Confidence matching in group decision-making

Unveiling the perception of politicians' intellectual humility

Embracing intellectual humility has been touted as a potential key factor in improving relationships among people with different perspectives. Surprisingly, little research has been conducted on how individuals perceive those who express their views with intellectual humility, and no research, to our knowledge, examined perceptions of intellectual humility in political leaders specifically. This study aimed to examine to what extent perceivers value intellectual humility in the face of a polarizing topic (abortion) and when it is expressed by political leaders (hypothetical presidential candidates) sharing or opposing one's view. We predicted that individuals would like the same-view leader more than the opposing-view leader; however, they would also prefer leaders expressing intellectual humility overall. Importantly, we also explored whether individuals would be more tolerant of intellectual arrogance when arrogance came from a leader who shared (vs. opposed) their ideology. A pilot study (N = 94) confirmed all these predictions. A preregistered study with a larger sample (N = 927) replicated these patterns and showed that positive evaluations of leaders' intellectual humility were also contingent on their views and the ways they expressed intellectual humility (openness to alternative views or fallibility of their own view). While perceivers evaluated both the same and opposing-view leaders' openness to alternative views positively, they evaluated the same-view (but not the opposing-view) leaders' expression of fallibility negatively. Our findings shed light on the boundary conditions of valuing intellectual humility while offering insights on when and why people may refrain from expressing humility themselves and knowingly or unknowingly contribute to polarizing discourse.

What the eyes, confidence, and partner's identity can tell about change of mind

Perceptual confidence reflects the ability to evaluate the evidence that supports perceptual decisions. It is thought to play a critical role in guiding decision-making. However, only a few empirical studies have actually investigated the function of perceptual confidence. To address this issue, we designed a perceptual task in which participants provided a confidence judgment on the accuracy of their perceptual decision. Then, they viewed the response of a machine or human partner, and they were instructed to decide whether to keep or change their initial response. We observed that confidence predicted participants' changes of mind more than task difficulty and perceptual accuracy. Additionally, interacting with a machine, compared to a human, decreased confidence and increased participants tendency to change their initial decision, suggesting that both confidence and changes of mind are influenced by contextual factors, such as the identity of a partner. Finally, variations in confidence judgments but not change of mind were correlated with pre-response pupil dynamics, indicating that arousal changes are linked to confidence computations. This study contributes to our understanding of the factors influencing confidence and changes of mind and also evaluates the possibility of using pupil dynamics as a proxy of confidence.

Manipulating Prior Beliefs Causally Induces Under- and Overconfidence

Humans differ vastly in the confidence they assign to decisions. Although such under- and overconfidence relate to fundamental life outcomes, a computational account specifying the underlying mechanisms is currently lacking. We propose that prior beliefs in the ability to perform a task explain confidence differences across participants and tasks, despite similar performance. In two perceptual decision-making experiments, we show that manipulating prior beliefs about performance during training causally influences confidence in healthy adults (N = 50 each; Experiment 1: 8 men, one nonbinary; Experiment 2: 5 men) during a test phase, despite unaffected objective performance. This is true when prior beliefs are induced via manipulated comparative feedback and via manipulated training-phase difficulty. Our results were accounted for within an accumulation-to-bound model, explicitly modeling prior beliefs on the basis of earlier task exposure. Decision confidence is quantified as the probability of being correct conditional on prior beliefs, causing under- or overconfidence. We provide a fundamental mechanistic insight into the computations underlying under- and overconfidence.

Radical Collective Intelligence and the Reimagining of Cognitive Science

To introduce our special issue How Minds Work: The Collective in the Individual, we propose "radical CI," a form of collective intelligence, as a new paradigm for cognitive science. Radical CI posits that the representations and processes necessary to perform the cognitive functions that humans perform are collective entities, not encapsulated by any individual. To explain cognitive performance, it appeals to the distribution of cognitive labor on the assumption that the human project runs on countless interactions between locally acting individuals with specialized skills that each retain a small part of the relevant information. Some of the papers in the special issue appeal to radical CI to account for a variety of cognitive phenomena including memory performance, metacognition, belief updating, reasoning, and problem-solving. Other papers focus on the cultural and institutional practices that make radical CI possible.

Subjective Confidence as a Monitor of the Replicability of the Response

Confidence is commonly assumed to monitor the accuracy of responses. However, intriguing results, examined in the light of philosophical discussions of epistemic justification, suggest that confidence actually monitors the reliability of choices rather than (directly) their accuracy. The focus on reliability is consistent with the view that the construction of truth has much in common with the construction of reality: extracting reliable properties that afford prediction. People are assumed to make a binary choice by sampling cues from a "collective wisdomware," and their confidence is based on the consistency of these cues, in line with the self-consistency model. Here, however, I propose that internal consistency is taken to index the reliability of choices themselves-the likelihood that they will be repeated. The results of 10 studies using binary decisions from different domains indicated that confidence in a choice predicts its replicability both within individuals and across individuals. This was so for domains for which choices have a truth value and for those for which they do not. For the former domains, differences in replicability mediated the prediction of accuracy whether confidence was diagnostic or counterdiagnostic of accuracy. Metatheoretical, methodological, and practical implications are discussed.

Metacognition and Confidence: A Review and Synthesis

Determining the psychological, computational, and neural bases of confidence and uncertainty holds promise for understanding foundational aspects of human metacognition. While a neuroscience of confidence has focused on the mechanisms underpinning subpersonal phenomena such as representations of uncertainty in the visual or motor system, metacognition research has been concerned with personal-level beliefs and knowledge about self-performance. I provide a road map for bridging this divide by focusing on a particular class of confidence computation: propositional confidence in one's own (hypothetical) decisions or actions. Propositional confidence is informed by the observer's models of the world and their cognitive system, which may be more or less accurate-thus explaining why metacognitive judgments are inferential and sometimes diverge from task performance. Disparate findings on the neural basis of uncertainty and performance monitoring are integrated into a common framework, and a new understanding of the locus of action of metacognitive interventions is developed.

Interpersonal alignment of neural evidence accumulation to social exchange of confidence

Private, subjective beliefs about uncertainty have been found to have idiosyncratic computational and neural substrates yet, humans share such beliefs seamlessly and cooperate successfully. Bringing together decision making under uncertainty and interpersonal alignment in communication, in a discovery plus pre-registered replication design, we examined the neuro-computational basis of the relationship between privately held and socially shared uncertainty. Examining confidence-speed-accuracy trade-off in uncertainty-ridden perceptual decisions under social vs isolated context, we found that shared (i.e. reported confidence) and subjective (inferred from pupillometry) uncertainty dynamically followed social information. An attractor neural network model incorporating social information as top-down additive input captured the observed behavior and demonstrated the emergence of social alignment in virtual dyadic simulations. Electroencephalography showed that social exchange of confidence modulated the neural signature of perceptual evidence accumulation in the central parietal cortex. Our findings offer a neural population model for interpersonal alignment of shared beliefs.

Majority rule can help solve difficult tasks even when confident members opt out to serve individual interests

When sharing a common goal, confident and competent members are often motivated to contribute to the group, boosting its decision performance. However, it is unclear whether this process remains effective when members can opt in or out of group decisions and prioritize individual interests. Our laboratory experiment (n = 63) and cognitive modeling showed that at the individual level, confidence, competence, and a preference for risk motivated participants' opt-out decisions. We then analyzed the group-level accuracy of majority decisions by creating many virtual groups of 25 members resampled from the 63 participants in the experiment. Whereas the majority decisions by voters who preferred to participate in group decision making were inferior to individual decisions by loners who opted out in an easy task, this was reversed in a difficult task. Bootstrap-simulation analyses decomposed these outcomes into the effects of a decrease in group size and a decrease in voters' accuracy accruing from the opt-in/out mechanism, demonstrating how these effects interacted with task difficulty. Our results suggest that the majority rule still works to tackle challenging problems even when individual interests are emphasized over collective performance, playing a functional as well as a democratic role in consensus decision making under uncertainty.

Metacognitive Information Theory

The capacity that subjects have to rate confidence in their choices is a form of metacognition, and can be assessed according to bias, sensitivity and efficiency. Rich networks of domain-specific and domain-general regions of the brain are involved in the rating, and are associated with its quality and its use for regulating the processes of thinking and acting. Sensitivity and efficiency are often measured by quantities called meta-d' and the M-ratio that are based on reverse engineering the potential accuracy of the original, primary, choice that is implied by the quality of the confidence judgements. Here, we advocate a straightforward measure of sensitivity, called meta-𝓘, which assesses the mutual information between the accuracy of the subject's choices and the confidence reports, and two normalized versions of this measure that quantify efficiency in different regimes. Unlike most other measures, meta-𝓘-based quantities increase with the number of correctly assessed bins with which confidence is reported. We illustrate meta-𝓘 on data from a perceptual decision-making task, and via a simple form of simulated second-order metacognitive observer.

History biases reveal novel dissociations between perceptual and metacognitive decision-making

Human decision-making and self-reflection often depend on context and internal biases. For instance, decisions are often influenced by preceding choices, regardless of their relevance. It remains unclear how choice history influences different levels of the decision-making hierarchy. We used analyses grounded in information and detection theories to estimate the relative strength of perceptual and metacognitive history biases and to investigate whether they emerge from common/unique mechanisms. Although both perception and metacognition tended to be biased toward previous responses, we observed novel dissociations that challenge normative theories of confidence. Different evidence levels often informed perceptual and metacognitive decisions within observers, and response history distinctly influenced first- (perceptual) and second- (metacognitive) order decision-parameters, with the metacognitive bias likely to be strongest and most prevalent in the general population. We propose that recent choices and subjective confidence represent heuristics, which inform first- and second-order decisions in the absence of more relevant evidence.

Casting votes of antecedents play a key role in successful sequential decision-making

Aggregation of opinions often results in high decision-making accuracy, owing to the collective intelligence effect. Studies on group decisions have examined the optimum weights for opinion aggregation to maximise accuracy. In addition to the optimum weights of opinions, the impact of the correlation among opinions on collective intelligence is a major issue in collective decision-making. We investigated how individuals should weigh the opinions of others and their own to maximise their accuracy in sequential decision-making. In our sequential decision-making model, each person makes a primary choice, observes his/her predecessors' opinions, and makes a final choice, which results in the person's answer correlating with those of others. We developed an algorithm to find casting voters whose primary choices are determinative of their answers and revealed that decision accuracy is maximised by considering only the abilities of the preceding casting voters. We also found that for individuals with heterogeneous abilities, the order of decision-making has a significant impact on the correlation between their answers and their accuracies. This could lead to a counter-intuitive phenomenon whereby, in sequential decision-making, respondents are, on average, more accurate when less reliable individuals answer earlier and more reliable individuals answer later.

On the social nature of abstraction: cognitive implications of interaction and diversity

The human capacity for abstraction is remarkable. We effortlessly form abstract representations from varied experiences, generalizing and flexibly transferring experiences and knowledge between contexts, which can facilitate reasoning, problem solving and learning across many domains. The cognitive process of abstraction, however, is often portrayed and investigated as an individual process. This paper addresses how cognitive processes of abstraction-together with other aspects of human reasoning and problem solving-are fundamentally shaped and modulated by online social interaction. Starting from a general distinction between convergent thinking, divergent thinking and processes of abstraction, we address how social interaction shapes information processing differently depending on cognitive demands, social coordination and task ecologies. In particular, we suggest that processes of abstraction are facilitated by the interactive sharing and integration of varied individual experiences. To this end, we also discuss how the dynamics of group interactions vary as a function of group composition; that is, in terms of the similarity and diversity between the group members. We conclude by outlining the role of cognitive diversity in interactive processes and consider the importance of group diversity in processes of abstraction. This article is part of the theme issue 'Concepts in interaction: social engagement and inner experiences'.

Neural activity tracking identity and confidence in social information

Humans learn about the environment either directly by interacting with it or indirectly by seeking information about it from social sources such as conspecifics. The degree of confidence in the information obtained through either route should determine the impact that it has on adapting and changing behaviour. We examined whether and how behavioural and neural computations differ during non-social learning as opposed to learning from social sources. Trial-wise confidence judgements about non-social and social information sources offered a window into this learning process. Despite matching exactly the statistical features of social and non-social conditions, confidence judgements were more accurate and less changeable when they were made about social as opposed to non-social information sources. In addition to subjective reports of confidence, differences were also apparent in the Bayesian estimates of participants' subjective beliefs. Univariate activity in dorsomedial prefrontal cortex and posterior temporoparietal junction more closely tracked confidence about social as opposed to non-social information sources. In addition, the multivariate patterns of activity in the same areas encoded identities of social information sources compared to non-social information sources.

Neurocomputational mechanisms of confidence in self and others

Computing confidence in one’s own and others’ decisions is critical for social success. While there has been substantial progress in our understanding of confidence estimates about oneself, little is known about how people form confidence estimates about others. Here, we address this question by asking participants undergoing fMRI to place bets on perceptual decisions made by themselves or one of three other players of varying ability. We show that participants compute confidence in another player’s decisions by combining distinct estimates of player ability and decision difficulty – allowing them to predict that a good player may get a difficult decision wrong and that a bad player may get an easy decision right. We find that this computation is associated with an interaction between brain systems implicated in decision-making (LIP) and theory of mind (TPJ and dmPFC). These results reveal an interplay between self- and other-related processes during a social confidence computation.

Empirical test of the many-wrongs hypothesis reveals weighted averaging of individual routes in pigeon flocks

The 'many-wrongs hypothesis' predicts that groups improve their decision-making performance by aggregating members' diverse opinions. Although this has been considered one of the major benefits of collective movement and migration, whether and how multiple inputs are in fact aggregated for superior directional accuracy has not been empirically verified in non-human animals. Here we showed that larger homing pigeon flocks had significantly more efficient (i.e. shorter) homing routes than smaller flocks, consistent with previous findings and with the predictions of the many-wrongs hypothesis. However, detailed analysis showed that flock routes were not simply averages of individual routes, but instead that pigeons that more faithfully recapitulated their routes during individual flights had a proportionally greater influence on their flocks' routes. We discuss the implications of our results for possible mechanisms of collective learning as well as for the definition of leadership in animals solving navigational tasks collectively.

The motor Wisdom of the Crowd

Wisdom of the Crowd is the aggregation of many individual estimates to obtain a better collective one. Because of its enormous social potential, this effect has been thoroughly investigated, but predominantly on tasks that involve rational thinking (such as estimating a number). Here we tested this effect in the context of drawing geometrical shapes, which still enacts cognitive processes but mainly involves visuomotor control. We asked more than 700 school students to trace five patterns shown on a touchscreen and then aggregated their individual trajectories to improve the match with the original pattern. Our results show the characteristics of the strongest examples of Wisdom of the Crowd. First, the aggregate trajectory can be up to 5 times more accurate than the individual ones. Second, this great improvement requires aggregating trajectories from different individuals (rather than trials from the same individual). Third, the aggregate trajectory outperforms more than 99% of individual trajectories. Fourth, while older individuals outperform younger ones, a crowd of young individuals outperforms the average older one. These results demonstrate for the first time Wisdom of the Crowd in the realm of motor control, opening the door to further studies of human and also animal behavioural trajectories and their mechanistic underpinnings.

Alpha oscillations and stimulus-evoked activity dissociate metacognitive reports of attention, visibility, and confidence in a rapid visual detection task

Variability in the detection and discrimination of weak visual stimuli has been linked to oscillatory neural activity. In particular, the amplitude of activity in the alpha-band (8–12 Hz) has been shown to impact the objective likelihood of stimulus detection, as well as measures of subjective visibility, attention, and decision confidence. Here we investigate how preparatory alpha in a cued pretarget interval influences performance and phenomenology, by recording simultaneous subjective measures of attention and confidence (experiment 1) or attention and visibility (experiment 2) on a trial-by-trial basis in a visual detection task. Across both experiments, alpha amplitude was negatively and linearly correlated with the intensity of subjective attention. In contrast with this linear relationship, we observed a quadratic relationship between the strength of alpha oscillations and subjective ratings of confidence and visibility. We find that this same quadratic relationship links alpha amplitude with the strength of stimulus-evoked responses. Visibility and confidence judgments also corresponded with the strength of evoked responses, but confidence, uniquely, incorporated information about attentional state. As such, our findings reveal distinct psychological and neural correlates of metacognitive judgments of attentional state, stimulus visibility, and decision confidence when these judgments are preceded by a cued target interval.

Dynamic influences on static measures of metacognition

Humans differ in their capability to judge choice accuracy via confidence judgments. Popular signal detection theoretic measures of metacognition, such as M-ratio, do not consider the dynamics of decision making. This can be problematic if response caution is shifted to alter the tradeoff between speed and accuracy. Such shifts could induce unaccounted-for sources of variation in the assessment of metacognition. Instead, evidence accumulation frameworks consider decision making, including the computation of confidence, as a dynamic process unfolding over time. Using simulations, we show a relation between response caution and M-ratio. We then show the same pattern in human participants explicitly instructed to focus on speed or accuracy. Finally, this association between M-ratio and response caution is also present across four datasets without any reference towards speed. In contrast, when data are analyzed with a dynamic measure of metacognition, v-ratio, there is no effect of speed-accuracy tradeoff.

Strengthening Criteria Independence through Optimization of Alternative Value Ratio Comparisons

Every decision maker’s internal scale is different based on a myriad of possible factors unique to that decision maker. Conflicting criteria within and between alternatives in multicriteria decision making can create negative effects within the weighting schemes and amplify preference biases and scale disparities between decision makers in a group decision context. Additionally, the weighting of group decision-making frameworks can intensify the already skewed criteria values. When making judgments against requirements, it may be preferable to reduce scale trend distortions between decision makers as much as possible. Previous research supports that certain information presentation modes can significantly reduce preference bias and strengthen criteria independence against requirements through cross alternative anchoring. This paper expands that research and proposes a new optimization model for strengthening criteria independence and consensus in group decision making. Initial results indicate the proposed optimization model can significantly reduce scale distortions and smooth comparative alternative value trends between decision makers toward strengthened group consensus. Furthermore, results support the potential and opportunity for semiautonomous group consensus processes.

Inferences regarding oneself and others in the human brain

The human brain can infer one’s own and other individuals’ mental states through metacognition and mentalizing, respectively. This Primer explores a new study in PLOS Biology that implicates distinct brain regions of the medial prefrontal cortex in metacognition and mentalizing.

Distinct Generation of Subjective Vividness and Confidence during Naturalistic Memory Retrieval in Angular Gyrus

Our subjective experience of remembering guides and monitors the reconstruction of past and simulation of the future, which enables us to identify mistakes and adjust our behavior accordingly. However, it remains incompletely understood what underlies the process of subjective mnemonic experience. Here, we combined behavior, repetitive TMS, and functional neuroimaging to probe whether vividness and confidence are generated differently during retrieval. We found that preretrieval repetitive TMS targeting the left angular gyrus (AnG) selectively attenuated the vividness efficiency compared with control stimulation while keeping metacognitive efficiency and objective memory accuracy unaffected. Using trialwise data, we showed that AnG stimulation altered the mediating role of vividness in confidence in the accuracy of memory judgment. Moreover, resting-state functional connectivity of hippocampus and AnG was specifically associated with vividness efficiency, but not metacognitive efficiency across individuals. Together, these results identify the causal involvement of AnG in gauging the vividness, but not the confidence, of memory, thereby suggesting a differentiation account of conscious assessment of memory by functionally and anatomically dissociating the monitoring of vividness from confidence.

Political coherence and certainty as drivers of interpersonal liking over and above similarity

Affective polarization and political segregation have become a serious threat to democratic societies. One standard explanation for these phenomena is that people like and prefer interacting with similar others. However, similarity may not be the only driver of interpersonal liking in the political domain, and other factors, yet to be uncovered, could play an important role. Here, we hypothesized that beyond the effect of similarity, people show greater preference for individuals with politically coherent and confident opinions. To test this idea, we performed two behavioral studies consisting of one-shot face-to-face pairwise interactions. We found that people with ambiguous or ambivalent views were nonreciprocally attracted to confident and coherent ingroups. A third experimental study confirmed that politically coherent and confident profiles are rated as more attractive than targets with ambiguous or ambivalent opinions. Overall, these findings unfold the key drivers of the affability between people who discuss politics.

On the psychological origins of tool use

The ubiquity of tool use in human life has generated multiple lines of scientific and philosophical investigation to understand the development and expression of humans' engagement with tools and its relation to other dimensions of human experience. However, existing literature on tool use faces several epistemological challenges in which the same set of questions generate many different answers. At least four critical questions can be identified, which are intimately intertwined-(1) What constitutes tool use? (2) What psychological processes underlie tool use in humans and nonhuman animals? (3) Which of these psychological processes are exclusive to tool use? (4) Which psychological processes involved in tool use are exclusive to Homo sapiens? To help advance a multidisciplinary scientific understanding of tool use, six author groups representing different academic disciplines (e.g., anthropology, psychology, neuroscience) and different theoretical perspectives respond to each of these questions, and then point to the direction of future work on tool use. We find that while there are marked differences among the responses of the respective author groups to each question, there is a surprising degree of agreement about many essential concepts and questions. We believe that this interdisciplinary and intertheoretical discussion will foster a more comprehensive understanding of tool use than any one of these perspectives (or any one of these author groups) would (or could) on their own.

Sources of confidence in value-based choice

Confidence, the subjective estimate of decision quality, is a cognitive process necessary for learning from mistakes and guiding future actions. The origins of confidence judgments resulting from economic decisions remain unclear. We devise a task and computational framework that allowed us to formally tease apart the impact of various sources of confidence in value-based decisions, such as uncertainty emerging from encoding and decoding operations, as well as the interplay between gaze-shift dynamics and attentional effort. In line with canonical decision theories, trial-to-trial fluctuations in the precision of value encoding impact economic choice consistency. However, this uncertainty has no influence on confidence reports. Instead, confidence is associated with endogenous attentional effort towards choice alternatives and down-stream noise in the comparison process. These findings provide an explanation for confidence (miss)attributions in value-guided behaviour, suggesting mechanistic influences of endogenous attentional states for guiding decisions and metacognitive awareness of choice certainty.

The Cognitive Science of Technology

Technology is central to human life but hard to define and study. This review synthesizes advances in fields from anthropology to evolutionary biology and neuroscience to propose an interdisciplinary cognitive science of technology. The foundation of this effort is an evolutionarily motivated definition of technology that highlights three key features: material production, social collaboration, and cultural reproduction. This broad scope respects the complexity of the subject but poses a challenge for theoretical unification. Addressing this challenge requires a comparative approach to reduce the diversity of real-world technological cognition to a smaller number of recurring processes and relationships. To this end, a synthetic perceptual-motor hypothesis (PMH) for the evolutionary-developmental-cultural construction of technological cognition is advanced as an initial target for investigation.

Probabilistic social learning improves the public's judgments of news veracity

The digital spread of misinformation is one of the leading threats to democracy, public health, and the global economy. Popular strategies for mitigating misinformation include crowdsourcing, machine learning, and media literacy programs that require social media users to classify news in binary terms as either true or false. However, research on peer influence suggests that framing decisions in binary terms can amplify judgment errors and limit social learning, whereas framing decisions in probabilistic terms can reliably improve judgments. In this preregistered experiment, we compare online peer networks that collaboratively evaluated the veracity of news by communicating either binary or probabilistic judgments. Exchanging probabilistic estimates of news veracity substantially improved individual and group judgments, with the effect of eliminating polarization in news evaluation. By contrast, exchanging binary classifications reduced social learning and maintained polarization. The benefits of probabilistic social learning are robust to participants' education, gender, race, income, religion, and partisanship.

Listeners' perceptions of the certainty and honesty of a speaker are associated with a common prosodic signature

The success of human cooperation crucially depends on mechanisms enabling individuals to detect unreliability in their conspecifics. Yet, how such epistemic vigilance is achieved from naturalistic sensory inputs remains unclear. Here we show that listeners' perceptions of the certainty and honesty of other speakers from their speech are based on a common prosodic signature. Using a data-driven method, we separately decode the prosodic features driving listeners' perceptions of a speaker's certainty and honesty across pitch, duration and loudness. We find that these two kinds of judgments rely on a common prosodic signature that is perceived independently from individuals' conceptual knowledge and native language. Finally, we show that listeners extract this prosodic signature automatically, and that this impacts the way they memorize spoken words. These findings shed light on a unique auditory adaptation that enables human listeners to quickly detect and react to unreliability during linguistic interactions.

Sources of Metacognitive Inefficiency

Confidence judgments are typically less informative about one's accuracy than they could be; a phenomenon we call metacognitive inefficiency. We review the existence of different sources of metacognitive inefficiency and classify them into four categories based on whether the corruption is due to: (i) systematic or nonsystematic influences, and (ii) the input to or the computation of the metacognitive system. Critically, the existence of different sources of metacognitive inefficiency provides an alternative explanation for behavioral findings typically interpreted as evidence for domain-specific (and against domain-general) metacognitive systems. We argue that, contrary to the dominant assumption in the field, metacognitive failures are not monolithic and suggest that understanding the sources of metacognitive inefficiency should be a primary goal of the science of metacognition.

Concept-metacognition

Concepts are our tools for thinking. They enable us to engage in explicit reasoning about things in the world. Like physical tools, they can be more or less good, given the ways we use them-more or less dependable for categorisation, learning, induction, action-planning, and so on. Do concept users appreciate, explicitly or implicitly, that concepts vary in dependability? Do they feel that some concepts are in some way defective? If so, we metacognise our concepts. This article offers a preliminary taxonomy of different forms of metacognition directed at concepts and suggests that concept-metacognition impacts on several different cognitive processes.

Private-public mappings in human prefrontal cortex

A core feature of human cognition is an ability to separate private states of mind - what we think or believe - from public actions - what we say or do. This ability is central to successful social interaction - with different social contexts often requiring different mappings between private states and public actions in order to minimise conflict and facilitate communication. Here we investigated how the human brain supports private-public mappings, using an interactive task which required subjects to adapt how they communicated their confidence about a perceptual decision to the social context. Univariate and multivariate analysis of fMRI data revealed that a private-public distinction is reflected in a medial-lateral division of prefrontal cortex - with lateral frontal pole (FPl) supporting the context-dependent mapping from a private sense of confidence to a public report. The concept of private-public mappings provides a promising framework for understanding flexible social behaviour.

Brain dynamics for confidence-weighted learning

Learning in a changing, uncertain environment is a difficult problem. A popular solution is to predict future observations and then use surprising outcomes to update those predictions. However, humans also have a sense of confidence that characterizes the precision of their predictions. Bayesian models use a confidence-weighting principle to regulate learning: for a given surprise, the update is smaller when the confidence about the prediction was higher. Prior behavioral evidence indicates that human learning adheres to this confidence-weighting principle. Here, we explored the human brain dynamics sub-tending the confidence-weighting of learning using magneto-encephalography (MEG). During our volatile probability learning task, subjects’ confidence reports conformed with Bayesian inference. MEG revealed several stimulus-evoked brain responses whose amplitude reflected surprise, and some of them were further shaped by confidence: surprise amplified the stimulus-evoked response whereas confidence dampened it. Confidence about predictions also modulated several aspects of the brain state: pupil-linked arousal and beta-range (15–30 Hz) oscillations. The brain state in turn modulated specific stimulus-evoked surprise responses following the confidence-weighting principle. Our results thus indicate that there exist, in the human brain, signals reflecting surprise that are dampened by confidence in a way that is appropriate for learning according to Bayesian inference. They also suggest a mechanism for confidence-weighted learning: confidence about predictions would modulate intrinsic properties of the brain state to amplify or dampen surprise responses evoked by discrepant observations.

Learning in a changing and uncertain world is difficult. In this context, facing a discrepancy between my current belief and new observations may reflect random fluctuations (e.g. my commute train is unexpectedly late, but it happens sometimes), if so, I should ignore this discrepancy and not change erratically my belief. However, this discrepancy could also denote a profound change (e.g. the train company changed and is less reliable), in this case, I should promptly revise my current belief. Human learning is adaptive: we change how much we learn from new observations, in particular, we promote flexibility when facing profound changes. A mathematical analysis of the problem shows that we should increase flexibility when the confidence about our current belief is low, which occurs when a change is suspected. Here, I show that human learners entertain rational confidence levels during the learning of changing probabilities. This confidence modulates intrinsic properties of the brain state (oscillatory activity and neuromodulation) which in turn amplifies or reduces, depending on whether confidence is low or high, the neural responses to discrepant observations. This confidence-weighting mechanism could underpin adaptive learning.

Knowing Ourselves Together: The Cultural Origins of Metacognition

Metacognition - the ability to represent, monitor and control ongoing cognitive processes - helps us perform many tasks, both when acting alone and when working with others. While metacognition is adaptive, and found in other animals, we should not assume that all human forms of metacognition are gene-based adaptations. Instead, some forms may have a social origin, including the discrimination, interpretation, and broadcasting of metacognitive representations. There is evidence that each of these abilities depends on cultural learning and therefore that cultural selection might shape human metacognition. The cultural origins hypothesis is a plausible and testable alternative that directs us towards a substantial new programme of research.

Advice-taking as a bridge between decision neuroscience and mental capacity

A person's capacity to process advice is an important aspect of decision making in the real world. For example, in decisions about treatment, the way patients respond to the advice of family, friends and medical professionals may be used (intentionally or otherwise) as a marker of the "use or weigh" requirement of decision-making capacity. Here we explore neuroscientific research on decision-making to identify features of advice-taking that help conceptualize this requirement. We focus on studies of the neural and computational basis of decision-making in laboratory settings. These studies originally investigated simple perceptual decisions about ambiguous stimuli, but have more recently been extended to more complex "value-based" decisions involving the comparison of subjective preferences. Value-based decisions are a useful model system for capacity-related decision-making as they do not have an objectively 'correct' answer and are instead based on subjective preferences. In this context, advice-taking can be seen as a process in which new evidence for one or other option is integrated, leading to altered behaviour or choices. We use this framework to distinguish between different types of advice-taking: private compliance consists of updating one's privately held beliefs based on new evidence, whereas in the case of public compliance, people change their behaviour at a surface level without shifting their privately-held beliefs. Importantly, both types of advice-taking may lead to similar outcomes but rely on different decision processes. We suggest that understanding how multiple mechanisms drive advice-taking holds promise for targeting decision-making support and improving our understanding of the use and weigh requirement in cases of contested capacity.

Neurophysiological correlates of collective perceptual decision-making

Humans frequently perform tasks collaboratively in daily life. Collaborating with others may or may not result in higher task performance than if one were to complete the task alone (i.e., a collective benefit). A recent study on collective benefits in perceptual decision-making showed that dyad members with similar individual performances attain collective benefit. However, little is known about the physiological basis of these results. Here, we replicate this earlier work and also investigate the neurophysiological correlates of decision-making using EEG. In a two-interval forced-choice task, co-actors individually indicated presence of a target stimulus with a higher contrast and then indicated their confidence on a rating scale. Viewing the individual ratings, dyads made a joint decision. Replicating earlier work, we found a positive correlation between the similarity of individual performances and collective benefit. We analyzed event-related potentials (ERPs) in three phases (i.e., stimulus onset, response and feedback) using explorative cluster mass permutation tests. At stimulus onset, ERPs were significantly linearly related to our manipulation of contrast differences, validating our manipulation of task difficulty. For individual and joint responses, we found a significant centro-parietal error-related positivity for correct versus incorrect responses, which suggests that accuracy is already evaluated at the response level. At feedback presentation, we found a significant late positive fronto-central potential elicited by incorrect joint responses. In sum, these results demonstrate that response- and feedback-related components elicited by an error-monitoring system differentially integrate conflicting information exchanged during the joint decision-making process.

Human noise blindness drives suboptimal cognitive inference

Humans typically make near-optimal sensorimotor judgements but show systematic biases when making more cognitive judgements. Here we test the hypothesis that, while humans are sensitive to the noise present during early sensory encoding, the “optimality gap” arises because they are blind to noise introduced by later cognitive integration of variable or discordant pieces of information. In six psychophysical experiments, human observers judged the average orientation of an array of contrast gratings. We varied the stimulus contrast (encoding noise) and orientation variability (integration noise) of the array. Participants adapted near-optimally to changes in encoding noise, but, under increased integration noise, displayed a range of suboptimal behaviours: they ignored stimulus base rates, reported excessive confidence in their choices, and refrained from opting out of objectively difficult trials. These overconfident behaviours were captured by a Bayesian model blind to integration noise. Our study provides a computationally grounded explanation of human suboptimal cognitive inference.

Santiago Herce Castañón and colleagues show that people are blind to mental errors that arise when combining multiple pieces of discordant information. This blindness helps explain why cognitive judgements often are suboptimal.

Mathematical Structures in Group Decision-Making on Resource Allocation Distributions

Optimal decisions on the distribution of finite resources are explicitly structured by mathematical models that specify relevant variables, constraints, and objectives. Here we report analysis and evidence that implicit mathematical structures are also involved in group decision-making on resource allocation distributions under conditions of uncertainty that disallow formal optimization. A group’s array of initial distribution preferences automatically sets up a geometric decision space of alternative resource distributions. Weighted averaging mechanisms of interpersonal influence reduce the heterogeneity of the group’s initial preferences on a suitable distribution. A model of opinion formation based on weighted averaging predicts a distribution that is a feasible point in the group’s implicit initial decision space.

Confidence is higher in touch than in vision in cases of perceptual ambiguity

The inclination to touch objects that we can see is a surprising behaviour, given that vision often supplies relevant and sufficiently accurate sensory evidence. Here we suggest that this 'fact-checking' phenomenon could be explained if touch provides a higher level of perceptual certainty than vision. Testing this hypothesis, observers explored inverted T-shaped stimuli eliciting the Vertical-horizontal illusion in vision and touch, which included clear-cut and ambiguous cases. In separate blocks, observers judged whether the vertical bar was shorter or longer than the horizontal bar and rated the confidence in their judgments. Decisions reached by vision were objectively more accurate than those reached by touch with higher overall confidence ratings. However, while confidence was higher for vision rather than for touch in clear-cut cases, observers were more confident in touch when the stimuli were ambiguous. This relative bias as a function of ambiguity qualifies the view that confidence tracks objective accuracy and uses a comparable mapping across sensory modalities. Employing a perceptual illusion, our method disentangles objective and subjective accuracy showing how the latter is tracked by confidence and point towards possible origins for 'fact checking' by touch.

Group decision-making is optimal in adolescence

Group decision-making is required in early life in educational settings and central to a well-functioning society. However, there is little research on group decision-making in adolescence, despite the significant neuro-cognitive changes during this period. Researchers have studied adolescent decision-making in 'static' social contexts, such as risk-taking in the presence of peers, and largely deemed adolescent decision-making 'sub-optimal'. It is not clear whether these findings generalise to more dynamic social contexts, such as the discussions required to reach a group decision. Here we test the optimality of group decision-making at different stages of adolescence. Pairs of male pre-to-early adolescents (8 to 13 years of age) and mid-to-late adolescents (14 to 17 years of age) together performed a low-level, perceptual decision-making task. Whenever their individual decisions differed, they were required to negotiate a joint decision. While there were developmental differences in individual performance, the joint performance of both adolescent groups was at adult levels (data obtained from a previous study). Both adolescent groups achieved a level of joint performance expected under optimal integration of their individual information into a joint decision. Young adolescents' joint, but not individual, performance deteriorated over time. The results are consistent with recent findings attesting to the competencies, rather than the shortcomings, of adolescent social behaviour.

Group decision-making is optimal in adolescence

Group decision-making is required in early life in educational settings and central to a well-functioning society. However, there is little research on group decision-making in adolescence, despite the significant neuro-cognitive changes during this period. Researchers have studied adolescent decision-making in ‘static’ social contexts, such as risk-taking in the presence of peers, and largely deemed adolescent decision-making ‘sub-optimal’. It is not clear whether these findings generalise to more dynamic social contexts, such as the discussions required to reach a group decision. Here we test the optimality of group decision-making at different stages of adolescence. Pairs of male pre-to-early adolescents (8 to 13 years of age) and mid-to-late adolescents (14 to 17 years of age) together performed a low-level, perceptual decision-making task. Whenever their individual decisions differed, they were required to negotiate a joint decision. While there were developmental differences in individual performance, the joint performance of both adolescent groups was at adult levels (data obtained from a previous study). Both adolescent groups achieved a level of joint performance expected under optimal integration of their individual information into a joint decision. Young adolescents’ joint, but not individual, performance deteriorated over time. The results are consistent with recent findings attesting to the competencies, rather than the shortcomings, of adolescent social behaviour.

The application of computational models to social neuroscience: promises and pitfalls

Interactions with conspecifics are key to any social species. In order to navigate this social world, it is crucial for individuals to learn from and about others. From learning new skills by observing parents perform them to making complex collective decisions, understanding the mechanisms underlying social cognitive processes has been of considerable interest to psychologists and neuroscientists. Here, we review studies that have used computational modelling techniques, combined with neuroimaging, to shed light on how people learn and make decisions in social contexts. As opposed to standard social neuroscience methods, the computational approach allows one to directly examine where in the brain particular computations, as estimated by models of behavior, are implemented. Findings suggest that people use several strategies to learn from others: vicarious reward learning, where one learns from observing the reward outcomes of another agent; action imitation, which relies on encoding a prediction error between the expected and actual actions of the other agent; and social inference, where one learns by inferring the goals and intentions of others. These computations are implemented in distinct neural networks, which may be recruited adaptively depending on task demands, the environment and other social factors.

"It's Not a Tumor": A Framework for Capitalizing on Individual Diversity to Boost Target Detection

Even experts routinely miss infrequent targets, such as weapons in baggage scans or tumors in mammograms, because the visual system is not equipped to notice the unusual. To date, limited progress has been made toward improving human factors that mediate such critical diagnostic tasks. Here, we present a novel framework for pairing individuals' estimates to increase target detection. Using a wisdom-of-crowds approach that capitalizes on the visual system's ability to efficiently combine information, we demonstrated how averaging two noninteracting individuals' continuous estimates of whether a briefly presented image contained a prespecified target can significantly boost detection across a range of tasks. Furthermore, we showed how pairing individuals' estimates to maximize decorrelated patterns of performance in one task can optimize performance on a separate task. These results make significant advances toward combating severe deficits in target detection using straightforward applications for maximizing performance within limited pools of observers.

Reciprocity of social influence

Humans seek advice, via social interaction, to improve their decisions. While social interaction is often reciprocal, the role of reciprocity in social influence is unknown. Here, we tested the hypothesis that our influence on others affects how much we are influenced by them. Participants first made a visual perceptual estimate and then shared their estimate with an alleged partner. Then, in alternating trials, the participant either revised their decisions or observed how the partner revised theirs. We systematically manipulated the partner’s susceptibility to influence from the participant. We show that participants reciprocated influence with their partner by gravitating toward the susceptible (but not insusceptible) partner’s opinion. In further experiments, we showed that reciprocity is both a dynamic process and is abolished when people believed that they interacted with a computer. Reciprocal social influence is a signaling medium for human-to-human communication that goes beyond aggregation of evidence for decision improvement.

Humans give and receive social influence—e.g. advice—in many situations, but it is not known whether social influence is a reciprocal process, like trade. Here, the authors show that people are more likely to follow a partner's advice if that partner has previously complied with their advice.

Distinct encoding of decision confidence in human medial prefrontal cortex

Our confidence in a choice and the evidence pertaining to a choice appear to be inseparable. However, an emerging computational consensus holds that the brain should maintain separate estimates of these quantities for adaptive behavioral control. We have devised a psychophysical task to decouple confidence in a perceptual decision from both the reliability of sensory evidence and the relation of such evidence with respect to a choice boundary. Using human fMRI, we found that an area in the medial prefrontal cortex, the perigenual anterior cingulate cortex (pgACC), tracked expected performance, an aggregate signature of decision confidence, whereas neural areas previously proposed to encode decision confidence instead tracked sensory reliability (posterior parietal cortex and ventral striatum) or boundary distance (presupplementary motor area). Supporting that information encoded by pgACC is central to a subjective sense of decision confidence, we show that pgACC activity does not simply covary with expected performance, but is also linked to within-subject and between-subject variation in explicit confidence estimates. Our study is consistent with the proposal that the brain maintains choice-dependent and choice-independent estimates of certainty, and sheds light on why dysfunctional confidence often emerges following prefrontal lesions and/or degeneration.

Group benefits in joint perceptual tasks-a review

In daily life, humans often perform perceptual tasks together to reach a shared goal. In these situations, individuals may collaborate (e.g., by distributing task demands) to perform the task better than when the task is performed alone (i.e., attain a group benefit). In this review, we identify the factors influencing if, and to what extent, a group benefit is attained and provide a framework of measures to assess group benefits in perceptual tasks. In particular, we integrate findings from two frequently investigated joint perceptual tasks: visuospatial tasks and decision-making tasks. For both task types, we find that an exchange of information between coactors is critical to improve joint performance. Yet, the type of exchanged information and how coactors collaborate differs between tasks. In visuospatial tasks, coactors exchange information about the performed actions to distribute task demands. In perceptual decision-making tasks, coactors exchange their confidence on their individual perceptual judgments to negotiate a joint decision. We argue that these differences can be explained by the task structure: coactors distribute task demands if a joint task allows for a spatial division and stimuli can be accurately processed by one individual. Otherwise, they perform the task individually and then integrate their individual judgments.

Performance similarities predict collective benefits in dyadic and triadic joint visual search

When humans perform tasks together, they may reach a higher performance in comparison to the best member of a group (i.e., a collective benefit). Earlier research showed that interindividual performance similarities predict collective benefits for several joint tasks. Yet, researchers did not test whether this is the case for joint visuospatial tasks. Also, researchers did not investigate whether dyads and triads reach a collective benefit when they are forbidden to exchange any information while performing a visuospatial task. In this study, participants performed a joint visual search task either alone, in dyads, or in triads, and were not allowed to exchange any information while doing the task. We found that dyads reached a collective benefit. Triads did outperform their best individual member and dyads—yet, they did not outperform the best dyad pairing within the triad. In addition, similarities in performance significantly predicted the collective benefit for dyads and triads. Furthermore, we find that the dyads’ and triads’ search performances closely match a simulated performance based on the individual search performances, which assumed that members of a group act independently. Overall, the present study supports the view that performance similarities predict collective benefits in joint tasks. Moreover, it provides a basis for future studies to investigate the benefits of exchanging information between co-actors in joint visual search tasks.

Making better decisions in groups

We review the literature to identify common problems of decision-making in individuals and groups. We are guided by a Bayesian framework to explain the interplay between past experience and new evidence, and the problem of exploring the space of hypotheses about all the possible states that the world could be in and all the possible actions that one could take. There are strong biases, hidden from awareness, that enter into these psychological processes. While biases increase the efficiency of information processing, they often do not lead to the most appropriate action. We highlight the advantages of group decision-making in overcoming biases and searching the hypothesis space for good models of the world and good solutions to problems. Diversity of group members can facilitate these achievements, but diverse groups also face their own problems. We discuss means of managing these pitfalls and make some recommendations on how to make better group decisions.