Ian Kerr, Privacy and the Bad Man: Or, How I Got Lucky With Oliver Wendell Holmes Jr.
Comment by: Tal Zarsky
Workshop draft abstract:
You all (y’all?) having likewise experienced the recursive nature of the exercise of writing a law review article, you will appreciate that, this year, for PLSC, I decided to challenge myself to a game of Digital Russian Roulette. I wondered what result Google’s predictive algorithm would generate as the theoretical foundation for an article that I would soon write on predictive computational techniques and their jurisprudential implications. Plugging the terms: ‘prediction’, ‘computation’, ‘law’ and ‘theory’ into Google, I promised myself that I would focus the article on whatever subject matter popped up when I clicked on the ‘I’m Feeling Lucky’ search feature.
So there I was, thanks to Google’s predictive algorithm, visiting a Wikipedia page on the jurisprudence of Oliver Wendell Holmes Jr. (Wikipedia, 2011). Google done good. Perhaps America’s most famous jurist, Holmes was clearly fascinated by the power of predictions and the predictive stance. So much so that he made prediction the centerpiece of his own prophecies regarding the future of legal education: ‘The object of our study, then, is prediction, the prediction of the incidence of the public force through the instrumentality of the courts’ (Holmes, 1897: 457).
Given his historical role in promoting the skill of prediction to aspiring lawyers and legal educators, one cannot help but wonder what Holmes might have thought of the proliferation of predictive technologies and probabilistic techniques currently under research and development within the legal domain. Would he have approved of the legal predictions generated by expert systems software that provide efficient, affordable, computerized legal advice as an alternative to human lawyers? What about the use of argument schemes and other machine learning techniques in the growing field of ‘artificial intelligence and the law’ (Prakken, 2006) seeking to make computers, rather than judges, the oracles of the law?
Although these were not live issues in Holmes’s time, contemporary legal theorists cannot easily ignore such questions. We are living in the kneecap of technology’s exponential growth curve, with a flight trajectory limited more by our imaginations than the physical constraints upon Moore’s Law. We are also knee-‐deep in what some have called ‘the computational turn’ (Hildebrandt, 2011) wherein innovations in storage capacity, data aggregation techniques and cross-‐contextual linkability enable new forms of idiopathic predictions. Opaque, anticipatory algorithms and social graphs allow inferences to be drawn about people and their preferences. These inferences may be accurate (or not), without our knowing exactly why.
One might say that our information society has swallowed whole Oliver Wendell Holmes Jr.’s predictive pill, except that our expansive social investment in predictive techniques extends well beyond the bounds of predicting, ‘what the courts will do in fact’ (Holmes, 1897: 457). What Holmes said more than a century and a decade ago about the ‘body of reports, of treatises, and of statutes in the United States and in England, extending back for six hundred years, and now increasing annually by hundreds’ (Holmes, 1897: 457) can now be said of the entire global trade in personal information, fueled by emerging techniques in computer and information science, such as KDD (knowledge discovery in databases):
In these sibylline leaves are gathered the scattered prophecies of the past upon the cases in which the axe will fall. These are what properly have been called the oracles of the law. Far the most important and pretty nearly the whole meaning of every new effort of … thought is to make these prophecies more precise, and to generalize them into a thoroughly connected system. (Homes,1897: 457)
As described in my article, the computational axe has fallen many times already and will continue to fall.
My article examines the path of law after the computational turn. Inspired by Holmes’s use of prediction to better understand the fabric of law and social change, I suggest that his predictive stance (the famous “bad man” theory) is also a useful heuristic device for understanding and evaluating the predictive technologies currently embraced by public-‐ and private-‐sector institutions worldwide. I argue that today’s predictive technologies threaten privacy and due process. My concern is that the perception of increased efficiency and reliability in the use of predictive technologies might be seen as the justification for a fundamental jurisprudential shift from our current ex post facto systems of penalties and punishments to ex ante preventative measures premised on social sorting, increasingly adopted across various sectors of society.
This jurisprudential shift, I argue, could significantly undermine the value-‐based approach that underlies the ‘reasonable expectation of privacy’ standard adopted by common law courts, privacy and data commissioners and an array of other decision makers. More fundamentally, it could alter the path of law, significantly undermining core presumptions built into the fabric of today’s retributive and restorative models of social justice, many of which would be preempted by tomorrow’s actuarial justice.
Holmes’s predictive approach was meant to shed light on the nature of law by shifting law’s standpoint to the perspective of everyday citizens who are subject to the law. Preemptive approaches enabled by the computational turn will obfuscate the citizen’s legal standpoint championed by Holmes. I warn that preemptive approaches have the potential to alter the very nature of law without justification, undermining many core legal presumptions and other fundamental commitments.
In the article, I propose that the unrecognized genius in Holmes’s jurisprudence is his (self-‐fulfilling) prophecy, more than a century ago, that law would become one of a series of businesses focused on prediction and the management of risk. I suggest that his famous speech, The Path of Law, lays a path not only for future lawyers but also for data scientists and other information professionals. The article commences with an examination of Holmes’s predictive theory. I articulate what I take to be his central contribution—that to understand prediction, one must come to acknowledge, understand and account for the point of view from which it is made. An appreciation of Holmes’s “predictive stance” allows for comparisons with the standpoints of today’s prediction industries. I go on to discuss these industries, attempting to locate potential harms generated by the prediction business associated with the computational turn. These harms are more easily grasped through a deeper investigation of prediction, wherein I argue that when prediction is understood in the broader context of risk, it is readily connected to the idea of preemption of harm. I suggest that the rapid increase in technologies of prediction and preemption go hand in hand, and I demonstrate how their broad acceptance could undermine the normative foundations of the ‘reasonable expectations of privacy’ standard, and show how it also fosters a growing social temptation to adopt a philosophy of preemption, and demonstrate how this could also have a significant impact on our fundamental commitments to due process.