Proctor : September 2017
34 PROCTOR | September 2017 Building Judge Hercules Blending the science of analytics with the art of law Jurist Ronald Dworkin opined that the role of the judiciary is to look beyond the law to uncover its underlying principles. In his 1986 text, Law’s Empire,1 Dworkin created ‘Judge Hercules’ as the embodiment of his idealistic version of a lawyer with legal skills sufficient to surpass the traditional limitations of human decision-making. In the contemporary context, alarmists argue that the rapid development of technology- driven processes foreshadows the impending obsolescence of lawyers. To the contrary, the authors argue that the use of data analytics allows lawyers to embody Judge Hercules by enabling a decision-making process that combines the best of both technological and human capabilities. Growth of analytics Global internet traffic has increased from an average of about 100 gigabytes a day in 1992 to an astronomical 26,600 gigabytes a second today.2 At the same time, the increasing capacity of computer processors to digest big data has made data analytics more viable. Data analytics is now capable of extracting and categorising information to identify patterns and trends. From neuroradiology to chess, data is fast becoming a new commodity with tangible value. Interestingly, the growth of data analytics in chess serves as a useful parallel for the purposes of forecasting the role of analytics in the legal profession. Garry Kasparov, arguably the greatest chess player of all time, advocates for a future punctuated by the increased use of artificial intelligence.3 Despite his prestigious title as a grand master, in 1997 Kasparov suffered a controversial loss against IBM’s early chess computer, Deep Blue. The defeat prompted Kasparov to spend years studying the relationship humans have with technology. As a result, Kasparov formed the belief that the integration of humans and computers has enormous benefits for complex decision- making, both in and beyond chess. Kasparov argues that computers are undeniably better calculators and data processors whereas humans hold superior analogical thinking, pattern recognition and executive decision- making capabilities. According to Kasparov, “we should look for the way of combining human skills and machine skills. And that, I believe, is the future role of humanity... to make sure [we] will be using this immense power of brute force of calculation for our benefit”. 4 Kasparov believes that technology provides a “steady hand” to assist us in mitigating the damage caused by the weaknesses of the human condition, including fatigue, distraction and cognitive biases. At the same time he argues that there is irreplaceable value in human intuition and its potential to complement complex data analytics. The analytics-empowered practitioner Data analysis in the legal context (legal analytics) is extremely powerful and provides the ability to aggregate enormous volumes of data and form sophisticated prediction models. Legal analytics enables lawyers to automate processes and subsequently reduce the time and cost of manual work. Obvious examples of the court’s growing reliance on legal analytics include: a. the Federal Court’s Practice Note on Technology and the Court5 b. recent decisions requiring parties to perform discovery with the assistance of data analytics and automated filtering6 (eDiscovery) c. smart contracts (see ‘Blockchain 101 – cracking the code’, Proctor, November 2016, page six). However, the court’s progressive approach to analytics prompts the question – will technology make lawyers redundant? Wisconsin v Loomis The answer lies in reconciling the growing schism in the profession between those who view the law as an industry ripe for automation and those who retain the traditional view of the law as an art form. Recently in the United States, the Wisconsin Supreme Court considered the role automated prediction should play in determining the likelihood of recidivism. In Wisconsin v Loomis, 7 Loomis was alleged to have been involved in a drive-by shooting. The court was required to rule on whether the use of an analytics tool in initial sentencing had violated Loomis’ constitutional right to due process.8 At trial, an analytics tool called the Correctional Offender Management Profiling for Alternative Sanctions9 (COMPAS) had been utilised. The role of COMPAS is to determine whether an offender is likely to reoffend by referencing the behaviour of past offenders in similar circumstances. COMPAS operates by taking information provided by a defendant and comparing it with publicly available data to build predictive models based on historical correlations. In Loomis’ case, COMPAS indicated that, based on available metrics and data, Loomis posed a ‘high risk’ of reoffending10 if released.