The Fourth Industrial Revolution is fusing disciplines across the digital and physical worlds, with legal technology the latest example of how improved automation is reaching further and further into service-oriented professions. Casetext for example—a legal tech-startup providing Artificial Intelligence (AI)-based research for lawyers—recently secured $12 million in one of the industry’s largest funding rounds, but research is just one area where AI is being used to assist the legal profession.
Others include contract review and due diligence, analytics, prediction, the discovery of evidence, and legal advice. Technology and the law are converging, and where they meet new questions arise about the relative roles of artificial and human agents—and the ethical issues involved in the shift from one to the other. While legal technology has largely focused on the activities of the bar, it challenges us to think about its application to the bench as well. In particular, could AI replace human judges?
Before going any further, we should distinguish algorithms from Artificial Intelligence. In simple terms, algorithms are self-contained instructions, and are already being applied in judicial decision-making. In New Jersey, for example, the Public Safety Assessment algorithm supplements the decisions made by judges over bail by using data to determine the risk of granting bail to a defendant. The idea is to assist judges in being more objective, and increase access to justice by reducing the costs associated with complicated manual bail assessments.
AI is more difficult to define. People often conflate it with machine learning, which is the ability of a machine to work with data and processes, analyzing patterns that then allow it to analyze new data without being explicitly programmed. Deeper machine learning techniques can take in enormous amounts of data, tapping into neural networks to simulate human decision-making. AI subsumes machine learning, but it is also sometimes used to describe a futuristic machine super-intelligence that is far beyond our own.
The idea of AI judges raises important ethical issues around bias and autonomy. AI programs may incorporate the biases of their programmers and the humans they interact with. For example, a Microsoft AI Twitter chatbot named Tay became racist, sexist, and anti-Semitic within 24 hours of interactive learning with its human audience. But while such programs may replicate existing human biases, the distinguishing feature of AI over an algorithm is that it can behave in surprising and unintended ways as it ‘learns.’ Eradicating bias therefore becomes even more difficult, though not impossible. Any AI judging program would need to account for, and be tested for, these biases.
Giving AI decision-making powers over human cases also raises a fundamental issue of autonomy. In 1976, the German-American computer scientist Joseph Weizenbaum argued against replacing humans in positions of respect and care, and specifically mentioned judges. He argued that doing so would threaten human dignity and lead to alienation and devaluation.
Appealing to rationality, the counter-argument is that human judges are already biased, and that AI can be used to improve the way we deal with them and reduce our ignorance. Yet suspicions about AI judges remain, and are already enough of a concern to lead the European Union to promulgate a General Data Protection Regulation which becomes effective in 2018. This Regulation contains “the right not to be subject to a decision based solely on automated processing”.
In any case, could an AI judge actually do what human judges claim to do? If AI can correctly identify patterns in judicial decision-making, it might be better at using precedent to decide or predict cases. For example, an AI judge recently developed by computer scientists at University College London drew on extensive data from 584 cases before the European Court of Human Rights (ECHR).
