Ethical Dimensions of Data Science

Explore the ethical challenges in data science through this comprehensive talk. Delve into historical controversies, systemic biases, and the moral implications of machine learning models. Learn about the Simpsons Paradox, Stanford Prison Experiment, and Milgram Experiment. Examine dilemmas in competence, data representation, privacy, and hypothesis testing. Gain insights on imposing human ethics on AI and paving the way for responsible data science practices. Discover how to navigate the complex ethical landscape of data science beyond raw numbers and spreadsheets.

Introduction
Overview
Awareness Test
Simpsons Paradox
Controversies
Stanford Prison Experiment
Milgram Experiment
Tesla
Dilemmas
Competence
Data Representation
Data Protection Privacy
Machine Learning
Hypothesis Testing