The emergence of artificial intelligence raises critical questions about the implications of algorithms in decision-making processes, particularly in the legal system. Concerns about bias arise when algorithms trained on historical data inform judicial decisions, potentially perpetuating existing inequalities. The challenge lies in the opaque nature of these algorithms, often described as "black boxes," making it difficult to scrutinize their outputs and understand the biases they may carry.
