The swift incorporation of artificial intelligence (AI) into legal systems across the globe is changing the way justice is administered and posing significant ethical, legal, and societal issues. From predictive risk assessment models like the UK's HART to case prioritization systems like Brazil's VICTOR, artificial intelligence (AI) solutions promise consistency and efficiency yet function as opaque decision-making entities with far-reaching effects. The structural, algorithmic, and institutional aspects of AI in courts are critically examined in this paper, with particular attention paid to issues of bias, accountability, transparency, and human rights. It examines how algorithmic governance interacts with legal norms, societal inequities, and procedural fairness through a comparative analysis of AI applications in Brazil, Singapore, Argentina, Colombia, India, and the United Kingdom. The study highlights the dangers of proxy-based discrimination, "black box" systems, and the responsibility gaps that come with automated decision-making. It delves deeper into ethical frameworks like the OECD AI guidelines, the Montreal Declaration, and the Asilomar Principles, putting forth a rightscentered paradigm for AI governance that upholds individual liberties, maintains judicial legitimacy, and lessens systemic unfairness. In the end, the paper makes the case that merging technical innovation with strong legal protections, democratic oversight, and open accountability procedures is necessary to achieve Algorithmic Justice.
M. K. Srinivas (Sat,) studied this question.