Transparency in Predictive Algorithms: A Judicial Perspective
Although the apparent hyperbole about the promises of AI algorithms has successfully entered upon the judicial precincts; it has also procreated some robust concerns spanning from unfairness, privacy invasion, bias, discrimination, and the lack of legitimacy to the lack of transparency and explainability, etc. Notably, critics have already denounced the current use of the predictive algorithm in the judicial decision-making process in many ways, and branded them as ethically, legally, and technically distressing. So contextually, whereas there is already an ongoing transparency debate on board, this paper attempts to revisit, extend and contribute to such simmering debate with a particular focus from a judicial perspective. Since there is a good cause to preserve and promote trust and confidence in the judiciary as a whole, a searchlight is beamed on exploring how and why justice algorithms ought to be transparent as to their outcomes, with a sufficient level of explainability, interpretability, intelligibility, and contestability. This paper also ends up delineating the tentative paths to do away with black-box effects, and suggesting the way out for the use of algorithms in the high-stake areas like the judicial settings.