Exploring the use of algorithms and AI in criminal justice and the concerns surrounding their impact, including examples of polluted air being deemed safe and racial bias affecting health algorithms. Examining the growing automation in the justice system and the role of AI in investigations and trials, as well as the concept of black boxes in AI.
Many AIs are 'black box' in nature, meaning that part of all of the underlying structure is obfuscated, either intentionally to protect proprietary information, due to the sheer complexity of the model, or both. This can be problematic in situations where people are harmed by decisions made by AI but left without recourse to challenge them.
Many researchers in search of solutions have coalesced around a concept called Explainable AI, but this too has its issues. Notably, that there is no real consensus on what it is or how it should be achieved. So how do we deal with these black boxes? In this podcast, we try to find out.
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