Judicial Decision-Making in the Age of Artificial Intelligence

Abstract

Artificial intelligence (AI) has become a pervasive presence in almost every aspect of society and business: from assigning credit scores to people, to identifying the best candidates for an employment position, to ranking applicants for admission to university. One of the most striking innovations in the United States criminal justice system in the last three decades has been the introduction of risk-assessment software, powered by sophisticated algorithms, to predict whether individual offenders are likely to re-offend. The focus of this contribution is on the use of these risk-assessment tools in criminal sentencing. Apart from the broader social, ethical and legal considerations, to date, not much is known about how perceptions of technology influence cognition in decision-making, particularly in the legal context. What research does demonstrate is that humans are inclined to trust algorithms as objective, and, as such, as unobjectionable. This contribution examines two phenomena in this regard: (i) the “technology effect”—the human tendency towards excessive optimism when making decisions involving technology; and (ii) “automation bias”—the phenomenon whereby judges accept the recommendations of an automated decision-making system, and cease searching for confirmatory evidence, perhaps even transferring responsibility for decision-making onto the machine.