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.

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).

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

This section considers how people’s autonomy and free will are hindered or supported by past and present KTs. By focusing on the structural level, we will examine systemic issues such as monopolies over KTs, data extraction and colonialism, labour, and political participation.

This section analyses how different knowledge technologies impact people’s attention and, consequently, their decisions regarding which information is worth storing and remembering, and which is instead forgotten or not even registered in the first place.

This section analyses how different knowledge technologies impact people’s creativity. Here creativity is intended as the ability to express themselves in a way that is both truthful to what they feel and believe, as well as the power to experiment with artistic creation.

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

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.