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An AI with an Agenda

NDC Conferences via YouTube

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Overview

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This talk examines common ways human bias and other errors can enter AI and machine learning systems, from confusing correlation with causation to feedback effects. It discusses practical ways to address these issues, including distributionally robust optimization.

Syllabus

Introduction
Why does this matter
Consequences
Correlation
Conditional Probability
Data vs Sample Data
Bias
What can you do
Pricing algorithms
Shadow of understanding
What can we do
Distributionally Robust Optimization
Feedback

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NDC Conferences

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