Displaying 32 resources
Online Course Online Course

Certificate in Ethical Artificial Intelligence (AI)

Why study this course?

Category
Support guidance in the responsible implementation of ADR, Understanding of the fundamental rights and values, Certification and Compliance
Target audience
ADR Experts and Associations, Private Sector, Researchers and Academic
Source
Adra-e
Certification Certification

VCIO based description of systems for AI trustworthiness characterisation

This VDE SPEC provides a way to describe certain socio-technical characteristics of systems and applications that incorporate artificial intelligence techniques and methods.
Category
Support guidance in the responsible implementation of ADR, Understanding of the fundamental rights and values, Best practices in deployment, Certification and Compliance, Legal framework and regulation, Standards, Trustworthiness
Target audience
ADR Experts and Associations, Private Sector, Researchers and Academic
Source
Adra-e
Article/Books/eBooks Article/Books/eBooks
Certification Certification
Professional development resources for teachers/educators Professional development resources for teachers/educators

Labelling initiatives, codes of conduct and other self-regulatory mechanisms for artificial intelligence applications

AI has emerged as a critical area of interest to numerous stakeholders across the world.

Category
Support guidance in the responsible implementation of ADR, Understanding of the fundamental rights and values, Policy, Regulation, Certificates, and Standards, Best practices in deployment, Certification and Compliance, Legal framework and regulation, Recommendations towards policy changes, Standards, Trustworthiness
Target audience
ADR Experts and Associations, Private Sector, Researchers and Academic
Source
Adra-e
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

Adaptable robots, ethics, and trust: a qualitative and philosophical exploration of the individual experience of trustworthy AI

Open Access paper exploring issues of trust and trustworthiness in relation to technologies
Category
Trustworthiness
Target audience
ADR Experts and Associations, Individual Citizens/Members of the Society, Researchers and Academic
Source
Adra-e
Article/Books/eBooks Article/Books/eBooks

Digital environment – Version 1.0

This is deliverable 1.2 of the AI4REALNET project.
Category
Action and Interaction Technologies, Experiment and Deployment, Reasoning and decision-making Technologies
Target audience
ADR Experts and Associations, Private Sector, Researchers and Academic
Source
Adra-e
Article/Books/eBooks Article/Books/eBooks

AI fundamental blocks – beta release

This is the deliverable 2.2 of the AI4REALNET project. This work package objective consists on developing the AI fundamental blocks for augmented decision-making, namely novel AI algorithms for large-scale sequential decision-making problems.
Category
Action and Interaction Technologies, Data for AI, Experiment and Deployment, Reasoning and decision-making Technologies
Target audience
ADR Experts and Associations, Private Sector, Researchers and Academic
Source
Adra-e
Certification Certification
Online Course Online Course
Video/Webinars Video/Webinars

Webinar "Distributed and Hierarchical Reinforcement Learning"

Category
Action and Interaction Technologies, Data for AI, Systems, methodologies, hardware, and tools, Reasoning and decision-making Technologies
Target audience
ADR Experts and Associations, Policy Makers, Private Sector, Public Sector, Researchers and Academic
Source
Adra-e
Certification Certification
Online Course Online Course
Video/Webinars Video/Webinars

Webinar "Industry-driven Use Cases"

Category
Action and Interaction Technologies, Data for AI, Systems, methodologies, hardware, and tools, Reasoning and decision-making Technologies
Target audience
ADR Experts and Associations, Individual Citizens/Members of the Society, Policy Makers, Private Sector, Public Sector, Researchers and Academic
Source
Adra-e
Video/Webinars Video/Webinars

Webinar "Towards Transparent, Safe and Trustworthy AI for critical infrastructures"

This webinar focuses on the development of safe, explainable, and algorithmically transparent methods as part of the AI4REALNET project.
Category
Action and Interaction Technologies, Data for AI, Reasoning and decision-making Technologies, Sensing and perception technologies, Systems, methodologies, hardware, and tools
Target audience
ADR Experts and Associations, Policy Makers, Private Sector, Public Sector, Researchers and Academic
Source
Adra-e
Video/Webinars Video/Webinars

Webinar Towards Transparent, Safe and Trustworthy AI for critical infrastructures

This webinar focuses on the development of safe, explainable, and algorithmically transparent methods as part of the AI4REALNET project.

Category
Action and Interaction Technologies, Data for AI, Reasoning and decision-making Technologies, Sensing and perception technologies, Systems, methodologies, hardware, and tools
Target audience
ADR Experts and Associations, Policy Makers, Private Sector, Public Sector, Researchers and Academic
Source
Adra-e