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

The Recommendation Algorithms explainer aims to demonstrate how algorithms work on social media platforms. It allows the users to simulate their experience on a social media platform, where their choices shape a personalised feed.