Epistemic advantage on the margin: A network standpoint Epistemology

Wu, Jingyi

doi:10.1111/phpr.12895

Cited by 14 publications

(15 citation statements)

References 45 publications

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“…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(Zollman, , 2010Wu, 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.…”

Section: Discussionmentioning

confidence: 99%

“…Echo chambers function when individuals seek out and connect to friends and peers who share their beliefs (see also modeling work by Baldassarri & Bearman (2007)). Wu (2021) finds polarization arises when entire groups mistrust other groups based on social identity. O 'Connor & Weatherall (2018), as noted, find that polarization emerges when actors do not trust data from peers who hold different beliefs.…”

Section: Discussionmentioning

confidence: 99%

“…Reflecting some of our results, though, they find that devaluation at a low level is not harmful, but at a higher level eventually causes polarization. Wu (2021) presents models where a dominant group devalues or ignores information coming from a marginalized group. Wu's model (again) can yield stable polarization under conditions in which this devaluation is very strong.…”

Section: Previous Modelsmentioning

confidence: 99%

“…To summarize, this model represents a social learning scenario where members of a community 1) attempt to figure out which of two actions/options/beliefs is more successful, 2) use their current beliefs to guide their data gathering practices, and 3) share data with each other. This is often taken as a good model of scientific theory development (Zollman, 2010;Holman & Bruner, 2015;Kummerfeld & Zollman, 2015;Frey & Šešelja, 2020) or the emergence of social consensus/beliefs more broadly (O'Connor & Weatherall, 2018;Wu, 2021;Fazelpour & Steel, in press).…”

Section: Base Modelmentioning

confidence: 99%

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Can Confirmation Bias Improve Group Learning?

O’Connor¹,

Gabriel²

2022

Preprint

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Previous Modelsmentioning

confidence: 99%

Section: Base Modelmentioning

confidence: 99%

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Can Confirmation Bias Improve Group Learning?

O’Connor¹,

Gabriel²

2022

Preprint

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“…29 Now let us turn to mechanisms that lead to transient diversity, but that have not been associated with explicit policy proposals. These include testimonial injustice (Wu, 2022a), industrial proprietary science (Wu, 2022b), confirmation bias (Gabriel & O'Connor, 2021), and intransigence (Zollman, 2010). In these cases we have good reasons to believe that these factors are widely present in many epistemic communities.…”

Section: Mechanisms For Transient Diversitymentioning

confidence: 99%

How should we promote transient diversity in science?

O’Connor

2023

Synthese

Self Cite

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Diversity of practice is widely recognized as crucial to scientific progress. If all scientists perform the same tests in their research, they might miss important insights that other tests would yield. If all scientists adhere to the same theories, they might fail to explore other options which, in turn, might be superior. But the mechanisms that lead to this sort of diversity can also generate epistemic harms when scientific communities fail to reach swift consensus on successful theories. In this paper, we draw on extant literature using network models to investigate diversity in science. We evaluate different mechanisms from the modeling literature that can promote transient diversity of practice, keeping in mind ethical and practical constraints posed by real epistemic communities. We ask: what are the best ways to promote an appropriate amount of diversity of practice in scientific communities?

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Risk, Rationality and (Information) Resistance: De-rationalizing Elite-Group Ignorance

Yong

2023

Erkenn

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There has been a movement aiming to teach agents about their privilege by making the information about their privilege as costless as possible. However, some argue that in risk-sensitive frameworks, such as Lara Buchak's (2013), it can be rational for privileged agents to shield themselves from learning about their privilege, even if the information is costless and relevant. This threatens the efficacy of these information-access efforts in alleviating the problem of elite-group ignorance.In response, I show that even within the same framework, in this case David Kinney and Liam Kofi Bright's (2021), the rationality of this information avoidance rests on shaky ground in practice. In this framework, whether an agent should avoid information depends on the precise details of (1) how relevant they expect the information to be, (2) their priors about the value of various options, and (3) their risk attitudes. The model suggests that rationality of elite-group ignorance is a function of structural factors that are pervasive but nonetheless not insurmountable, thus offering a way out of pessimism about elite group education.

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Epistemic advantage on the margin: A network standpoint Epistemology

Cited by 14 publications

References 45 publications

Can Confirmation Bias Improve Group Learning?

Can Confirmation Bias Improve Group Learning?

How should we promote transient diversity in science?

Risk, Rationality and (Information) Resistance: De-rationalizing Elite-Group Ignorance

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