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Epistemic Communities under Active Inference.

Mahault Albarracin1,2, Daphne Demekas3, Maxwell J D Ramstead2,4

  • 1Department of Cognitive Computing, Université du Québec a Montreal, Montreal, QC H2K 4M1, Canada.

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Summary
This summary is machine-generated.

This study models how confirmation bias fuels echo-chamber formation. Agents reinforce beliefs by seeking confirming information, making views resistant to change and solidifying epistemic communities.

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Area of Science:

  • Cognitive Science
  • Computational Neuroscience
  • Social Network Analysis

Background:

  • Information spread dynamics are crucial in the modern news ecology.
  • Individuals often form echo chambers, driven by confirmation bias.
  • Understanding these phenomena is critical for addressing misinformation.

Purpose of the Study:

  • To develop an in silico model of confirmation bias and echo-chamber formation using active inference.
  • To investigate how agents' belief-updating mechanisms contribute to self-reinforcing belief systems.
  • To explore the role of epistemic value and social network structures in community formation.

Main Methods:

  • Leveraged the active inference framework to build a computational model.
  • Simulated agents seeking information to confirm existing beliefs, leading to high certainty.
  • Developed a generative model inspired by social networks (e.g., Twitter) where agents post and observe claims.

Main Results:

  • The active inference model successfully reproduced echo-chamber formation in simulated social networks.
  • Demonstrated that high certainty in beliefs makes agents resistant to changing their views.
  • Showed that agents' attention to others' posts and network perspectives influence belief formation.

Conclusions:

  • Active inference provides a framework for understanding the cognitive underpinnings of echo chambers.
  • The model highlights how self-confirming beliefs and social interactions reinforce ingrained ideas.
  • Findings offer insights into the cognitive processes driving belief polarization and community segregation.