you one. Want, instead, to promote traffic safety by regulating drivers? Be careful not to presume that only humans can drive (as our Federal Motor Vehicle Safety Standards do), or you may soon exclude the best drivers on the road.<\/p>\n\n\n\n
In this Article, we suggest that the problem isn\u2019t simply that we haven\u2019t hit upon the right definition. Instead, there may not be a \u201cright\u201d definition for the multifaceted, rapidly evolving technologies we call robots or AI. As we will demonstrate, even the most thoughtful of definitions risk being overbroad, underinclusive, or simply irrelevant in short order. Rather than trying in vain to find the perfect definition, we instead argue that policymakers should do as the great computer scientist, Alan Turing, did when confronted with the challenge of defining robots: embrace their ineffable nature. We offer several strategies to do so. First, whenever possible, laws should regulate behavior, not things (or as we put it, regulate verbs, not nouns). Second, where we must distinguish robots from other entities, the law should apply what we call Turing\u2019s Razor, identifying robots on a case-by-case basis. Third, we offer six functional criteria for making these types of \u201cI know it when I see it\u201d determinations and argue that courts are generally better positioned than legislators to apply such standards. Finally, we argue that if we must have definitions rather than apply standards, they should be as short-term and contingent as possible. That, in turn, suggests that regulators\u2014not legislators\u2014should play the defining role.<\/p>\n\n\n\n