Confirmation bias in the age of AI: Examining the role of information source and conclusive recommendations

In an era where artificial intelligence (AI) increasingly mediates information access, understanding its influence on cognitive biases is critical. This research examines whether information source (AI vs. human) and the presence of conclusive recommendations shape confirmation bias across six studies, using both information evaluation and selection paradigms. Across studies, participants consistently exhibited confirmation bias. At the aggregate level, information source did not produce a reliable effect, with similar levels of bias observed for AI-generated and human-provided information. In contrast, the presence of conclusive recommendations consistently amplified confirmation bias, whereas their absence mitigated it. These findings suggest that the structure of information, rather than its source, plays a central role in shaping biased information processing. These results have important implications for the design of AI systems and information environments aimed at reducing cognitive biases in decision-making. • This research examined how information source (AI vs. human) and conclusive recommendations shape confirmation bias. • Across three novel scenarios and one established paradigm, confirmation bias emerged consistently. • Confirmation bias was comparable for AI-generated and human-provided information. • Conclusive recommendations amplified confirmation bias, whereas their absence mitigated it.

Authors

Institutions

Publication Details

Journal
Computers in Human Behavior Reports
Published
2026-04-01
DOI
https://doi.org/10.1016/j.chbr.2026.101047
Primary Topic
Decision-Making and Behavioral Economics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Confirmation bias in the age of AI: Examining the role of information source and conclusive recommendations

Guibing He, Chenchen Zhu, Zhiqin Chen, Hongzhou Xuan
Computers in Human Behavior Reports
Decision-Making and Behavioral Economics
article

Confirmation bias in the age of AI: Examining the role of information source and conclusive recommendations

Guibing He, Chenchen Zhu, Zhiqin Chen, Hongzhou Xuan
article en

Abstract

In an era where artificial intelligence (AI) increasingly mediates information access, understanding its influence on cognitive biases is critical. This research examines whether information source (AI vs. human) and the presence of conclusive recommendations shape confirmation bias across six studies, using both information evaluation and selection paradigms. Across studies, participants consistently exhibited confirmation bias. At the aggregate level, information source did not produce a reliable effect, with similar levels of bias observed for AI-generated and human-provided information. In contrast, the presence of conclusive recommendations consistently amplified confirmation bias, whereas their absence mitigated it. These findings suggest that the structure of information, rather than its source, plays a central role in shaping biased information processing. These results have important implications for the design of AI systems and information environments aimed at reducing cognitive biases in decision-making. • This research examined how information source (AI vs. human) and conclusive recommendations shape confirmation bias. • Across three novel scenarios and one established paradigm, confirmation bias emerged consistently. • Confirmation bias was comparable for AI-generated and human-provided information. • Conclusive recommendations amplified confirmation bias, whereas their absence mitigated it.

Computers in Human Behavior ReportsVol. 22
Zhejiang Gongshang University (CN), Zhejiang University (CN)
National Natural Science Foundation of China
Peace, Justice and strong institutions
Openalex Percentile: Top 41%
Decision-Making and Behavioral Economics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.