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.

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

Companies have significant influence over public discourse in online platforms, necessitating that the algorithms that shape these online platforms should be regulated and constrained to sufficiently consider the public interest (Susskind, 2018: 350).

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.

The source, which comprises excerpts from Module A of the KT4D Social Risk Toolkit, explores the complex challenge presented by artificial intelligence to individual autonomy and free will within modern society.