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explainable ai and good public policy


The tensions between explainable AI and good public policy

#artificialintelligence

There are two reasons why. First, with machine learning in general and neural networks or deep learning in particular, there is often a trade-off between performance and explainability. The larger and more complex a model, the harder it will be to understand, even though its performance is generally better. Unfortunately, for complex situations with many interacting influences--which is true of many key areas of policy--machine learning will often be more useful the more of a black box it is. As a result, holding such systems accountable will almost always be a matter of post hoc monitoring and evaluation.