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1
Intro
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Outline
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Data Ethics
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Why Data Ethics
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Caredot Data Program
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Unintended Behavior
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Lack of Foresight
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Oversight
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Distributed Responsibility
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Risks
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Nightscope
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General Approaches
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Deontology
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Environmental Approach
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Algorithms
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Normative Concerns
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Ethical Challenges
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Unjustified Actions
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Informational Privacy
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Algorithmic Systems
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Opacity
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Houston Teachers Union
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General Data Protection Regulation
Description:
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.

Introduction to Data Ethics - Brent Mittelstadt

Alan Turing Institute
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