Reports of the Death of Expertise May Be Exaggerated: Limits on Knowledge Resistance in Health and Medicine

During the past decade the idea that expertise is dead, or at best moribund, has become commonplace. Knowledge resistance appears to be growing more politicized and is increasing across a wide range of science-based topics, such as agriculture, evolution and genetics, vaccination, and climate change; even flat-earth beliefs are undergoing a renaissance. But in many of these areas, denying expert authority is cost-free in everyday behavior, making it more rational for people to prize identity and group affiliation over realism. To probe the health of expertise in a domain with everyday consequences for knowledge resistance, we conducted three incentive-compatible studies of laypeople’s preferences for sources of information they would read about specific medical conditions (e.g., heart disease, cancer, COVID-19). We found quite rational preference patterns, by which people preferred sources based on experts (physicians and scientists) over non-experts (celebrities and politicians) and group consensus (professional societies, polls) over individual opinions. These findings held most strongly for issues of personal medical concern, but were robust for less concerning health conditions, and for the highly politicized topic of COVID-19. Individuals who scored higher in intellectual humility and preferences for rational over experiential thinking were more likely to prefer the most expert sources. Expertise retains broad respect in the medical domain, at least when one’s own health is at stake.

Taking A Closer Look At The Bayesian Truth Serum: A Registered Report

Over the past decades, psychology and its cognate disciplines have undergone substantial reform, ranging from advances in statistical methodology to significant changes in academic norms. One aspect of experimental design that has received comparatively little attention is incentivisation, i.e. the way that participants are rewarded and incentivised monetarily for their participation. While incentive-compatible designs are in use in disciplines like economics, the majority of studies in psychology and experimental philosophy are constructed such that individuals’ incentives to maximise their payoffs in many cases counteract their incentives to state their true preferences honestly. This is in part because the subject matter is often self-report data about subjective topics. One mechanism that allows for the introduction of an incentive-compatible design in such circumstances is the Bayesian Truth Serum (Prelec, 2004), which rewards participants based on how surprisingly common their answer are. Recently, Schoenegger (2021) applied this mechanism in the context of Likert-scale self-reports, finding that the introduction of this mechanism significantly altered response behaviour. In this registered report, we further investigate this mechanism by (i) replicating the original result and (ii) teasing out whether the effect may be explainable by an increase in expected earnings or the addition of a prediction task. We take this project to help introduce incentivisation mechanisms into fields where they were not widely used before.

ForkDec: Accurate Detection for Selfish Mining Attacks

Incentive mechanism is the key to the success of the Bitcoin system as a permissionless blockchain. It encourages participants to contribute their computing resources to ensure the correctness and consistency of user transaction records. Selfish mining attacks, however, prove that Bitcoin’s incentive mechanism is not incentive-compatible, which is contrary to traditional views. Selfish mining attacks may cause the loss of mining power, especially those of honest participants, which brings great security challenges to the Bitcoin system. Although there are a series of studies against selfish mining behaviors, these works have certain limitations: either the existing protocol needs to be modified or the detection effect for attacks is not satisfactory. We propose the ForkDec, a high-accuracy system for selfish mining detection based on the fully connected neural network, for the purpose of effectively deterring selfish attackers. The neural network contains a total of 100 neurons (10 hidden layers and 10 neurons per layer), learned on a training set containing about 200,000 fork samples. The data set, used to train the model, is generated by a Bitcoin mining simulator that we preconstructed. We also applied ForkDec to the test set to evaluate the attack detection and achieved a detection accuracy of 99.03%. The evaluation experiment demonstrates that ForkDec has certain application value and excellent research prospects.

EXPRESS: Preference Reversals Between Digital and Physical Goods

The proliferation of digital goods has led to an increased interest in how the digitization of products and services affects consumer behavior. In this paper, the authors show that although consumers are willing to pay more for physical than digital goods, this difference attenuates—and even reverses—when consumers are asked to make a choice between the two product formats. This effect is explained by a contingent weighting principle: In willingness to pay, a quantitative task, consumers anchor on quantitative information (e.g., market beliefs). On the other hand, in choice, a qualitative task, consumers anchor on qualitative information (e.g., which good dominates on the most important attribute). These differences in contingent weighting result in physical goods being preferred in willingness to pay, but their digital equivalent being preferred relatively more in choice. The authors draw conclusions from ten pre-registered experiments and six supplemental studies using a variety of goods in hypothetical and incentive-compatible contexts, as well as within- and between-subjects designs. The paper concludes with a discussion of implications for the marketing of digital goods.

Dynamic climate clubs: On the effectiveness of incentives in global climate agreements

A proposal to combat free riding in international climate agreements is the establishment of a climate club—a coalition of countries in a structure to encourage high levels of participation. Empirical models of climate clubs in the early stages relied on the analysis of single-period coalition formation. The earlier results suggested that there were limits to the potential strength of clubs and that it would be difficult to have deep abatement strategies in the club framework. The current study extends the single-period approach to many periods and develops an approach analyzing “supportable policies” to analyze multiperiod clubs. The major element of the present study is the interaction between club effectiveness and rapid technological change. Neither alone will produce incentive-compatible policies that can attain the ambitious objectives of international climate policy. The trade sanctions without rapid technological decarbonization will be too costly to produce deep abatement; similarly, rapid technological decarbonization by itself will not induce deep abatement because of country free riding. However, the two together can achieve international climate objectives.

The randomized communication complexity of revenue maximization

We study the communication complexity of incentive compatible auction-protocols between a monopolist seller and a single buyer with a combinatorial valuation function over n items [Rubinstein and Zhao 2021]. Motivated by the fact that revenue-optimal auctions are randomized [Thanassoulis 2004; Manelli and Vincent 2010; Briest et al. 2010; Pavlov 2011; Hart and Reny 2015] (as well as by an open problem of Babaioff, Gonczarowski, and Nisan [Babaioff et al. 2017]), we focus on the randomized communication complexity of this problem (in contrast to most prior work on deterministic communication). We design simple, incentive compatible, and revenue-optimal auction-protocols whose expected communication complexity is much (in fact infinitely) more efficient than their deterministic counterparts. We also give nearly matching lower bounds on the expected communication complexity of approximately-revenue-optimal auctions. These results follow from a simple characterization of incentive compatible auction-protocols that allows us to prove lower bounds against randomized auction-protocols. In particular, our lower bounds give the first approximation-resistant, exponential separation between communication complexity of incentivizing vs implementing a Bayesian incentive compatible social choice rule, settling an open question of Fadel and Segal [Fadel and Segal 2009].

Modeling College Admission as a Signaling Game

This paper models the college admission process as a signaling game between the admissions office and a pool of heterogeneous applicants characterized by academic abilities and demonstrated interest. In the screening and selection process, applicants attempt to signal their private information through their performance on a standardized test (for academic abilities) and interview (for demonstrated interest). We show, under general conditions, that a separating equilibrium exists in which it is incentive-compatible for applicants to reveal their characteristics truthfully, and thus the admissions office does not fall victim to the problem of information asymmetry. Furthermore, we delineate how this equilibrium can be induced by setting appropriate “scoring” thresholds associated with standardized tests and interviews.

Rationality in games and institutions

Against the orthodox view of the Nash equilibrium as “the embodiment of the idea that economic agents are rational” (Aumann, 1985, p 43), some theorists have proposed ‘non-classical’ concepts of rationality in games, arguing that rational agents should be capable of improving upon inefficient equilibrium outcomes. This paper considers some implications of these proposals for economic theory, by focusing on institutional design. I argue that revisionist concepts of rationality conflict with the constraint that institutions should be designed to be incentive-compatible, that is, that they should implement social goals in equilibrium. To resolve this conflict, proponents of revisionist concepts face a choice between three options: (1) reject incentive compatibility as a general constraint, (2) deny that individuals interacting through the designed institutions are rational, or (3) accept that their concepts do not cover institutional design. I critically discuss these options and I argue that a more inclusive concept of rationality, e.g. the one provided by Robert Sugden’s version of team reasoning, holds the most promise for the non-classical project, yielding a novel argument for incentive compatibility as a general constraint.