Data analytics in judicial decision making: Enhancing transparency or undermining independence?

Data analytics in legal decision-making is fast moving into the mainstream as courts everywhere try to bring their processes up-to-date and improve their effectiveness, consistency and openness. With the help of algorithms, large sets of data and predictive justice models, courts can analyze their past decisions, assist in choosing the right outcome and deal with inconsistencies that may arise in discretionary systems. People who support using technology in the courtroom believe it helps judges be held accountable, reveals problem areas, leads to needed changes and improves public trust. The issue with AI in law is that it could threaten judicial independence by using algorithmic techniques developed by different organizations which might lead to mistakes and ruin proper reasoning. Some point out that AI might include biases from history and this could lead judges to trust the algorithm’s decisions and neglect its impact on fairness, causing the algorithm to be favored over regular due process. Through researching writings, judicial rulings and new technologies, this study investigates the conflicts generated by the shift and proposes how to regulate legal data science to maintain judicial fairness, lawful procedure and the credibility of legal organizations. To sum up, technology cannot replace human experience, ethics and judicial values in changing the justice system.