Module B focuses on the risks AI poses for social fairness and trust: how the use of AI-based tools can generate inequality or dishonesty, particularly when human productions differ in nature (e.g. creative vs.

This document examines how AI-driven content curation and recommendation systems affect the quality of public deliberation.

This interactive explainer introduces the concept of AI-generated deepfake images and provides clues to help the user understand how and why they are created.

The experimental component of Module A aims to further characterise internet users' behaviours when faced with online choices potentially undermining their autonomy: how people evaluate AI-generated information and/or content selected through AI-based algorithms, and how people are influenced by

This policy brief focuses on short-term action (2026-2028) around AI governance and provides practical guidelines for experts and policymakers. It introduces a framework that embeds democratic pillars — participation, freedom, equality, transparency, knowledge, and the rule of law — directly into the entire AI lifecycle.

The aim of the first three modules of KT4D’s Social Risk Toolkit thus focuses on the individual aspects of this challenge and is multifaceted.

This document examines autonomy as a form of agentive control grounded in attention regulation, goal-directed action, and reflexivity.