Introduction to Data Ethics - Brent Mittelstadt

Explore the ethical implications of data science and artificial intelligence in this comprehensive lecture by Dr. Brent Mittelstadt from the Alan Turing Institute. Delve into key topics such as algorithmic fairness, accountability, transparency, and privacy in complex systems. Examine case studies like the Houston Teachers Union and the General Data Protection Regulation to understand real-world applications. Learn about various ethical approaches, including deontology and environmental perspectives, and their relevance to data ethics. Gain insights into the challenges of distributed responsibility, unintended behaviors, and the lack of foresight in AI development. Discover the importance of ethical auditing and the development of standards to ensure responsible use of algorithms and machine learning technologies.

Intro
Outline
Data Ethics
Why Data Ethics
Caredot Data Program
Unintended Behavior
Lack of Foresight
Oversight
Distributed Responsibility
Risks
Nightscope
General Approaches
Deontology
Environmental Approach
Algorithms
Normative Concerns
Ethical Challenges
Unjustified Actions
Informational Privacy
Algorithmic Systems
Opacity
Houston Teachers Union
General Data Protection Regulation