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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.
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.
Stanford Online
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