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Week 5: Transparency and explainability
Week 5: Transparency and explainability
AI transparency
AI transparency
AI transparency helps people access information to better understand how an artificial intelligence (AI) system was created and how it makes decisions.
Alongside explanation (see below), transparency is crucial in ethics because it is central to the practice of giving reasons to one another; to recognizing the moral agency of those with whom we engage.
AI explainability
AI explainability
General
Explainable artificial intelligence (XAI) is a set of processes and methods that allows human users to comprehend and trust the results and output created by machine learning algorithms.
Case study: GDPR compliance
Case study: GDPR compliance
Explanation in philosophy
Explanation in philosophy
Why
Example-based explanations
Reliabilist epistemology
Reliabilist epistemology
Preservation of human oversight and control
Preservation of human oversight and control
Examples
Reason
Options for human involvement
Options for human involvement
Types
Need for discretion in decision-making
Need for discretion in decision-making
Reason
Case study: Sale and Supply of Alcohol Act 2012
Case study: Sale and Supply of Alcohol Act 2012
Empathy, emotion, and engagement in data
Empathy, emotion, and engagement in data
Accountability for AI misdemeanors
Accountability for AI misdemeanors
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