Displaying 4 resources
Article/Books/eBooks Article/Books/eBooks

STRATEGIC RESEARCH & INNOVATION ROADMAP OF TRUSTWORTHY AI

This document is the first version of the Strategic Research and Innovation Roadmap of the TAILOR project, focussed on Trustworthy Artificial Intelligence through Learning, Optimization and Reasoning.

Category
Cooperation with partners, Multistakeholder dialogue, Support guidance in the responsible implementation of ADR, Understanding of the fundamental rights and values, Best practices in deployment, Legal framework and regulation, Recommendations towards policy changes, Standards, Trustworthiness
Target audience
ADR Experts and Associations, Policy Makers, Private Sector, Researchers and Academic
Source
Adra-e
Article/Books/eBooks Article/Books/eBooks
Professional development resources for teachers/educators Professional development resources for teachers/educators

Handbook of Trustworthy AI

The main goal of the Handbook of Trustworthy AI (HTAI) is to provide to non-experts, researchers and students, an overview of the problem related to the developing of ethical and trustworthy AI systems.

Category
Multistakeholder dialogue, Support guidance in the responsible implementation of ADR, Understanding of the fundamental rights and values, Best practices in deployment, Legal framework and regulation, Trustworthiness
Target audience
ADR Experts and Associations, Policy Makers, 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
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