AI Ethics in Legal Decision-Making Bias, Transparency, And Accountability

Artificial Intelligence (AI) systems used in legal decision-making processes have created significant ethical challenges through their integration, leading to problems with bias and necessitating better transparency and accountability measures. This paper investigates the discriminatory effects of algorithmic bias by analyzing AI technologies that learn from historical legal datasets containing potential institutional biases. The opacity of AI decision-making, referred to as "black-boxed" decisions, creates complex obstacles to achieving both explainable judgments and fair outcomes. The article examines the absent responsibility structure that arises when legal practitioners utilize AI systems, as it complicates the identification of responsible parties for unfair and erroneous decisions. The author advocates for the development of a robust ethical framework to regulate AI applications in judicial systems, presenting real-world examples and analyzing current regulatory practices. The latent goals include building trust while safeguarding the principles of justice to ensure technology remains aligned with fundamental legal elements.