Linear Digressions is a podcast that touches upon the technical and social aspects of machine learning and data science. If you are interested in learning about the actual practice of machine learning, you can listen to episodes such as “Convolutional Neural Networks,” “Gaussian Processes,” “Better know a distribution: the Poisson distribution,” as well as many others. If you are interested in learning about the societal impacts of machine learning, tune into “Racism, the criminal justice system, and data science,” “Facial recognition, society, and the law,” “Interesting technical issues prompted by the GDPR and data privacy concerns,” or “Differential Privacy: how to study people without being weird and gross.” Episodes are short and digestable, ranging anywhere from 15 to 35 minutes, and are riddled with witty humor, interesting insights, and information from experts.
Your Undivided Attention
It is no surprise that any content coming from Tristan Harris would make the recommendation list. He is joined by Aza Raskin to host Your Undivided Attention, a podcast from the Center for Humane Technology. This podcast centers around raising awareness of the “arms race to seize your attention” by Big Tech corporations, as Harris and Raskin dive deep into how these companies use hidden and covert strategies to capture our attention and control our choices. Episodes include “Down the Rabbit Hole by Design,” “When Attention Went on Sale,” “Digital Democracy is Within Reach,” and “The Opposite of Addiction.” This podcast is incredibly accessible to people from all backgrounds who are interested in the ethics of the tactics used by technology companies.
Practical AI: Machine Learning and Data Science
Practical AI is a podcast that focuses on ways of bringing artificial intelligence to the real world in accessible ways. This podcast is great for people who want to keep up with the latest advancements in artificial intelligence and how they can be applied to our lives. While many episodes tend to be a bit more focused on the, well, practical uses of artificial intelligence, there are many episodes that address the necessity and possibility of artificial intelligence ethics—including “Practical AI Ethics,” “Explaining AI Explainability,” AI for Good: clean water access in Africa,” and “Exposing the Deception of Deepfakes.” What makes this podcast is unique is its coverage of specific instances of ethical and unethical artificial intelligence, rather than discussing the broader issue as a whole. Both are crucial, but if you are more interested in the actual ways we can use artificial intelligence for good, this podcast is for you.
Towards Data Science
Towards Data Science is an online publication and organization hosted through Medium where experts can publish articles on a wide range of topics related to machine learning and data science. But TDS has gone one step further, and started their own podcast. Each episode features a different professional in the field of STEM, which keeps the podcast fresh and intriguing, and allows it to touch on all different aspects of machine learning and data science. While many episodes are either strictly technical or dive into the data science practices at a specific company, many others touch on crucial aspects of artificial intelligence ethics, including “Edouard Harris – Emerging problems in machine learning: making AI ‘good,'” “Rohin Shah – Effective altruism, AI safety, and learning human preferences from the state of the world,” “Annette Zummermann – The ethics of AI,” and “Rob Miles – Why should I care about AI safety?”. For those looking to expand their machine learning and data science foundation at a high level, look no further than the Towards Data Science podcast.