Can we trust AI algorithms to make decisions for us? If the algorithm makes a mistake, who's responsible for it? It all boils down to being able to track how the machine learning model has been built. In other words, explainability!
In this episode we mentioned the following resources:
https://en.wikipedia.org/wiki/Explainable_artificial_intelligence
https://www.napier.ai/post/explainability-in-ai
https://vitalflux.com/what-is-explainable-ai-concepts-examples/

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