Introduction
What is AI accountability?
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1. The Context for AI
The promise of AI
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General and narrow AI
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2. Technical Challenges of AI
The challenge of classification errors
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The causes of classification errors
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Bias in AI
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Supervised and unsupervised learning
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Biased labeling of data
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Construct validity
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The absence of meaning
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Vulnerability to attacks
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3. Social Challenges of AI
Dimensions of justice
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Moral and relational reasoning
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Issues of authenticity
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4. Legal Challenges of AI
Privacy laws
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Spurious discrimination
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The right to explanation
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Discrimination in data
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Discrimination in implementation
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5. Safety Challenges of AI
AI in life and death situations
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AI in the military
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The challenges of military AI
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6. Confronting the Challenges of AI
Strategies for developers
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Strategies for executives
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Strategies for public relations
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Strategies for regulators
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Strategies for consumers
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Glossary_AI_Accountability.zip
(89 KB)