The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.
https://dataskeptic.com
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Black Boxes Are Not Required
Deep neural networks are undeniably effective. They rely on such a high number of parameters, that htey are appropriately described as “black boxes”. While black boxes lack desirably properties like interpretability and explainability, in some...
Understanding Neural Networks
What does it mean to understand a neural network? That’s the question posted on . Kyle speaks with about this and several other big questions.
Self-Explaining AI
joins us to discuss self-explaining AI. What could be better than an interpretable model? How about a model wich explains itself in a conversational way, engaging in a back and forth with the user. We discuss the paper which presents...
Plastic Bag Bans
joins us to discuss her work studying the impact of plastic bag bans as published in from the Journal of Environmental Economics and Management. How does one measure the impact of these bans? Are they achieving their intended goals?...