AI Explainability in Practice_UK_2024

2024

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AI-generated summary

1) This participant workbook from The Alan Turing Institute provides public sector practitioners with a practical governance framework and workshop activities to operationalize AI explainability, transparency, and accountability.
2)
- Defines key concepts, maxims of AI explainability, and six main explanation types (rationale, responsibility, data, fairness, safety, and impact).
- Outlines an Explainability Assurance Management process with six actionable tasks across the AI project lifecycle.
- Includes an interactive case study and activities focused on applying explainability principles to AI use in children's social care.
3) Tags: artificial intelligence, explainability, governance, ethics, public sector

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