Machine learning techniques are transforming the manner in which much of the legal system works, and criminal justice is the area which will be most fundamentally changed. Given the fundamental rights and interests at stake in the criminal justice system, this is also the field where the unthinking application of artificial intelligence ("AI") is most troubling, and where there is the greatest threat to individual rights and the likelihood of unanticipated damage to the rule of law. These problems will occur (and are occurring) throughout the criminal justice system: from data-driven predictive policing systems in the criminal investigation process, through to recidivism prediction for parole applications and sentencing recommendation systems post-trial. The risks presented by Al to the proper functioning of the criminal justice system will be exacerbated by commercial pressures on law enforcement and the criminal justice system, partisan political interests, and a lack of technological understanding by the judiciary and the legal profession more generally. Notwithstanding this dystopian vision, there is an opportunity to use AI techniques to improve the detection of crime, prosecute and sentence criminal offenders, help uncover discrimination, ensure parity of treatment across the system, and identify unfair and unjust treatment. The thoughtful and appropriate use of "ethical" Al systems can greatly assist in the administration of justice and the rule of law. In this Article, we propose a framework for systematically implementing Al into the criminal justice system in order to ensure that the system operates in a normatively enhanced and more effective and efficient manner. In proposing this framework we grapple with the reality that humans have an intrinsic emotional dislike of computers making decisions that have an important impact on peoples' lives.
Dan Hunter, Mirko Bagaric & Nigel Stobbs,
A Framework for the Efficient and Ethical Use of Artificial Intelligence in the Criminal Justice System,
47 Fla. St. U. L. Rev.