Olivier Morin

Pierre Olivier Jacquet

Krist Vaesen

Alberto Acerbi

Social information use and social information waste

Keywords: Egocentric discounting, social learning, cultural evolution, imitation, epistemic vigilance, information cascades, conformity, advice-taking, judge-advisor-system

Social information is immensely valuable. Yet we waste it. The information we get from observing other humans and from communicating with them is a cheap and reliable informational resource. It is considered the backbone of human cultural evolution. Theories and models focused on the evolution of social learning show the great adaptive benefits of evolving cognitive tools to process it. In spite of this, human adults in the experimental literature use social information quite inefficiently: they do not take it sufficiently into account. A comprehensive review of the literature on five experimental tasks documented 45 studies showing social information waste, and 4 studies showing social information being over-used. These studies cover "egocentric discounting" phenomena as studied by social psychology, but also include experimental social learning studies. Social information waste means that human adults fail to give social information its optimal weight. Both proximal explanations and accounts derived from evolutionary theory leave crucial aspects of the phenomenon unaccounted for: egocentric discounting is a pervasive effect that no single unifying explanation fully captures. Cultural evolutionary theory's insistence on the power and benefits of social influence is to be balanced against this phenomenon.

Introduction

The human capacity to use social information is fundamental to our species' cultural evolutionarguably humankind's key adaptive asset [1][2][3][4]. It affords enormous cognitive benefits, allowing individuals to avoid the costs of individual exploration, and most importantly, to avail themselves of collective progresses no individual could have made on their own. One is naturally tempted to infer that humans evolved both uncommon capacities for using social information, and an uncommon degree of dependence on it. Leading specialists of cultural evolution embrace this view, drawing on alleged cases of over-reliance on the example of others, such as the imitation of kamikaze suicides [5] or celebrity suicides [4,6], and the copying of prestigious models in domains where these models are clearly incompetent [START_REF] Richerson | Not by genes alone[END_REF]. However, several experimental results, including from the cultural evolution research tradition, suggest that individuals (this paper focuses on human adults) use social information sub-optimally. Specifically, they do not use it enough.

Social information consists in all the things that an individual can learn from others, be it through intentional communication, demonstrations, or the mere observation of behaviours that are not necessarily meant to be seen [1,[START_REF] Danchin | Public information: from nosy neighbors to cultural evolution[END_REF]. We use social information whenever we let it affect our behaviour. Alongside social information, we routinely process large amounts of non-social information. Here we'll call it "individual": primary perceptions that come to us directly from the world, neither coming from nor mediated by other people. Individual information has one clear advantage over social information: it comes to us processed by no filter but our own sensory nervous system. Social information is processed or produced by others before we process it, which can cause distortions due to random error, bias, or deliberate deception.

In a social world, individual information acquires two new uses.

First, each agent's individual information can be combined with others agents' individual information, producing "wisdom of crowds" effects. When several agents produce two independent (i.e., not influenced by or copied from the other agent) guesses on a state of the world, and if (for binary decisions) each individual agent is more likely to be right than wrong, the combination of their guesses through majority voting or averaging usually gives a far more reliable guess than any single answer [START_REF] Lorge | A survey of studies contrasting the quality of group performance and individual performance, 1920-1957[END_REF][10][START_REF] Condorcet | Essai sur l'application de l'analyse à la probabilité des décisions rendues à la pluralité des voix[END_REF]. This well-known result only holds, however, to the extent that individual guesses are independent from each other: each guess must reflect individual information [12,[START_REF] Lorenz | How social influence can undermine the wisdom of crowd effect[END_REF].

Second, possessing a piece of information that is not (or not yet) social may give one an edge in strategic relations with conspecifics. Disclosed to others, it enhances one's reputation as a reliable informant and valuable cooperator [14]. Kept to oneself, it makes it possible to reap rewards that elude others [START_REF] Giraldeau | Potential disadvantages of using socially acquired information[END_REF]. Both types of information (the social and the asocial) thus have their advantages and drawbacks. How much weight should we give to individual or social information, and how much effort should we spend acquiring one or the other? Experimental evidence from several independent research traditions has evidenced a surprising discrepancy between efficiency rules for social information use, and human participants' actual behaviour. Contrary to what one might expect from a cultural species, participants appear to put too little weight on the information they can gather from other people's decisions or testimony.

In each of the literatures we survey, the relevant findings are relatively uncontroversial: we do not claim to be discovering anything that is not already known. However, researchers in one field do not necessarily know about all the findings from other fields. As a result, the pervasiveness of egocentric discounting is not always fully realised. Furthermore, no single field possesses an integrated account of why it occurs in its multiple manifestations. The present paper precisely aims at filling this lacuna, proceeding in three steps. Part 2 synthetises the available experimental evidence for the overweighting of individual information relative to social information, surveying social psychology, cultural evolution, and experimental economics. In Part 3, we discuss the putative proximate factors that have been put forward to explain this effect: cognitive biases, task-specific demands, biases in participants sampling. In Part 4, we discuss some ultimate factors that one can derive from theories or models about social learning's evolutionary history. In conclusion (part 5), our survey reveals that no single explanation taken in isolation captures all the aspects of the phenomenon.

How much does social information weigh in our decisions?

The supplementary materials present a list of publications that specifically document how experimental participants (focusing exclusively on human adults) give less weight to social information when it conflicts with a belief that they hold based on previous knowledge, or with a piece of private information provided by the experimenters to them but not to others. A comprehensive list of inclusion criteria is given in Section 1 of the Supplementary Materials.

These are studies in which participants are asked to perform a task, having access to both individual and social information. Pieces of information of both kinds are potentially relevant to the task, but often conflict. What counts as success in the task is clearly defined, and there are widely accepted normative frameworks that specify how agents should behave to succeed.

Accurate performance, as opposed to agreement with other participants, is valued (usually incentivised). The participants are presented with social information, usually concerning the other participants' responses, freely or at a small cost.

The exact criteria for what constitutes rational or efficient use of social information vary depending on authors, protocols, or studies, but some basic criteria are shared by all. First, the opinion of two random participants should be given equal weights. Second, absent suspicions of deceptive intent or noisy transmission, other people's opinion should not be given less weight merely because they come from others. These two principles imply that the average random participant should give equal weight to her opinion and to that of a random participant from the same group [START_REF] Yaniv | Receiving other people's advice: Influence and benefit[END_REF]. This basic principle can be formalised in various ways, the most common being Bayesian updating rules [START_REF] Anderson | Information Cascades in the Laboratory[END_REF][START_REF] Whalen | Sensitivity to Shared Information in Social Learning[END_REF][START_REF] Pescetelli | The role of decision confidence in advice-taking and trust formation[END_REF][START_REF] Mahmoodi | Equality bias impairs collective decision-making across cultures[END_REF][START_REF] Leong | Unrealistic optimism in advice taking: A computational account[END_REF][22] or the averaging heuristic [START_REF] Yaniv | Receiving other people's advice: Influence and benefit[END_REF][START_REF] Larrick | Intuitions About Combining Opinions: Misappreciation of the Averaging Principle[END_REF]. This point of view is not universally shared. Hawthorne-Madell and Goodman [START_REF] Hawthorne-Madell | Reasoning about social sources to learn from actions and outcomes[END_REF] defend a somewhat more relaxed view of what counts as a rational use of social information. Their model does not place a priori restrictions on the degree of competence that an agent should attribute to a random unknown agent. If an agent believes themselves to be more knowledgeable and reliable than others, it is rational for them to discount others' opinions. Indeed, under this assumption, the very fact that others disagree with the agent is evidence that their advice shouldn't be trusted [START_REF] Hawthorne-Madell | Reasoning about social sources to learn from actions and outcomes[END_REF]. This model, however, does not explain why an agent would believe themselves to be better informed and more reliable than any random agent, on a topic that neither agent is especially competent about.

We did a comprehensive search of the literature on five experimental tasks, detailed below.

Overall, between 45 (counting only clear cases) and 49 (counting ambiguous cases, see Supp.

Mat. Section 1 on what counts as a ambiguous case) of the studies we collected show that participants clearly fail to give enough weight to social information, showing excessive reliance on their own information, a phenomenon known as "egocentric discounting" in the advice-taking literature [START_REF] Yaniv | Advice Taking in Decision Making: Egocentric Discounting and Reputation Formation[END_REF]. We re-use this label, here, to name a phenomenon that goes far beyond advicetaking experiments. In contrast, we found only 3 publications (5 if we include two ambiguous cases) showing a bias in the other direction or an absence of bias. This review is no quantitative proof, but it is in line with the consensus view in the publications we surveyed (See supplementary materials, in particular section 1 on inclusion criteria). Evidence for egocentric discounting, which consists in giving individual information greater weight than would be normatively warranted, comes from at least three independent research traditions (social psychology, cultural evolution-inspired experiments, and behavioural economics). In all three, egocentric discounting came up as a surprise discovery-at least not one that previous theorising had predicted. These studies mainly use five broad types of tasks.

The advice-taking paradigm. The standard form of this task is the "Judge-Advisor System" [START_REF] Sniezek | Cueing and cognitive conflict in Judge-Advisor decision making[END_REF], but we also consider studies that do not use this exact paradigm, or do not explicitly do so, as well as studies from the forecast combination literature [START_REF] Harvey | Effects of judges' forecasting on their later combination of forecasts for the same outcomes[END_REF][START_REF] Soll | Strategies for revising judgment: how (and how well) people use others' opinions[END_REF]. In a typical advice-taking task, the participant is asked to make a quantitative judgement on a factual question (e.g. "What is the height of Mount Everest?"). Having given this first answer, they are confronted with another participant's answer, and allowed to give a second answer. Accurate answers are usually (but not always) incentivized (incentives tend to decrease the egocentric discounting effect without eliminating it) [START_REF] Bonaccio | Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences[END_REF]. The main variants involve presenting the participant with the other estimate before asking them for their own, presenting the participant with an average of the group's estimate, or allowing discussions between participants. The normative strategy in such tasks, for the second answer, is to average, i.e., to move halfway towards the other participant's guess [START_REF] Soll | Strategies for revising judgment: how (and how well) people use others' opinions[END_REF], unless one has reasons to think the advisor is clearly more (or less) knowledgeable than oneself.

All the studies we gathered find evidence of egocentric discounting, at least in their baseline condition: the participants' second guess modifies their first guess in the direction of the advisor's guess, but gives much more weight to the participant's first guess than to the advisor's.

Table 1 in the supplementary materials shows weight of advice (WOA) values (or similar measures) for 40 experiments across 17 publications. All 40 studies document a WOA below 0.5, consistent with egocentric discounting, in one condition at least (usually the baseline condition). Egocentric discounting can be modulated by changing the participants' confidence in their own answer and their perception of the advisor's expertise, but all this happens against a baseline of heavy discounting.

Two-armed bandit problems with social learning. In a typical task, a participant must choose between two options, A and B, one of which yields greater rewards on average. The payoff function linking A or B to the attached rewards is noisy, so that the best response can only be detected after a certain amount of exploration. Participants are typically informed about their rewards on each trial, with a piece of individual (and usually, private) information, but they are also informed about other participants' choices. This information may concern one participant, a few, or all previous participants, it may or may not include the feedback that these participants received, it may or may not be available for free. Given this variation, there is not one single optimal strategy for taking social information into account in all these tasks, and even inside a given task, what would constitute optimal use cannot always be straightforwardly determined.

Nevertheless, six studies show clear cases of egocentric discounting (vs. only one showing clear evidence of the opposite effect). In [START_REF] Efferson | Learning, productivity, and noise: an experimental study of cultural transmission on the Bolivian Altiplano[END_REF]'s "Best Color" condition, the option that gave the best payoff for the majority of participants on the previous round is announced, yet the model that best fits the data does not include social information. In [START_REF] Efferson | Conformists and mavericks: the empirics of frequency-dependent cultural transmission[END_REF], participants in the "social learning" condition are not given any individual feedback on their own responses, but they are told what the majority of participants chose in another condition, where those participants were given feedback. This information is under-used, resulting in sub-optimal choices. (Specifically, 12 out of 40 participants, self-described non-conformists, ignore it altogether.) In [32] (experiment 2), participants sometimes or (for 20 participants out of 55) always refuse to view a piece of information about others' choices that is made freely available and would have improved decisions if followed. In experiment 3 of the same study, a conformist strategy (imitating what the majority of participants did on the previous rounds) is consistently optimal but not consistently followed by participants, who tend to prefer relying on their own private information. Importantly, learning based on non-social information is, in these studies, highly effective (e.g. [START_REF] Efferson | Conformists and mavericks: the empirics of frequency-dependent cultural transmission[END_REF]). In other words, participants have no difficulty updating their behaviour when the feedback consists in individual (rather than social) information. This suggests that general difficulties with belief updating cannot explain social information under-use in these tasks.

"Virtual arrowheads" experiments. These experiments, developed by Mesoudi and his group (e.g. [START_REF] Mesoudi | An experimental comparison of human social learning strategies: payoff-biased social learning is adaptive but underused[END_REF][START_REF] Acerbi | Social learning solves the problem of narrowpeaked search landscapes: experimental evidence in humans[END_REF]) can be seen as a many-dimensional version of a multi-armed bandit task.

Participants devise, via a computer interface, arrowheads that are used for simulated "hunts", and rewarded depending on their hunts' success. Hunting success is a function of the arrowhead's properties (a range of parameters that participants determine). Although [START_REF] Mesoudi | An experimental simulation of the "copy-successful-individuals" cultural learning strategy: adaptive landscapes, producer-scrounger dynamics, and informational access costs[END_REF] found that participants readily consulted and used social information when given the opportunity to view the choices of other players for free, requiring participants to pay for this information clearly pushes them to rely on their own feedback instead. In subsequent studies where participants must choose between getting feedback on their own hunts and seeing other people's choices of arrowhead parameters, they choose the former, even though choosing the latter is more beneficial [START_REF] Mesoudi | An experimental comparison of human social learning strategies: payoff-biased social learning is adaptive but underused[END_REF][START_REF] Acerbi | Social learning solves the problem of narrowpeaked search landscapes: experimental evidence in humans[END_REF][START_REF] Mesoudi | Higher frequency of social learning in China than in the West shows cultural variation in the dynamics of cultural evolution[END_REF].

In the last two types of tasks, a participant must guess a given state of the world on the basis of cues provided by the experimenter, and may be given, in addition to these cues, information on other participants' choices (one or more). This general description fits both the use of cue-based learning paradigms in the advice-taking and social learning literatures [START_REF] Harvey | Taking Advice: Accepting Help, Improving Judgment, and Sharing Responsibility[END_REF][START_REF] Läpple | How do learning ability, advice from experts and peers shape decision making?[END_REF][START_REF] Tump | Individuals fail to reap the collective benefits of diversity because of over-reliance on personal information[END_REF][START_REF] Puskaric | How social and non-social information influence classification decisions: A computational modelling approach[END_REF], and the "balland-urn" task used by behavioural economists to simulate cascades (e.g. [START_REF] Anderson | Information Cascades in the Laboratory[END_REF], and see sup. mat.).

In addition to the cues, participants may be given feedback regarding the accuracy of their choices, but in "ball-and-urn" studies, no feedback is given until rewards are disclosed at the end of the task.

Cue-based learning. These studies, inspired by advice-taking tasks, differ from advice-taking tasks in one essential respect. Instead of basing their guesses on general knowledge, the subjects have access to a series of experimentally controlled cues. The subject makes a first guess on the basis of these cues, then makes a second (possibly revised) guess after being exposed to social information (either an expert's guess, or a peer's guess, or a group's average guess). Once again, participants fail to update their first guess as much as they should [START_REF] Harvey | Taking Advice: Accepting Help, Improving Judgment, and Sharing Responsibility[END_REF][START_REF] Läpple | How do learning ability, advice from experts and peers shape decision making?[END_REF][START_REF] Tump | Individuals fail to reap the collective benefits of diversity because of over-reliance on personal information[END_REF]. Here again we only looked for positive evidence for egocentric discounting, or for the opposite effect. We do not include studies whose design may have allowed them to capture egocentric discounting, but which do not mention it among their findings, possibly because they did not look for it. Possible examples include [START_REF] Puskaric | How social and non-social information influence classification decisions: A computational modelling approach[END_REF][START_REF] Collins | Integrating advice and experience: learning and decision making with social and nonsocial cues[END_REF].

Ball-and-urn tasks. In a typical ball-and-urn task (see sup. mat. for more information),the experiment starts with the experimenter randomly picking one out of two urns. Each urn contains balls of different colours, one urn having more balls of colour A, the other urn more balls of colour B. Participants, playing one after the other, are each given a ball drawn (with replacement) from the chosen urn. They must guess which of the two urns is being used, knowing that one urn contains more balls of colour A, the other more balls of colour B. (The ratio of A/B balls in each urn is typically known to the participants.) In addition to seeing the colour of their own ball (individual information), each participant knows the guesses made by everyone else before them. The studies in this group are the least straightforward to interpret, because of issues surrounding the normative criteria that apply to the task. To determine the weight that a participant should give to the decisions of the preceding participants, assumptions need to be made regarding their rationality, the probability that they err randomly, and the weight that they themselves put on their predecessors' decisions. Standard models, based on rational choice (in the specific sense of Bayesian updating) and game-theoretic equilibria [START_REF] Bikhchandani | Learning from the Behavior of Others: Conformity, Fads, and Informational Cascades[END_REF][START_REF] Kübler | Are Longer Cascades More Stable?[END_REF], assume that all agents update their beliefs in a fully normative way, and know that other agents also do.

Yet experimental participants do not behave in the normative way, as these models make clearly false predictions [START_REF] Kübler | Are Longer Cascades More Stable?[END_REF][START_REF] Weizsaecker | Do We Follow Others when We Should? A Simple Test of Rational Expectations[END_REF]. Since standard models are normatively valid for an agent only if other agents behave as the model say they should, which they do not, using them as a normative benchmark is questionable. Several alternative ways to prove egocentric discounting coexist in the literature. One consists in showing that a simple "private information" model, where participants take no account whatsoever of social information and only rely on their individual information, outperforms more complex model like the Bayes-Nash model [START_REF] Çelen | Distinguishing Informational Cascades from Herd Behavior in the Laboratory[END_REF][START_REF] Çelen | An experimental test of observational learning under imperfect information[END_REF][START_REF] Noth | Information Aggregation with Random Ordering: Cascades and Overconfidence[END_REF]. Another is to demonstrate that participants overweigh their private information both relative to the optimal Bayes-Nash model but also relative to more realistic models, like the Quantal Response Equilibrium model [START_REF] Goeree | Self-Correcting Information Cascades[END_REF]. Perhaps the most concrete demonstration comes from showing how much of the possible payoff participants forego by relying on private information (an important amount, while almost no payoff is lost from following social information) [START_REF] Weizsaecker | Do We Follow Others when We Should? A Simple Test of Rational Expectations[END_REF][START_REF] Ziegelmeyer | Do We Follow Others when We Should? A Simple Test of Rational Expectations: Comment[END_REF]. Together, these different lines of circumstantial evidence converge to show that participants in these tasks generally underuse social information.

Proximate explanations for egocentric discounting

Many potential explanations have been put forward to explain egocentric discounting [3,[START_REF] Bonaccio | Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences[END_REF][START_REF] Eriksson | Biases for acquiring information individually rather than socially[END_REF].

A generally endorsed explanation is that people put less trust in socially acquired information than in individual information [START_REF] Bonaccio | Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences[END_REF][START_REF] Krueger X | Return of the ego--self-referent information as a filter for social prediction: comment on Karniol[END_REF]. This explanation is not trivial. It does exclude some possible causes, for instance a general inability to revise one's opinions in the face of information of whatever nature. There is a general consensus that egocentric discounting is different from, and stronger than, a simple inability to update our beliefs [START_REF] Harvey | Effects of judges' forecasting on their later combination of forecasts for the same outcomes[END_REF][START_REF] Bonaccio | Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences[END_REF]. Belief updating in human adults is not optimal, but consistent evidence for a clear bias in favour of one's prior opinion is lacking [START_REF] Tversky | Evidential impact of base rates[END_REF]. In most of the "bandit" and "arrowhead" tasks, participants get private feedback on their actions, which they take into account in a near-optimal way, contrasting with their poor use of social information [START_REF] Efferson | Conformists and mavericks: the empirics of frequency-dependent cultural transmission[END_REF][START_REF] Toelch | Individual consistency and flexibility in human social information use[END_REF]. Likewise, participants in advice-taking tasks use new evidence efficiently when it is not social [START_REF] Yaniv | Receiving other people's advice: Influence and benefit[END_REF]22]. Self-confidence is a reliable predictor of egocentric discounting [START_REF] Bonaccio | Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences[END_REF]: indeed, as Hawthorne-Madell & Goodman show, it is rational (in the authors' specific sense) for a self-confident agent to discount divergent opinions. However, simply saying that people fail to place as much trust in other informants as they place in themselves eschews the main question. Why do we not trust others as much as we ought to?

Lack of ecological validity. The value of social information may be higher in experiments than it is in real life. According to a common critique of the experimental psychology of decisionmaking, subjects tackle laboratory tasks with a series of heuristics adapted to real-life circumstances that need not obtain in the lab, leading to a mere appearance of irrationality [START_REF] Gigerenzer | Reasoning the fast and frugal way: Models of bounded rationality[END_REF].

Is there evidence that people fail to profit from social information optimally outside the lab? Non-laboratory evidence that people fail to trust social information as much as would be useful for them includes studies of vaccine refusal, climate change skepticism, and resistance to mass persuasion attempts (synthesised in [START_REF] Mercier | Not Born Yesterday: The Science of Who We Trust and What We Believe[END_REF]). The experiments reviewed here represent a wide range of methodologies, some highly controlled, others much closer to everyday experience. Among the most ecologically relevant, the early experiments on forecast updating grew from ergonomic research [START_REF] Harvey | Taking Advice: Accepting Help, Improving Judgment, and Sharing Responsibility[END_REF][START_REF] Gardner | The effect of different forms of advice on the control of a simulated complex system[END_REF][START_REF] Lim | Judgemental adjustment of initial forecasts: Its effectiveness and biases[END_REF] What these studies ask of their subjects is little different from what they would do in the ordinary course of their life: update an epidemiological forecast or a medical treatment forecast, based on another opinion. Experiments in the advice-taking literature also place subjects in a fairly ordinary situation, that of updating one's estimate for a date (e.g. a historical or news event), a quantity (e.g., a price), given someone else's estimate. It is not clear how these tasks depart from ordinary situations in such a systematic way as to explain pervasive egocentric discounting.

Culture. One popular explanation among cultural evolutionists explains egocentric discounting as an effect of culturally inculcated individualistic values [1,[START_REF] Mesoudi | Higher frequency of social learning in China than in the West shows cultural variation in the dynamics of cultural evolution[END_REF][START_REF] Glowacki | Subsistence styles shape human social learning strategies[END_REF]. Individualistic cultural learning is thought to be a "Western" phenomenon, absent in some cultures at least: China, Japan or Korea [1,[START_REF] Nisbett | The Geography of Thought: How Asians and Westerners Think Differently[END_REF], or small-scale societies relying on pastoralism (according to [START_REF] Glowacki | Subsistence styles shape human social learning strategies[END_REF]). However, clear evidence for egocentric discounting has been found in both groups. Egocentric discounting was documented in Japanese [START_REF] Jayles | How social information can improve estimation accuracy in human groups[END_REF][START_REF] Mercier | Is the Use of Averaging in Advice Taking Modulated by Culture?[END_REF] and Chinese participants [START_REF] Mahmoodi | Equality bias impairs collective decision-making across cultures[END_REF][START_REF] Mesoudi | Higher frequency of social learning in China than in the West shows cultural variation in the dynamics of cultural evolution[END_REF][START_REF] Wang | Why Does Advice Discounting Occur? The Combined Roles of Confidence and Trust[END_REF], and in a group of executives from 24 different nationalities [START_REF] Soll | Strategies for revising judgment: how (and how well) people use others' opinions[END_REF]. While some studies find stronger rates of egocentric discounting in East Asian participants as opposed to Western ones [START_REF] Mercier | Is the Use of Averaging in Advice Taking Modulated by Culture?[END_REF], others do not [START_REF] Mahmoodi | Equality bias impairs collective decision-making across cultures[END_REF][START_REF] Jayles | How social information can improve estimation accuracy in human groups[END_REF]. In [START_REF] Mesoudi | Higher frequency of social learning in China than in the West shows cultural variation in the dynamics of cultural evolution[END_REF], only one sample of East Asian participants shows higher reliance on social learning, but the other two do not. Pastoralists in [START_REF] Glowacki | Subsistence styles shape human social learning strategies[END_REF] show less discounting of social information compared to horticulturalists or city-dwellers, but they still discount it, as do the Altiplano pastoralists studied in [START_REF] Efferson | Learning, productivity, and noise: an experimental study of cultural transmission on the Bolivian Altiplano[END_REF]. Overall, the literature shows some evidence for cultural modulations of egocentric discounting, but does not support seeing it as a Western peculiarity.

Geographical differences may also be determined by external factors (rather than culturally transmitted ideologies). For instance, experiencing economic and psychosocial adversity seems to increase reliance on social information [START_REF] Jacquet | In press. The ecological roots of human susceptibility to social influence: a pre-registered study investigating the impact of early-life adversity[END_REF].

Access to reasons. One standard explanation in the advice-taking literature holds that participants trust their own views more because they have access to their reasons for those views [START_REF] Yaniv | Receiving other people's advice: Influence and benefit[END_REF][START_REF] Yaniv | Exploiting the Wisdom of Others to Make Better Decisions: Suspending Judgment Reduces Egocentrism and Increases Accuracy[END_REF].

There are, however, reasons to doubt that this is a necessary condition. Results show that egocentric discounting occurs even when participants are asked to revise an estimate without being given access to the cues that motivated the estimate [START_REF] Soll | Judgmental aggregation strategies depend on whether the self is involved[END_REF] and that egocentric discounting is also observed when participants are presented with someone else's opinion, falsely presented as their own [START_REF] Harvey | Effects of judges' forecasting on their later combination of forecasts for the same outcomes[END_REF][START_REF] Trouche | Vigilant conservatism in evaluating communicated information[END_REF]: they put more weight than they ought to on opinions that are presented as their own.

Task engagement. In most of the studies we reviewed, participants may be more actively involved in processing or producing individual information, than in receiving advice. Active engagement in a task promotes learning in a way that passive observation does not, arousing the participants' attention to a greater extent and allowing them to encode information in distinctive ways [START_REF] Gureckis | Self-Directed Learning: A Cognitive and Computational Perspective[END_REF]. In "two-armed bandit" and "arrowheads" tasks, the level of engagement is often strikingly higher for individual information: the nature of the feedback that participants receive is a direct consequence of their intentional actions, whereas social information is produced by others. In some of these tasks, participants may decide whether or not they want to see others' choices, but the extent of their active involvement with social information ends there. In most advice-taking tasks, the participants actively generate their personal estimate, and are then passively exposed to someone else's. Could this explain egocentric discounting in such cases?

Partly, but once again it fails to explain why egocentric discounting obtains when participants are presented with someone else's opinion falsely presented as their own [START_REF] Harvey | Effects of judges' forecasting on their later combination of forecasts for the same outcomes[END_REF][START_REF] Trouche | Vigilant conservatism in evaluating communicated information[END_REF]. The best argument against an account of egocentric discounting based on the participants' active involvement may come from ball-and-urn tasks, where both individual and social information consist in passively received cues. Social information remains discounted. It is worth noting, however, that in experiments where social information has to be actively requested, instead of being passively presented, subjects are prone to request too much social information [START_REF] Çelen | Social Learning Through Endogenous Information Acquisition: An Experiment[END_REF][START_REF] Duffy | Information choice in a social learning experiment[END_REF], even when that information is worthless [START_REF] Goeree | Conformity in the lab[END_REF].

An anchoring effect in advice-taking tasks. These tasks typically ask a participant to formulate their own guess for a quantitative or numerical question, then to update it after being exposed to someone else's guess. These are favourable conditions for an anchoring effect to occur.

Anchoring effects happen when a piece of information biases an estimate because all subsequent estimates are referred to it and weighed in its direction, to a greater extent than they should be, and even when the piece of information is completely irrelevant -for instance, a random number [START_REF] Tversky | Judgment under Uncertainty: Heuristics and Biases[END_REF]. In one sense, egocentric discounting truly is a type of anchoring effect: the participants' initial estimate is given excessive weight, preventing them from updating their guess as much as they should. However, there are good reasons to reject the view that the general mechanisms at work in the anchoring effect explain egocentric discounting [START_REF] Harvey | Effects of judges' forecasting on their later combination of forecasts for the same outcomes[END_REF][START_REF] Bonaccio | Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences[END_REF][START_REF] Soll | Judgmental aggregation strategies depend on whether the self is involved[END_REF][START_REF] Schultze | On the Inability to Ignore Useless Advice[END_REF]. One reason is that an egocentric effect still obtains when participants complete a number of unrelated numerical estimation tasks between their first estimate and their last estimate, which should cancel any priming effect [START_REF] Harvey | Effects of judges' forecasting on their later combination of forecasts for the same outcomes[END_REF]. Furthermore, telling participants that an estimate is their own is sufficient to trigger egocentric discounting in favour of that estimate, even when the estimate is not actually their own, and is presented for the first time [START_REF] Harvey | Effects of judges' forecasting on their later combination of forecasts for the same outcomes[END_REF][START_REF] Trouche | Vigilant conservatism in evaluating communicated information[END_REF]. If egocentric discounting rested on a mere anchoring effect, labelling estimates as one's own or others should not matter. See [START_REF] Rader | Advice as a form of social influence: Informational motives and the consequences for accuracy[END_REF] for an exploration of the possible role of anchoring mechanisms in advice-taking more generally.

Low exploration rates in "bandit" and "arrowhead" tasks. In these two types of tasks, participants must update their behaviour in response to feedback, in a simulated environment where the payoff associated with each response is noisy, and may change over time. In some of these experiments, environmental changes are faster than in habitual real-life situations. A failure to adjust to the rapid rates of these changes could lead to conservatism, i.e., a tendency to stick to the solution one chose on previous trials (or remain close to it) instead of changing to the (correct) solution available with social learning. Two studies show a correlation between exploratory behaviour and social learning. In the "social and individual learning condition" of [START_REF] Acerbi | Social learning solves the problem of narrowpeaked search landscapes: experimental evidence in humans[END_REF] (Experiment 2), changes in the up-coming responses were greater for participants who opted to copy a model than for those who did not. In [START_REF] Derex | Social learning and the replication process: an experimental investigation[END_REF] participants in the "social learning" condition, who could see the solutions that other participants gave to the task, were more explorative than participants in the individual learning condition, who could not. The data in [START_REF] Acerbi | Social learning solves the problem of narrowpeaked search landscapes: experimental evidence in humans[END_REF] in particular raise the possibility that participants neglected social information because of a general aversion to exploration (in [START_REF] Derex | Social learning and the replication process: an experimental investigation[END_REF], it is not clear whether participants under-use social information). However, neither study establishes causation. In [START_REF] Derex | Social learning and the replication process: an experimental investigation[END_REF], the availability of social information is experimentally manipulated and controlled, so high exploration must be a consequence of social learning-not its cause. Another study that experimentally manipulates the availability of social information, and finds that social information induces a greater level of exploration, is [START_REF] Eriksson | Biases for acquiring information individually rather than socially[END_REF]. Here again, greater explorativeness cannot cause social learning. Both studies suggest that relations between exploration and social learning, when present, are likely to reflect an effect of social information upon exploratory behaviours, rather than the opposite. (See [START_REF] Toyokawa | Individual differences in learning behaviours in humans: Asocial exploration tendency does not predict reliance on social learning[END_REF] for additional evidence against a causal link between exploratory behaviour and social information use).

Evolutionary explanations for egocentric discounting

The mechanisms discussed in the previous sections have to do with the specifics of experimental situations, from participant selection to task demands. We now move on to possible explanations for egocentric discounting that see it as a functional and adaptive feature of the way we deal with social information.

Epistemic vigilance. Trouche et al. [START_REF] Trouche | Vigilant conservatism in evaluating communicated information[END_REF] interpret egocentric discounting through the lens of Sperber et al.'s epistemic vigilance framework [START_REF] Sperber | Epistemic Vigilance[END_REF]. In this view, human adults have an a priori reluctance to believe communicated information, unless accompanied by arguments or other guarantees of reliability. This default vigilance serves as a protection against attempted manipulation [START_REF] Sperber | Epistemic Vigilance[END_REF]. A straightforward implication seems to be that social information will be less readily accepted when a source intentionally communicates it, rather than letting it leak inadvertently. Yet, it is unclear whether participants in the experiments we just reviewed usually perceive social information as being intentionally communicated to them by the source. With a few exceptions [START_REF] Swol | The effects of confidence and advisor motives on advice utilization[END_REF], social information is merely introduced as another participant's opinion, leaving it unspecified whether the participant intended their opinion to be shown, or even knew that it would be. The same is true of most two-armed bandit tasks, arrowhead experiments, and cue-based learning tasks: social information is eavesdropped by its recipient, not openly communicated by its source. The major exception are "ball-and-urn" experiments, where participants know that their answers will be made public to all subsequent participants [START_REF] Anderson | Information Cascades in the Laboratory[END_REF][START_REF] Weizsaecker | Do We Follow Others when We Should? A Simple Test of Rational Expectations[END_REF].

Contrary to what epistemic vigilance might imply, this seems to cause participants to trust social information more, not less. Participants in ball-and-urn tasks tend to answer in ways that are helpful for others (but possibly harmful for themselves). Working with a task similar in its main features to the ball-and-urn tasks, [START_REF] Çelen | An Experimental Test of Advice and Social Learning[END_REF] argue that participants are aware of this, and show that participants are more likely to follow their predecessor's advice than to imitate their action-the opposite of what epistemic vigilance would suggest. This piece of counter-evidence is merely suggestive: testing the epistemic vigilance hypothesis would require experiments that make it clear to participants whether other participants intentionally produced social information for other participants to use.

A producer-scrounger dilemma for information use. Social information is only useful when others also gather information asocially. Cultural-evolutionary models contain a possible explanation of egocentric discounting. Rogers' influential model [START_REF] Rogers | Does Biology Constrain Culture?[END_REF] showed that social learning may not provide any advantage over individual learning when the environment changes. The advantage of using social learning depends on the frequency of social learners in the population: if those are too numerous, social learning is useless. When there are mostly individual learners, copying is effective, because it saves the costs of individual exploration, and because the probability of copying a correct behaviour is high. However, when there are mostly social learners, the risk of copying an outdated behaviour increases and individual learners are advantaged. This means the advantages of social-learning are inversely frequency-dependent: the more other people learn socially, the less efficient it is to learn from them. The same logic is reflected, on a smaller scale, in models of information cascades, where social learning can (with a small probability) become detrimental for an individual when too many other individuals resort to it. More generally, a broad range of models converge upon the view that social information use can be likened, in terms of evolutionary game theory, to a producer-scrounger dynamic [START_REF] Mesoudi | An experimental simulation of the "copy-successful-individuals" cultural learning strategy: adaptive landscapes, producer-scrounger dynamics, and informational access costs[END_REF][START_REF] Toyokawa | Individual differences in learning behaviours in humans: Asocial exploration tendency does not predict reliance on social learning[END_REF][START_REF] Kameda | Cost-benefit analysis of social/cultural learning in a nonstationary uncertain environment An evolutionary simulation and an experiment with human subjects[END_REF]. At equilibrium, these games typically yield a mixed population of producers (individual learners) and scroungers (social learners), where neither type does better than the other [START_REF] Dall | Information and its use by animals in evolutionary ecology[END_REF][START_REF] Laland | Social learning strategies[END_REF]. Egocentric discounting might emerge from a producer-scrounger dilemma, as a response to the devaluation of social information which may occur when too many other agents rely on social learning. This hypothesis potentially explains several phenomena related to egocentric discounting. A frequency-dependent equilibrium could account for egocentric discounting in a subset of experimental participants [83]. These participants could be wasting social information for two reasons, a strategic one and an altruistic one. The strategic reason starts from the premise that other participants rely excessively on social learning, making it hazardous to follow them. On a more altruistic account, egocentric discounting may be a way to help the community of participants with first-hand information [START_REF] Eriksson | Biases for acquiring information individually rather than socially[END_REF]. Egocentric discounting, in this perspective, is altruistic: it increases the amount of information circulating in a group, at the cost of making the discounter less accurate [START_REF] Bikhchandani | Learning from the Behavior of Others: Conformity, Fads, and Informational Cascades[END_REF]. Only two studies, to our knowledge, address the possible effect of altruistic motivations on egocentric discounting. In Eriksson & Strimling [START_REF] Eriksson | Biases for acquiring information individually rather than socially[END_REF], subjects who scored high on a prosocial attitudes survey (Social Value Orientation scale) showed a greater propensity to acquire individual as distinct from social information, although [START_REF] Duffy | Information choice in a social learning experiment[END_REF] fails to find an impact of self-reported altruistic tendencies on subjects' preferences for social or private information. A "producer-scrounger equilibrium" account may also explain the widely documented inter-individual heterogeneity in propensities for social learning [START_REF] Toelch | Individual consistency and flexibility in human social information use[END_REF][START_REF] Toyokawa | Individual differences in learning behaviours in humans: Asocial exploration tendency does not predict reliance on social learning[END_REF][START_REF] Olsen | Knowing whom to learn from: individual differences in metacognition and weighting of social information[END_REF][START_REF] Molleman | Consistent individual differences in human social learning strategies[END_REF] since such an equilibrium is based upon the coexistence of two opposite strategies. However, this account leaves several questions unanswered, which future work might address.

-How do we explain egocentric discounting at the aggregate level? The experiments we review document egocentric discounting effects at the level of entire groups of subjects. Even though inter-individual variation, when explored, can be large, the discarding of social information is not driven by a minority, and it is not compensated, overall, by an equally strong tendency in the opposite direction. Why are there so few information scroungers? -Do egocentric discounters expect others to over-rely on social information, and why? The producer-scrounger dilemma account appears to assume that people waste social information because they assume (consciously or not) that others are too reliant on it, making it less useful. But in most of the studies we reviewed the opposite holds true: most participants rely too little on social information, not too much.

Conclusion

There is little doubt that our species relies a great deal on social information, and that cultural transmission would be impossible if we did not use it [START_REF] Richerson | Not by genes alone[END_REF][START_REF] Sperber | Epistemic Vigilance[END_REF][START_REF] Sterelny | The Evolved Apprentice: How evolution made humans unique[END_REF]. This makes the well-known phenomenon of egocentric discounting all the more puzzling. This paper documented it across five different experimental paradigms (going beyond standard cases of egocentric discounting in the advice-taking literature). Several independent research traditions uncovered different aspects of the same phenomenon, a phenomenon that none of them had predicted. Combining the results of a diverse range of tasks allows for a better assessment of the most common explanations. Our review highlights the difficulty of explaining away egocentric discounting with any single-cause account, and stresses the need to study egocentric discounting through the lenses of the multiple research traditions that have investigated it. Those complement each other. Social psychology is strong on ecological validity. Cultural evolution research seeks diverse subject pools of participants. Experimental economics is weaker on both these counts, but cascade experiments provides evidence against mechanisms that play a role in other paradigms: for instance, task engagement or epistemic vigilance.

A closer look at egocentric discounting also addresses a long-running debate in cultural evolutionary theory. A long-standing critical argument rightly stresses the artificial nature of the distinction between social and individual learning [START_REF] Heyes | Imitation, culture and cognition[END_REF][START_REF] Sterelny | The Evolution and Evolvability of Culture[END_REF]. Social learning, as the critics point out, need not be anything but individual learning from social cues: humans require no specialpurpose adaptation, no dedicated cognitive module to learn from others. We fully agree with this stance, with one subtle difference. Individual and social information may be processed by the same mechanisms, but not on an equal footing. The information that one gets on one's own engages our attention differently; it is more tractable and traceable than information that comes to us filtered through others' minds. Because it is acquired independently, it is also of more use to others than second-hand information.

Cultural evolution, alongside social psychology and experimental economics, has done much to document and explore the fact that socially acquired information may be given less weight than equivalent individual information. No extant theory predicts this phenomenon in all its dimensions or in a straightforward way. An exciting next step could consist in drawing the cultural consequences of our reluctance to incorporate information: how it impacted the evolution of social learning in our evolutionary past, and the diffusion of culture throughout our history.

Electronic Supplementary Material: Accessible at [URL to be added after peer-review].

[Appended to this submission.] Funding. This work has received funding from the "Frontiers in Cognition" EUR grant, ANR-17-EURE-0017 EUR. P.O.J. was supported by ANR-10-IDEX-0001-02 PSL.

Inclusion criteria

This document summarizes a comprehensive search of three literatures-social psychology, cultural evolution, and experimental economics. We looked specifically for empirical studies of social learning where human adult participants could access information from other human adults. (We include Gardner & Berry's 1995 study, where advice comes from a computer expert system because it is historically important and highly influential.) Studies of social learning in non-human animals or in children do not fall under the purview of this review. The non-human literature is too vast for a single paper to tackle it alongside the human literature. The developmental literature on social learning is more directly relevant but we believe the expertise gap between children and the adults they interact with is so broad as to cancel any specific effect of egocentric discounting [START_REF] Mascaro | Optimistic expectations about communication explain children's difficulties in hiding, lying, and mistrusting liars[END_REF]. (But see Atkinson et al., 2020 for an example of social learning in children, where egocentric discounting is not observed.) Since we needed reliable criteria against which to measure the efficient use of social information, we excluded tasks where the task lacks a straightforward normative solution. In other words, we focus on tasks where participants must make a guess (or a bet) concerning a state of affairs that is independent not only of their own opinion, but also of other participants' views. This excludes the vast literature on persuasion and attitude change, where participants are exposed to arguments concerning policy interventions (e.g., Should abortion be legal?) or matters of taste (e.g., Which colour do you prefer?). For similar reasons, we also excluded studies where the nature of the rational response depends on other people's responses, as happens in most economic games (e.g. Prisoner's dilemmas). For similar reasons, we excluded studies where "normative conformity" [START_REF] Deutsch | A study of normative and informational social influences upon individual judgment[END_REF], i.e., the pressure to give a response in conformity with other participants' responses for reasons of social desirability, was likely to play an important role: this explains the absence of Asch's famous experiment [START_REF] Asch | Opinions and social pressure[END_REF] and its various replications. We also excluded tasks based on strategic interactions (e.g., public goods game, ultimatum game, etc.), where aligning with others' actions may be beneficial or detrimental in itself, neither option being intrinsically "right" or "wrong" (e.g., [START_REF] Molleman | Societal background influences social learning in cooperative decision making[END_REF]. The various fields studying social learning use a wide variety of methods and measurement tools. There is no such thing as a unified metric for egocentric discounting, which the five families of studies covered here would share. The closest thing to such a metric is the "weight of advice" measure used in Judge-Advisor-System tasks (although WOA-like measures come in several variety: see the legend for Table 1). We collected WOA and similar measures whenever possible, to get a systematic and quantitative overview. For other studies, however, we rely on verbal descriptions, since the methods and measurements used are not commensurable. For all clear cases of egocentric discounting, we rely on the authors' interpretation, in their own words. When the evidence is less clear-cut we explain how we interpret the study. The following survey distinguishes two categories of evidence: ambiguous and nonambiguous. We count evidence is ambiguous if there are good reasons to doubt the effect as interpreted by the authors, or if we suspect the existence of an effect but the authors do not explicitly make this claim.

Advice-taking tasks

We include in this category all the studies that we found where a participant was asked to produce her individual answer to a numerical or quantitative question, then, having made this first guess, was confronted with that of another participant (real or fictitious), or (in rare variants) several participants. This survey mostly brought back studies from the literature on advice-taking, usually carried out with the Judge-Advisor System paradigm, as well as forecast combination tasks. We also include studies like ( Several studies measuring the "wisdom of crowds" effect provide relevant data because they measure participants' propensity to revise their opinion when exposed to a group's average guess (Jayles et al., 2017;[START_REF] Kerckhove | Modelling Influence and Opinion Evolution in Online Collective Behaviour[END_REF]. Lastly, two studies using an original methodology are [START_REF] Heath | Interaction with Others Increases Decision Confidence but Not Decision Quality: Evidence against Information Collection Views of Interactive Decision Making[END_REF], where exposure to the advisor's advice is replaced with live interactions, and Gardner & Berry, who use an idiosyncratic set-up (see description below). Our goal here is simply to show the pervasiveness of egocentric discounting and its importance. Bonaccio & Dalal's authoritative review (Bonaccio & Dalal, 2006) provide a comprehensive overview of the various factors that modulate egocentric discounting, not covered in this supplementary material. 16/03/2021 18:13:00

Advice-taking studies, reporting the weight of advice (or a related measure) (17 publications)

We include here all the studies we could find that measure egocentric discounting with a reported "Weight of Advice". When a participant updates her estimate in response to another participant's estimate, the rational strategy (other things being equal) is to use a WOA of 0.5, i.e., to move halfway towards the other participant's estimate. A WOA significantly below 0.5 is evidence of egocentric discounting. Most studies using the Judge-Advisor System report a "Weight of Advice" measure to assess egocentric discounting. All the studies that report this measure for one experiment at least are gathered in Table 1 below. Most studies include a control or baseline condition (i.e., subject's first guess > advisor's guess > subject's second guess) coupled with a test condition (e.g., modulating the difficulty of the task) designed to decrease egocentric discounting and increase the WOA, often successfully. Without a single exception, all studies find a WOA below 0.5, consistent with egocentric discounting, in at least one condition (the baseline, usually). We provide standard deviations and number of subjects when available.

Advice-taking studies, not reporting the weight of advice (or using other measures)

This list gathers all the relevant studies that did not report a raw weight of advice (or similar) measure, but described relevant effects either qualitatively or quantitatively through a different measure. We only mention positive evidence for egocentric discounting or for the opposite effect. We did not include studies whose design may have allowed them to capture egocentric discounting, but which do not mention it among their findings, because they did not look for it. Possible examples include two studies by Sniezek and co-authors (Sniezek & Buckley, 1995;[START_REF] Sniezek | Trust, Confidence, and Expertise in a Judge-Advisor System[END_REF]).

Evidence of Egocentric Discounting (12 publications)

Chacoma & Zanette (2015), one unique experiment. "The most frequent instance recorded in the experiment corresponds to no change in the answers (...)-in agreement with a comparable result in the original version of the experiment. In almost 60% of the events, the subjects chose not to modify their answers, while their confidence remained the same in more than 70%." (p. 13 We show that individuals behave near Bayes optimal when integrating two distinct sources of social information but systematically deviate from Bayes optimal choice when integrating individual with social information… In general, models confirmed that players underused social information when integrating social and individual information." (p. 1746) Yaniv & Choshen-Hillel (2012), all 3 experiments. "In three studies, participants used others' opinions to estimate uncertain quantities (the caloric value of foods). In the full-view condition, participants could form independent estimates prior to receiving others' opinions, whereas participants in the blindfold condition could not form prior opinions. (…) In all studies, the blindfolded participants provided more accurate estimates than did the full-view participants. (…) … the advantage of the blindfolded participants was due to their unbiased weighting of others' opinions." (p. 427)

Ambiguous evidence of Egocentric Discounting in an atypical task (1 publication)

Gardner & Berry (1995), Experiments 1 and 2 of 3. Note: This study does not follow the judge-advisor paradigm, and it is atypical in two respects. Subjects received advice from a computer "expert system" instead of a human advisor, and they had numerous occasions to make decisions based on this advice and based on the feedback they received. In the "Optional Advice" condition of experiment 1, subjects may use that is accurate and improves performance, if used. Yet it is ignored 40% of the time (p. S64-S65). This phenomenon is again observed in experiment 2, where the advice is explained verbally. Experiment 3 does not directly address egocentric discounting.

Ambiguous evidence for the opposite effect (2 publications)

Leong & Zaki (2018), all 2 experiments. Note: In this study, participants rely excessively on the advice of two virtual characters, which are misleadingly (in our view) presented as experts. In experiment 1, the three characters in this simulated financial decision task are presented as "financial advisors", suggesting relevant expertise, even though only one makes predictions more accurate than chance. In experiment 2, one crucial advisor receives aboveaverage ratings even though his performance is no better than chance. (Removing this misleading cues of competence cancels the effect.) Schultze et al. (2017), all 4 experiments. Note: Participants follow an advisor's opinion even when they have no reason to do so, because the advisor's estimate is preposterously off the mark, or because they know the advisor is a random numbers generator. This reversal of egocentric discounting relies entirely on an anchoring effect (see below on anchoring effects as potential explanations for egocentric discounting). The authors present their effect as compatible with egocentric discounting, which they see as a distinct mechanism.

"Multi-armed bandit" tasks

The experiments included here allow participants to choose between different bets (typically two) to obtain different payoffs. Some bets are associated with higher payoffs, but the relationship is noisy. Social information comes in the form of exposure to other participants' bets, possibly accompanied by their payoffs. Performance is incentivized as a rule, in contrast to the Judge-Advisor System literature where rewards often fail to follow performance. This list only mentions positive evidence for egocentric discounting or for the opposite effect. We did not include studies whose design may have allowed them to capture egocentric discounting, but which do not mention it among their findings, possibly because they did not look for it. [In Experiment 2, the "Farming game"] "… there was considerable individual variation in the use of this social information in planting decisions, and for many participants the observed social information had little influence on their planting decisions." (p. 4) Note: egocentric discounting was not clearly reported for the first experiment, a perceptual discrimination task with social input. shows greater utilization of social learning, yet it is not clear whether social learning reaches optimal level even in that group. Läpple & Barham (2019), one unique experiment. "… the subjects could have improved further by utilizing more advice. Therefore, our finding is also in line with the general literature on advice taking, which reports that people often discount advice and give greater weight to their own opinion (…). … expert advice utilization was 48 percent, while subjects put 52 percent of weight on their own initial estimate. This implies that on average, given own and expert's experience levels, subjects were egocentric towards their own opinions and discounted advice" (p. [START_REF] Yaniv | Receiving other people's advice: Influence and benefit[END_REF]

"Ball-and-urn" cascade experiments (and variants)

The studies listed here originate as variants of Anderson & Holt's protocol to test models of information cascades [START_REF] Anderson | Information Cascade Experiment[END_REF]Bikhchandani et al., 1998). In the original design, participants sequentially make guesses concerning the probability of drawing a ball of a given colour from an urn, based on their private information (the colour of one drawn ball) and on the sequence of other participants' previous bets. Studies using this basic design have not been reviewed here: instead, we cite two authoritative meta-analyses. Variants of the basic design include not informing participants of one previous choice instead of a whole sequence (Çelen & Kariv 2004(Çelen & Kariv , 2005)), or restricting access to the other participants' decisions in various ways. Performance is always incentivised. 6.1. Evidence of Egocentric Discounting (4 publications including 2 meta-analyses) Çelen & Kariv (2004), one unique experiment. "…subjects give excessive weight to private information relative to the public information revealed by the behaviour of others" (p. 497) Çelen & Kariv (2005), one unique experiment. "… under imperfect information, followown-signal heuristic out-performs Bayes' rule as a predictor. In contrast, under perfect information although in Bayesian terms subjects assign too much weight to their own information and too little weight to the public information they gradually increase their confidence in the information revealed by the history of actions taken before them." (p. 695) Weizsaecker (2010), meta-analysis of 13 experiments. "The average player contradicts her own signal only if the empirical odds ratio of the own signal being wrong, conditional on all available information, is larger than 2:1, rather than 1:1 as would be implied by rational expectations." (p. 2340) Ziegelmeyer et al. (2013), meta-analysis of 13 experiments. "... participants quite often fail to contradict their signal in decision situations where it is beneficial to do so though they (almost) always follow their signal in the complementary set of decision situations." (p. 7) 6.2. Evidence for an absence of bias (1 publication) Duffy et al. (2019), one unique experiment. "Our experiment modifies the standard sequential social learning setting. Subjects have to choose to observe either a private signal or the decisions made by earlier subjects in the sequence, rather than having both forms of information supplied by default. (…) In the aggregate, we find no overall bias for or against private information. In other words, when mistakes can run both ways, they do indeed run both ways." (p. 27-28) 6.3. Evidence for the opposite effect (2 publications) Çelen & Hyndman (2012), one unique experiment. "Our experiment consists of a group of four subjects who sequentially make decisions on the same problem. Each subject is endowed with a piece of information regarding the fundamentals of the problem. In addition to his private information, each subject, before making a decision, is allowed to form links to his predecessors. Forming a link is costly, yet it allows a subject to observe the actions of those with whom he linked. (…) … we show that subjects have a tendency to form too many links." (p. 1526) Goeree & Yariv (2015), one unique experiment. "… subjects choose between observing a private (statistically informative) signal or the history of play of predecessors who have not chosen a private signal (i.e., a statistically uninformative word-of-mouth signal). In our setup, subjects choose the statistically uninformative social signal 34 % of the time and, of those, 88% follow their observed predecessors' actions." (p. [START_REF] Giraldeau | Potential disadvantages of using socially acquired information[END_REF]

) 1

 1 De Filippis et al. (2016), one unique experiment. "Our main result is that subjects update on their private signal in an asymmetric way. They weigh the private signal as a Bayesian agent would do when the signal con...rms their prior belief; they overweight the signal when it contradicts their prior belief." (p. 1) Harvey & Harries (2004), experiment 2 of 2. "[InExperiment 2]... people combining forecasts put more weight on forecasts that are their own (whether or not they are labelled as such) or are labelled as their own (when they are not) than on equivalent forecasts that are neither their own nor labelled as such." (p. 391) Note: Experiment 1 deals with forecasts combination, not directly with Egocentric Discounting.Heath & Gonzalez (1995), Experiments 1-2 of 3. "[These] two studies show that interaction [with other participants] does not increase decision accuracy. (...) According to the studies in this paper, it appears that interaction is relatively ineffective as information collection. Decision quality does not improve much after interaction." (p. 305). Note: Experiment 3 focuses on rationalization as distinct from decision-making. Kerckhove et al. (2016), one unique experiment. "Most individuals overweight their own opinion compared to the mean opinion to revise their judgment … in accordance with the related literature on the subject. (p. 4) Lim & O'Connor (1995), all 3 experiments. "The studies reported in this paper examine the efficacy of allowing people to adjust their own forecasts in the light of statistical forecasts that are provided to them. (…) … people had considerable difficulty placing less weight on their own forecasts (compared to the statistical forecasts) and this behaviour became more pronounced over time. Even provision of decision support did not improve performance at the task." (p. 149) Mahmoodi et al. (2015), Experiment 1 of 4. [In Experiment 1] "When collapsed across dyad members, participants showed a small egocentric bias, confirming their partner's decision in 45 ± 16% (mean ± SD) of disagreement trials. This result is consistent with previous works on egocentric advice discounting." (p. 2) Note: The next experiments (2 to 4) do not address egocentric discounting. Mannes (2009), Experiments 2-4 of 4. "[In Experiment 2] participants improved upon their initial judgments but were conservative in their use of advice-increases in influence declined at a faster rate than recommended by an ego-neutral judgment policy. Accordingly, their observed policies failed to weight appropriately the more accurate and reliable judgments." (p. 1272) "[In Experiment 3] because ... participants placed too much weight on their initial beliefs, they underperformed the ego-neutral judgment policies." (p. 1274) "[In Experiment 4] participants continued to underperform the ego-neutral judgment policies." (p. 1276) Note: Experiment 1 does not ask participants to combine or confront their own estimate with that of a group. Minson et al. (2011), all 4 experiments. "[In the four studies] dyad members failed to give due weight to a partner's estimates" (p. 1325) Morgan et al. (2012), Experiment 2 of 4. "The rarity of conditions under which conformist behaviour is realized suggests a bias towards asocial over social information." (p. 660) Moussaïd et al. (2013), Experiment 2 of 2. "… participants exhibited a significant bias toward their own initial opinion rather than equally weighting all social information they were exposed to" (p. 6) Note: Experiment 1 addresses only individual performance. Toelch et al. (2014), one unique experiment. "

3 . 1 .

 31 A possible example includes McElreath et al. (2005). Evidence of Egocentric Discounting (6 publications) Efferson et al. (2008), one unique experiment. "A subset of social learners behaved according to a classic model of conformity. The remaining social learners did not respond to frequency information." (p. 56) Efferson et al. (2007), one unique experiment. "The analysis ... found neither a clear tendency to imitate success nor conformity. Players instead seemed to rely largely on private feedback about their own personal histories of choices and payoffs." (p. 11) Eriksson & Strimling (2009), Experiment 1 of 2."We found that people explore a smaller number of further options after having individually acquired information about three options, compared to when they had socially acquired the same information. This result supports our hypothesis that individually acquired information has greater cognitive impact than socially acquired information." (p. 10) Note: Experiment 2 does not directly address the importance of egocentric discounting but considers how personality traits may affect it. Najar et al. (2019), all two experiments. "The comparison of the private reward learning rate with the imitation learning rate was overall consistent with an egocentric bias." (p. 2) Toelch et al. (2014), Experiment 1 of 2.

4 . 1 .

 41 look for it. Possible examples include (Atkisson et al., 2012; Derex et al., 2015; Mesoudi, 2008; Mesoudi & O'Brien, 2008). Evidence of Egocentric Discounting (3 publications) Acerbi et al. (2016), one unique experiment. "… as in previous experiments social information was generally underutilized" (p. 1) Mesoudi (2011), one unique experiment. "… individual learning was chosen significantly more often than payoff bias, random copying, conformity, and averaging." (p. 338) Mesoudi et al. (2015), one experiment with 4 populations: 3 out of 4 populations. "We have … replicated, in our UK sample, the sub-optimal under-utilization of social information observed in the UK sample of a previous study that used the same task. (...) Despite their Chinese heritage, Hong-Kong and Chinese Immigrant participants were comparable to UK participants in their copying frequencies." (p. 6) Note: The fourth sample (mainland China)

5. Cue-based learning tasks 5 . 1 .

 51 Evidence of Egocentric Discounting (3 publications) Harvey & Fischer (1997), all 2 experiments. "… [subjects'] ability to use advice to improve judgement appears constrained by their overestimation of their own judgment skill relative to that of people who have had as much or more training."

- 22 )

 22 Novaes Tump et al. (2018), one unique experiment. "… individuals were relatively reluctant to incorporate social information and instead used suboptimal switching thresholds" (p. 7)

  De Filippis et al., 2016; Morgan et al., 2012, Experiment 2; Toelch et al., 2014, Heath & Gonzalez 1995) that do not derive from the advice-taking research traditions, but that use a highly similar task, with analogous results.

Table 1 . Weight of advice in 17 publications studying the Judge-Advisor System

 1 . (See references for the sources.) # The authors calculated a measure of Social influence that is very close to the standard WOA, both in its metric and interpretation. * The authors calculated a measure quantifying the weight given to one's own estimate (WOO). This measure in the inverse of the standard WOA. Hence, the values reported in the table correspond to the reversed WOO, that is, to the WOA. ° The authors adjusted the mean WOA for several covariates *^ InSoll & Larrick's (2001) Study 1 and Study 2, two main independent conditions are operationalized (No feedback on accuracy vs Feedback on accurcay), but only the WOA averaged over these two conditions is provided. ** The values reported in the table correspond to the reversed WOO (see *). The values reported for each level are the average of 3 subconditions (self better, equal accuracy, advisor better) detailed in table 3 of the Soll & Mannes study (2012) *° The values reported for each level are the average of two subconditions (with vs. without feedback) detailed Table 3 of the Yaniv & Kleinbergen study (2000). " The values reported for each level are the average of two subconditions (High vs low subject's knowledge) detailed in table 3 and table 5 of the Yaniv study (2004).

	Author(s)	Publication date	Country	Judgement type	Study # N Mean age Design	Mode of advice presentation	Main independent variable	WOA (SD)
				General knowledge	Study 1	73	19-26	Between-subjects	Conditional on subject's choice	Free advice	0.46 (0.09)
	Gino	2008	USA	General knowledge	Study 2	88 26	Between-subjects	By default	Paid advice Free advice Paid advice	0.72 (0.08) 0.62 (0.03) 0.42 (0.09)
				Perceptual	Study 1	102	21	Between-subjects	Conditional on subject's choice	Axiety induction	0.55 (0.26)
										Neutral	0.29 (0.26)
										Anxiety induction	0.51 (0.30)
				Perceptual	Study 2	127 21	Between-subjects By default	Neutral	0.36 (0.16)
										Anger induction	0.21 (0.14)
	Gino et al.	2012	USA	Perceptual	Study 4	122	32	Between-subjects	By default	Anxiety induction	0.61 (0.37)
										Neutral	0.36 (0.41)
				Perceptual	Study 5.c	118	21	Between-subjects By default	Anxiety induction	0.58 (_)
										Neutral	0.12 (_)
				Perceptual	Study 6	139	20	Between-subjects	By default	Anxiety induction Neutral	0.60 (_) 0.24 (_)
				Perceptual	Study 1	61	24	Within-subject	By default	No perceptual uncertainty	0.41 (0.03)
	Gino & Moore	2007	USA							Perceptual uncertainty	0.52 (0.03)
				Perceptual	Study 2	57	25	Within-subject	Conditional on subject's choice	No perceptual uncertainty Perceptual uncertainty	0.39 (0.05) 0.54 (0.03)
	Hofheinz et al.	2017	Germany	Perceptual	Study 1	56 39	Between-subjects By default	Participants without depressive symptoms	0.23 (0.15)
										Participants with diagnosed depressive symptoms	0.33 (0.17)
	ayles et al.	2017	France Japan	General knowledge General knowledge	Study 1 Study 2	180 186		Within-subject Within-subject	By default By default	_ _	0.45 (_) # 0.70 (_) #
	Koehler & Beauregard	2006	Canada	General knowledge	Study 3	88	_	Between-subjects	By default	Advice provided before the personal estimate	0.38 (_)*
										Advice provided after the personal estimate	0.32 (_)*
	Mercier et al.	2012	France/Japan	General knowledge	Study 2	115 _	Between-subjects By default	Subjects from Western culture (France)	0.28 (_)*
										Subjects from Eastern culture (Japan)	0.43 (_)*
				Perceptual	Study 1	191 23	Within-subject	By default	_	0.22 (0.14)
	Schultze et al.	2017	Germany	Perceptual	Study 2	251 21	Within-subject	By default	_	0.21 (0.14)
				Perceptual	Study 3	351 23	Within-subject	By default	_	0.24 (0.12)
				Perceptual	Study 2	63 _	Within-subject	By default	_	0.45 (0.23)
										Low power induction	0.28 (_)°N
	See et al.	2011	USA	Perceptual	Study 3	254	_	Between-subjects	By default	o induction	0.26 (_)°H
										igh power induction	0.19 (_)°L
				Perceptual	Study 3	126 _	Between-subjects By default	ow power induction	0.25 (_)°H
										igh power induction	0.19 (_)°J

This quote, like all other quotes in this document, describe the study's relevant result (as opposed to generalities or results of other studies).

Supplementary Materials: An overview of egocentric discounting effects

Table of Contents

Toyokawa et al. (2019), one unique experiment. "… the social learning weight['s]… estimated mean value was 𝜎̄ = 0.3. This implies a weaker social than asocial influence on decision-making as reported in several other experimental studies (…). Thanks to this relatively weak reliance of social learning, the kind of herding that would have blindly led a group to any option regardless of its quality (like the 'symmetry breaking' known in social insect collective foraging systems…) did not occur." 3.2. Ambiguous evidence of Egocentric Discounting (3 publications) Glowacki & Molleman (2017), Experiments 1-2 of 3 experiments (one study with 3 different populations). Note: At least two of the three groups of participants (the urban dwellers and the pastoralists) fail to request social information most of the time. Social information consists in the last decision of three other players, and thus it is likely to be at least as useful as information regarding a participant's own decision.

McElreath et al. (2005), Experiments 2-3 of 3. Note:

In experiment 2, participants can access, for free, information on the behaviour of another (randomly picked) participant (but not their payoff). 20 out of 55 participants never or rarely used this information. Social learning was higher in experiment 3, where participants could access the whole group's choices. (Social learning was impossible in experiment 1, a purely individual task.) Toyokawa et al. (2017), one unique experiment. Two-thirds of the participants make no use at all of the information they are given concerning the choices of another player. However, it is unclear whether using this information would be beneficial at all.

Evidence for the opposite effect (1 publication) Yahosseini et al., 2018), one unique experiment. "

The harmful effect of social information is caused by the participants' tendency to copy social information too early in the experiment, without knowing its relative value compared to what can be discovered by individual exploration." (p. 5)

"Virtual arrowheads" tasks

These experiments simulate the manufacture of arrow blades and its evolution in a virtual environment. Participants are asked to specify several characteristics of their arrowheads, each combination of characteristics being associated with a (noisy) payoff. The task can be seen as a many-dimensional version of a multi-armed bandit task. Performance is systematically incentivized. Social information comes as information concerning the other participants' arrowhead designs, possibly accompanied by the associated payoffs. This list only addresses positive evidence for egocentric discounting or for the opposite effect. We did not include studies whose design may have allowed them to capture egocentric discounting, but which do not mention it among their findings, possibly because they did not