Thematic report

Big Tech and Governing Uses of Data (chapter 4)

News Media, Information Integrity and the 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?

  • This report reveals injustices associated with the interplay of data extraction and data brokering.
  • It underscores the role of monopolistic actors and digital platforms in shaping data production and governance, replicating injustices and exacerbating inequalities.
  • It explores how permissive legislation and platforms business models fuel mis- and disinformation, global data dependencies, and exploitative online labor markets.
  • It highlights resistance strategies from Global Majority World countries while addressing their vulnerability to misinformation campaigns and datafication harmful consequences, and calls for more research into these phenomena.

 

Thematic reports

Other chapters

Information ecosystems and democracy (chapter 1)

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.

News Media, Information Integrity and the Public Sphere (chapter 2)

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?

  • The analysis shows how platform dominance and advertizing market concentration impact news media finances and public trust, with variations across countries. 
  • It highlights inconsistent findings on mis- and disinformation and urges to strengthen news organizations’ bargaining power. 
  • The study emphasizes government roles in information manipulation and the protective role of filter bubbles for marginalized groups. 
  • It calls for global studies on media trust, polarization, and news sustainability.

Artificial Intelligence, Information Integrity and Democracy (chapter 3)

What does research tell us on the properties of AI systems (machine learning algorithms), their role in content governance, and internationally protected human rights?

  • This report examines how AI development intersects with safeguarding human rights, emphasizing states’ responsibilities to address challenges from new actors, tools, and power dynamics.
  • It underscores the inevitability of bias in AI systems, the need for transparency in algorithms and data, and the risks of AI-driven content governance.
  • It highlights that effective content moderation requires multifaceted, ethical, and transparent approaches with legal frameworks geared towards accountability, and the regulation of personalization systems.
  • It calls for research on regional human rights applications, data diversity, independent algorithmic audits, and addressing emerging AI divides.

Awareness of Mis- and Disinformation and the Literacy Challenge (chapter 5)

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?

  • The analysis shows how platform dominance and advertizing market concentration impact news media finances and public trust, with variations across countries. 
  • It highlights inconsistent findings on mis- and disinformation and urges to strengthen news organizations’ bargaining power. 
  • The study emphasizes government roles in information manipulation and the protective role of filter bubbles for marginalized groups. 
  • It calls for global studies on media trust, polarization, and news sustainability.

Governing Information Ecosystems: Legislation and Regulation (chapter 6)

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?

  • The analysis shows how platform dominance and advertizing market concentration impact news media finances and public trust, with variations across countries. 
  • It highlights inconsistent findings on mis- and disinformation and urges to strengthen news organizations’ bargaining power. 
  • The study emphasizes government roles in information manipulation and the protective role of filter bubbles for marginalized groups. 
  • It calls for global studies on media trust, polarization, and news sustainability.

Combating Mis- and Disinformation in Practice (chapter 7)

What does research tell us on specific measures to combat mis- and disinformation by civil society organizations and governments?

  • This report highlights the risks to human rights posed by some measures against mis- and disinformation, emphasizing the need for diverse, context-sensitive approaches rather than a single solution. 
  • It calls for balancing economic growth, innovation, and human rights protections while avoiding regulatory overreach, particularly by authoritarian regimes. 
  • It underscores the limitations of overrelying on technical tools and stresses the need for adaptable practices like fact-checking. 
  • It also highlights global differences in protecting press freedom and countering disinformation, urging research with real-world data beyond the Global North and mixed methods to capture diverse experiences, and monitor platform practices that suppress dissenting voices.

Big Tech and Governing Uses of Data (chapter 4) – Interactive Map

Developed using GarganText by the OID in partnership with CNRS Institute for Complex Systems.

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.