Black Box Accountability

Black Box Accountability refers to the challenge of understanding and explaining how complex systems, especially those driven by artificial intelligence or machine learning, make decisions. These systems are often called "black boxes" because their internal processes are opaque or difficult to interpret. Ensuring accountability means being able to assess, verify, and explain their decisions to ensure fairness, transparency, and responsibility. It involves developing methods to peer inside these black boxes or create methods for oversight so stakeholders can trust and evaluate the system’s outputs, even if the underlying workings are intricate or hidden.