Displaying 14 resources
Video/Webinars Video/Webinars

Explainable AI for systems with functional safety requirements

Explainable AI (XAI) is vital for making AI decision-making processes transparent and understandable to human experts, and for ensuring safety and regulatory compliance.
Category
Certification and Compliance, Trustworthiness
Target audience
ADR Experts and Associations, Private Sector, Researchers and Academic
Source
Adra-e
Article/Books/eBooks Article/Books/eBooks

Don’t ask if AI is good or fair, ask how it shifts power

Opinion piece by Pratyusha Kalluri in Nature
Category
Support guidance in the responsible implementation of ADR, Understanding of the fundamental rights and values
Target audience
ADR Experts and Associations, Individual Citizens/Members of the Society, Policy Makers, Researchers and Academic
Source
Adra-e
Other Other

Is ethical AI possible?

An interview with Timnit Gebru, the founder of the Distributed AI Research Institute.
Category
Support guidance in the responsible implementation of ADR, Understanding of the fundamental rights and values
Target audience
ADR Experts and Associations, Individual Citizens/Members of the Society, Researchers and Academic
Source
Adra-e
Article/Books/eBooks Article/Books/eBooks

Pygmalion Displacement: When Humanising AI Dehumanises Women

Paper exploring the relationship between women and AI.
Category
Support guidance in the responsible implementation of ADR, Understanding of the fundamental rights and values
Target audience
ADR Experts and Associations, Researchers and Academic
Source
Adra-e
Article/Books/eBooks Article/Books/eBooks

Generative AI and Research Integrity

The article critically reviews the use of generative AI is research.
Category
Support guidance in the responsible implementation of ADR, Understanding of the fundamental rights and values
Target audience
Researchers and Academic
Source
Adra-e
Article/Books/eBooks Article/Books/eBooks

An overview of key trustworthiness attributes and KPIs for trusted ML-based systems engineering

When deployed, machine-learning (ML) adoption depends on its ability to actually deliver the expected service safely, and to meet user expectations in terms of quality and continuity of service.
Category
Support guidance in the responsible implementation of ADR
Target audience
ADR Experts and Associations, Policy Makers, Private Sector, Public Sector, Researchers and Academic
Source
Adra-e