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

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.

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.

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.

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.