The my-side bias is a well-documented cognitive bias in the evaluation of arguments, in which reasoners in a discussion tend to overvalue arguments that confirm their prior beliefs, while undervaluing arguments that attack their prior beliefs. The first part of this paper develops and justifies a Bayesian model of myside bias at the level of individual reasoning. In the second part, this Bayesian model is implemented in an agent-based model of group discussion among myside-biased agents. The agent-based model is then (...) used to perform a number of experiments with the objective to study whether the myside bias hinders or enhances the ability of groups to collectively track the truth, that is, to reach the correct answer to a given binary issue. An analysis of the results suggests the following: First, whether the truth-tracking ability of groups is helped or hindered by myside bias crucially depends on how the strength of myside bias is differentially distributed across subgroups of discussants holding different beliefs. Second, small groups are more likely to track the truth than larger groups, suggesting that increasing group size has a detrimental effect on collective truth-tracking through discussion. (shrink)

The English language now dominates scientific communications. Yet, many scientists have English as their second language. Their English proficiency may therefore often be more limited than that of a ‘native speaker’, and their scientific contributions (e.g. manuscripts) in English may frequently contain linguistic features that disrupt the fluency of a reader’s, or listener’s information processing even when the contributions are understandable. Scientific gatekeepers (e.g. journal reviewers) sometimes cite these features to justify negative decisions on manuscripts. Such justifications may rest on (...) the prima facie plausible assumption that linguistic characteristics that hinder fast and easy understandability of scientific contributions are epistemically undesirable in science. I shall raise some doubts about this assumption by drawing on empirical research on processing fluency and its biasing effects. I also argue that directing scientists with English as a foreign language toward approaching ‘native-level’ English can have the negative consequence of reducing their potential to make scientific belief formation more reliable. These points suggest that one seemingly compelling justification for linguistically discriminating against scientific contributions in ‘non-native’ English is questionable and that the common insistence by scientific gatekeepers on ‘native-like’ English may be epistemically harmful to science. (shrink)

Does algorithmic political bias contribute to an entrenchment and polarization of political positions? Franke argues that it may do so because the bias involves classifications of people as liberals, conservatives, etc., and individuals often conform to the ways in which they are classified. I provide a novel example of this phenomenon in human–computer interactions and introduce a social psychological mechanism that has been overlooked in this context but should be experimentally explored. Furthermore, while Franke proposes that algorithmic political classifications entrench (...) political identities, I contend that they may often produce the opposite result. They can lead people to change in ways that disconfirm the classifications. Consequently and counterintuitively, algorithmic political bias can in fact decrease political entrenchment and polarization. (shrink)

The social epistemology of science would benefit from paying more attention to the nature of argumentative exchanges. Argumentation is not only a cognitive activity but a collaborative social activity whose functioning needs to be understood from a psychological and communicative perspective. Thus far, social and organizational psychology has been used to discuss how social diversity affects group deliberation by changing the mindset of the participants. Argumentative exchanges have comparable effects, but they depend on cognitive diversity and emerge through critical interaction. (...) An example of a cognitive psychological theory is discussed that explains how mutual reasoning affects how we think, make decisions, and solve problems, as well as how cognitive biases may facilitate an efficient division of cognitive labor. These observations are compared with the existing results in the social epistemology of science. Moreover, I explicate the conceptual differences between the distributed and social processing of information. While argumentative exchanges belong to the latter domain, most existing simulations model distributed processing, which may compromise their real-world relevance and proper conceptual interpretation. However, I aim not to criticize the existing simulation methods but to promote an approach from the cognitive psychology of reasoning that complements the current use of organizational psychology and computer simulations by investigating a different set of mechanisms relating to similar phenomena of interest in the social epistemology of science. (shrink)

Human behavior and thought often exhibit a familiar pattern of within group similarity and between group difference. Many of these patterns are attributed to cultural differences. For much of the history of its investigation into behavior and thought, however, cognitive science has been disproportionately focused on uncovering and explaining the more universal features of human minds—or the universal features of minds in general. -/- This entry charts out the ways in which this has changed over recent decades. It sketches the (...) motivation behind the cultural turn in cognitive science, and situates some of its central findings with respect to the questions that animate it and the debates that it has inspired. Woven throughout the entry are examples of how the cognitive science of culture, and especially its elevated concern with different forms of diversity and variation, continues to influence and be influenced by philosophers. -/- One cluster of philosophical work falls within the traditional subject matter of philosophy of science, in this case of the cognitive and social sciences. Philosophers have analyzed and assessed the methods and evidence central to the scientific study of cognition and culture, and have offered conceptual scrutiny, clarification, and synthesis. Research in a second vein sees philosophers themselves contributing more directly to cognitive scientific projects, (co)constructing theories, helping build computational models, even gathering empirical data. A third kind of work is naturalistic philosophy or philosophy of nature, wherein philosophers seek to use results from the cognitive science of culture to inform or transform debates over long-standing philosophical questions, including questions about the nature of philosophy and philosophical methodology itself. (shrink)

After introducing the new field of cultural evolution, we review a growing body of empirical evidence suggesting that culture shapes what people attend to, perceive and remember as well as how they think, feel and reason. Focusing on perception, spatial navigation, mentalizing, thinking styles, reasoning (epistemic norms) and language, we discuss not only important variation in these domains, but emphasize that most researchers (including philosophers) and research participants are psychologically peculiar within a global and historical context. This rising tide of (...) evidence recommends caution in relying on one’s intuitions or even in generalizing from reliable psychological findings to the species, Homo sapiens. Our evolutionary approach suggests that humans have evolved a suite of reliably developing cognitive abilities that adapt our minds, information-processing abilities and emotions ontogenetically to the diverse culturally-constructed worlds we confront. (shrink)

Ainslie's account of willpower is conspicuously individualistic. Because other people, social influence, and culture appear only peripherally, it risks overlooking what may be resolve's deeply social roots. We identify a general “outside-in” explanatory strategy suggested by a range of recent research into human cognitive evolution, and suggest how it might illuminate the origins and more social aspects of resolve.

The broad spectrum revolution brought greater dependence on skill and knowledge, and more demanding, often social, choices. We adopt Sterelny's account of how cooperative foraging paid the costs associated with longer dependency, and transformed the problem of skill learning. Scaffolded learning can facilitate cognitive control including suppression, whereas scaffolded exchange and trade, including inter-temporal exchange, can help develop resolve.

When scientists or science reporters communicate research results to the public, this often involves ethical and epistemic risks. One such risk arises when scientific claims cause cognitive or behavioural changes in the audience that contribute to the self-fulfilment of these claims. I argue that the ethical and epistemic problems that such self-fulfilment effects may pose are much broader and more common than hitherto appreciated. Moreover, these problems are often due to a specific psychological phenomenon that has been neglected in the (...) research on science communication: many people tend to conform to ‘descriptive norms’, that is, norms capturing (perceptions of) what others commonly do, think, or feel. Because of this tendency, science communication may frequently produce significant social harm. I contend that scientists have a responsibility to assess the risk of this potential harm and consider adopting strategies to mitigate it. I introduce one such strategy and argue that its implementation is independently well motivated by the fact that it helps improve scientific accuracy. (shrink)

I introduce and discuss an underappreciated form of motivated cognition: motivational pessimism, which involves the biasing of beliefs for the sake of self-motivation. I illustrate how motivational pessimism avoids explanatory issues that plague other (putative) forms of motivated cognition and discuss distinctions within the category, related to awareness, aetiology, and proximal goals.

The "myside bias'' in evaluating arguments is an empirically well-confirmed phenomenon that consists of overweighting arguments that endorse one's beliefs or attack alternative beliefs while underweighting arguments that attack one's beliefs or defend alternative beliefs. This paper makes two contributions: First, it proposes a probabilistic model that adequately captures three salient features of myside bias in argument evaluation. Second, it provides a Bayesian justification of this model, thus showing that myside bias has a rational Bayesian explanation under certain conditions.

It has recently been suggested that politically motivated cognition leads progressive individuals to form beliefs that underestimate real differences between social groups and to process information selectively to support these beliefs and an egalitarian outlook. I contend that this tendency, which I shall call ‘egalitarian confirmation bias’, is often ‘Mandevillian’ in nature. That is, while it is epistemically problematic in one’s own cognition, it often has effects that significantly improve other people’s truth tracking, especially that of stigmatized individuals in academia. (...) Due to its Mandevillian character, egalitarian confirmation bias isn’t only epistemically but also ethically beneficial, as it helps decrease social injustice. Moreover, since egalitarian confirmation bias has Mandevillian effects especially in academia, and since progressives are particularly likely to display the bias, there is an epistemic reason for maintaining the often-noted political majority of progressives in academia. That is, while many researchers hold that diversity in academia is epistemically beneficial because it helps reduce bias, I argue that precisely because political diversity would help reduce egalitarian confirmation bias, it would in fact in one important sense be epistemically costly. (shrink)

Nudges are a way to steer people’s behavior through changes in how choices are presented. Nudge research has been incorporated into public policy in many countries, and nudge research, thus, has the potential to directly influence societies and individuals. As a result, research ethics for nudge research is needed to ensure that nudges developed are not instances of unethical manipulation of people. In this paper, I argue that two types of slippery slopes from ethically fine nudges to ethically problematic ones (...) can take place in nudge research. The conceptual slippery slope follows from (1) the broad way of defining nudges, (2) the multitude of different ways of understanding manipulation of people, (3) many manipulation definitions implying that some nudges are manipulative, and (4) some forms of manipulation of people being prima facie wrong. The empirical slippery slope rests, first, on the possibility of small steps from ethically acceptable to wrong nudges, and second, on the cognitive limits typical to human beings (including nudge researchers). Both slippery slope arguments imply the need to of nudge researchers to create so-called firebreaks. The firebreaks can take the form of ethical justifications. To avoid slippery slopes, certain types of arguments should be excluded from these justifications. (shrink)

In 2021, 193 Member States at UNESCO’s General Conference adopted the Recommendation on the Ethics of Artificial Intelligence as the first important step towards a future global standard-setting instrument on the subject. The text reflects an emerging consensus among the international community about the growing ethical concerns with artificial intelligence (AI). Among these concerns are also serious risks and dangers attributed to the manipulative effects of AI, which can be further exacerbated by the creative combination of AI with other innovative (...) technologies or applications, such as brain–computer interfaces (BCIs), functional magnetic resonance imaging (fMRI), robotics, and big data. The risks for individuals and society as a whole caused by manipulation through AI are already well known and have recently also been addressed by the European Union having released a proposal for an Artificial Intelligence Act (AIA). Among multiple risks related to AI, the AIA singles out the specific dangers related to AI systems that deploy “subliminal techniques beyond a person’s consciousness to materially distort a person’s behaviour in a manner that causes or is likely to cause that person or another person physical or psychological harm”. The present article thus aims to highlight the known and potential dangers related to AI systems manipulating human thoughts and behaviour through subliminal and supraliminal means and methods. To this end, it advocates the joint study of law and the senses captured by the concept of legal synaesthesia to correspond to the need for an interdisciplinary debate covering the complexity of the links between AI, related technologies, human perception based on the senses and the mind, as well as the role and instruments of law in the future organization of societies in this world. (shrink)