Thematic report
This report examines research on the properties of AI systems (specifically machine learning algorithms) and their embeddedness in online content governance systems.
How is ‘artificial intelligence’ (AI) defined, and what are the relationships between AI systems development and internationally protected human rights?
What are the relationships between AI systems development and internationally protected human rights?
What are the interdependencies between AI systems development, the use of automated tools and democratic processes?
The analysis covers the relationships between AI systems and human rights, AI systems use and content governance (generation and moderation), and how these developments are related to changes in democracy, societal resilience and cohesion.
It shows how:
The report also highlights the contribution of AI systems to changes in information ecosystems with a section on AI in the news media industry. The governance of legacy and online news media is examined in this report (chapter 6) and this report (chapter 7), and the role of non-mainstream news media is examined in this report (chapter 8).
Thematic reports
This chapter begins with an introduction that frames the central themes of the report, covers the key concepts and definitions, delves into the challenges facing democracies focusing on mis- and disinformation, acknowledges the limitations of the report and provides an outline of the report.
What does research tell us about changes in legacy and online news media and what can be done to promote information integrity and a democratic public sphere?
What does research tell us on the power of big tech companies and approaches to governing data extraction and use and influences on political deliberation?
What does research tell us about changes in legacy and online news media and what can be done to promote information integrity and a democratic public sphere?
What does research tell us about changes in legacy and online news media and what can be done to promote information integrity and a democratic public sphere?
What does research tell us on specific measures to combat mis- and disinformation by civil society organizations and governments?
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2025 - Observatory on Information & Democracy
This map represents a statistical summary of the thematic content of the report. The network graph represents relations between the words in the report, placing them closer to each other the more they are related. The bigger the node, the more present the word is, signalling its role in defining what the report is about. The colors represent words that are closely related to each other and can be interpreted as a topic.
The map is generated by the OID using GarganText – developed by the CNRS Institute of Complex Systems –on the basis of the repot’s text. Starting from a co-occurrence matrix generated from report’s text, GarganText forms a network where words are connected if they are likely to occur together. Clustering is conducted based on the Louvain community detection method, and the visualisation is generated using the Force Atlas 2 algorithm.