Gabriel, N. and O'Connor, C. (2022)
[Preprint]
Abstract
Confirmation bias has been widely studied for its role in failures of reasoning. Individuals exhibiting confirmation bias fail to engage with information that contradicts their current beliefs, and, as a result, can fail to abandon inaccurate beliefs. But although most investigations of confirmation bias focus on individual learning, human knowledge is typically developed within a social structure. How does the presence of confirmation bias influence learning and the development of consensus within a group? In this paper, we use network models to study this question. We find, perhaps surprisingly, that moderate confirmation bias often improves group learning. This is because confirmation bias leads the group to entertain a wider variety of theories for a longer time, and prevents them from prematurely settling on a suboptimal theory. There is a downside, however, which is that a stronger form of confirmation bias can cause persistent polarization, and hurt the knowledge producing capacity of the community. We discuss implications of these results for epistemic communities, including scientific ones.
Conclusion
We find that confirmation bias, in a more moderate form, improves the epistemic performance of agents in a networked community. This is perhaps surprising given that previous work mostly emphasizes the epistemic harms of confirmation bias. By decreasing the chances that a group pre-emptively settles on a
promising theory or option, confirmation bias can improve the likelihood that the group chooses optimal options in the long run. In this, it can play a similar role to decreased network connectivity or stubbornness (Zollman, 2007, 2010; Wu, 2021). The downside is that more robust confirmation bias, where agents entirely ignore data that is too disconsonant with their current beliefs, can lead to polarization, and harm the epistemic success of a community. Our modeling results thus provide potential support for the arguments of Mercier & Sperber (2017) regarding the benefits of confirmation bias to a group, but also a caution. Too much confirmation bias does not provide such benefits.
There are several ongoing discussions in philosophy and the social sciences where these results are relevant. Mayo-Wilson et al. (2011) use network models to argue for the independence thesis—that rationality of individual agents and rationality of the groups they form sometimes come apart. I.e., individually rational agents may form groups which are not ideally rational, and rational groups may sometimes consist in individually irrational agents. Our results lend support to this claim. While there is a great deal of evidence suggesting that confirmation bias is not ideal for individual reasoners, our results suggest that it can nonetheless improve group reasoning under the right conditions.
The authors conclude that confirmation bias can have both positive and negative effects on group learning. The key is to find a moderate level of confirmation bias that allows the group to explore a variety of theories without becoming too polarized.
Here are some of the key findings of the paper:
- Moderate confirmation bias can improve group learning by preventing the group from prematurely settling on a suboptimal theory.
- Too much confirmation bias can lead to polarization and a decrease in the group's ability to learn.
- The key to effective group learning is to find a moderate level of confirmation bias.
