In this episode, we are talking to Ph.D. candidate Travis Greene from the Institute of Service Science in Taipei, Taiwan, about the philosophical, ethical, and judicial implications of modern data science, machine learning algorithms, and recommender systems.

We talk about the ethical responsibilities of individual data scientists, a wider perspective on the role of behavioral big data in our societies, and the moral dilemma associated with building potentially harmful algorithms.

We discuss the difference between American and European approaches to data privacy and protection, the GDPR, the recent court rulings around Privacy Shield by the European Court of Justice, how we could shape online rights around ideas of building our own narrative online, how recommender systems of the future should take ideas around human well-being and flourishing into account, and how they are related to religions in giving us closure in complex information environments.

We end the conversation by talking about how scientific work prospers from personal contact, conferences, and collaborations.

The podcast is hosted by Manuel Brenner.