Contributed Talk Sessions | Poster Sessions | All Posters | Search Papers

Poster Session B: Wednesday, August 13, 1:00 – 4:00 pm, de Brug & E‑Hall

Biased Misinformation Distorts Beliefs

Juan Vidal-Perez¹, Raymond Dolan, Rani Moran²; ¹University College London, University of London, ²Queen Mary, University of London

Presenter: Rani Moran

Misinformation, particularly biased news, poses a growing threat to open societies by driving polarization and reinforcing false beliefs. This study explores how individuals process biased information through a reinforcement learning task. Participants (n=200) took part in a "bandit task," receiving feedback from biased (favorable, unfavorable) and unbiased sources. They first learned about the biases of these sources, then used this knowledge to adjust their belief updating. Although participants could identify and account for bias, their corrections were incomplete, leaving residual distortions in their beliefs. Exposure to biased sources also led participants to perceive unbiased sources as biased. These results underscore the difficulty of maintaining accurate beliefs in biased environments and offer strategies for combating misinformation.

Topic Area: Reward, Value & Social Decision Making

Extended Abstract: Full Text PDF