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.

Recipe series. 1st describing DITL

This recipe is about designing an entire democratic process—not just the AI tool within it. When AI is introduced into a deliberative setting, the surrounding process needs to change too: not just to make the AI work, but to make sure the democracy works.

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.

The purpose of this document is to provide an overview of how AI, big data and frontier technologies impact rights from the data protection perspective.

Module C of the Toolkit has two primary objectives: First, to understand AI and big data within the context of a long history of interactions between technological affordances and cultural norms, values, and practices. This recognises that knowledge technologies—such as written language, the printing press, television, radio, etc.—have shaped culture and knowledge production. The relationship between technology and culture is fundamentally mutual and reciprocal. Second, building upon the first objective, Module C focuses on the particular definition of AI and big data as advanced knowledge technologies (AKTs). We analyse the past in this module to better understand the present and—potentially—to anticipate what may lie ahead.

The policy brief published by KT4D suggests that examining culture allows for a deeper understanding of societal responses to AI development.