In this guest post, PhD researcher Christopher Markou, University of Cambridge, explores the use of Artificial Intelligence in the justice system and asks whether the use of algorithms should be used to decide questions of guilt or innocence.

Artificial intelligence is already helping determine your future – whether it’s your Netflix viewing preferences, your suitability for a mortgage or your compatibility with a prospective employer. But can we agree, at least for now, that having an AI determine your guilt or innocence in a court of law is a step too far?

Worryingly, it seems this may already be happening. When American Chief Justice John Roberts recently attended an event, he was asked whether he could forsee a day “when smart machines, driven with artificial intelligences, will assist with courtroom fact finding or, more controversially even, judicial decision making”. He responded: “It’s a day that’s here and it’s putting a significant strain on how the judiciary goes about doing things”.

Roberts might have been referring to the recent case of Eric Loomis, who was sentenced to six years in prison at least in part by the recommendation of a private company’s secret proprietary software. Loomis, who has a criminal history and was sentenced for having fled the police in a stolen car, now asserts that his right to due process was violated as neither he nor his representatives were able to scrutinise or challenge the algorithm behind the recommendation.

The report was produced by a software product called Compas, which is marketed and sold by Nortpointe Inc to courts. The program is one incarnation of a new trend within AI research: ones designed to help judges make “better” – or at least more data-centric – decisions in court.

While specific details of Loomis’ report remain sealed, the document is likely to contain a number of charts and diagrams quantifying Loomis’ life, behaviour and likelihood of re-offending. It may also include his age, race, gender identity, browsing habits and, I don’t know … measurements of his skull. The point is we don’t know.

What we do know is that the prosecutor in the case told the judge that Loomis displayed “a high risk of violence, high risk of recidivism, high pretrial risk.” This is standard stuff when it comes to sentencing. The judge concurred and told Loomis that he was “identified, through the Compas assessment, as an individual who is a high risk to the community”.

The Wisconsin Supreme Court convicted Loomis, adding that the Compas report brought valuable information to their decision, but qualified it by saying he would have received the same sentence without it. But how can we know that for sure? What sort of cognitive biases are involved when an all-powerful “smart” system like Compas suggests what a judge should do? Continue reading →