Stanford Seminar - The FATE of AI Ethics, Anna Bethke
Offered By: Stanford University via YouTube
Course Description
Overview
In this session I will be discussing the components of AI Ethics, and ways that researchers, and AI practitioners can incorporate these components into every stage of their development process. These components include fairness, accountability, transparency, explainability and human rights.
Anna Bethke is a Principal Data Scientist at Salesforce.
Syllabus
Introduction.
Principles of Ethical AI.
Why are Af Ethics important?.
Technology is Dual Use.
Pose Estimation Software.
What are the unintended positive and negative consequences of this technology?.
What are some strategies to mitigate the negative consequences, especially the most severe ones?.
Important aspects to note.
Measure and Mitigate Sources of Bias.
Open Source Tools.
Definitions of Fairness.
Algorithmic Bias Research.
Dispatcher.
Safety Workers.
Ethical Questions We Asked.
Ethical Considerations.
Model Cards.
Transparency Research.
Stanford Classes.
Salesforce Resources.
Taught by
Stanford Online
Tags
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Artificial Intelligence for Robotics
Stanford University via Udacity Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent