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AI assurance : towards trustworthy, explainable, safe, and ethical AI /
AI Assurance: Towards Trustworthy, Explainable, Safe, and Ethical AI provides readers with solutions and a foundational understanding of the methods that can be applied to test AI systems and provide assurance. Anyone developing software systems with intelligence, building learning algorithms, or de...
| Clasificación: | Libro Electrónico |
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| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Amsterdam :
Academic Press,
2022.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- 1. An introduction to AI assurance 2. Setting the goals for ethical, unbiased and fair AI 3. An overview of explainable and interpretable AI 4. Bias, Fairness, and assurance in AI: Overview and Synthesis 5. An evaluation of the potential global impacts of AI assurance 6. The role of inference in AI: start S.M.A.L.L. with mindful models 7. Outlier detection using AI: a survey 8. AI assurance using casual inference: application to public policy 9. Data collection, wrangling and preprocessing for AI assurance 10. Coordination-aware assurance for end-to-end machine learning systems: the R3E approach 11. Assuring AI methods for economic policymaking 12. Panopticon implications of ethical AI: equity, disparity, and inequality in healthcare 13. Recent advances in uncertainty quantification methods for engineering problems 14. Socially responsible AI assurance in precision agriculture for farmers and policymakers 15. The application of AI assurance in precision farming and agricultural economics 16. Bringing dark data to light with AI for evidence-based policy making