Counterfactual Information Research Articles

Counterfactual curiosity in real decisions: The roles of outcome valence and aging.

Non-instrumental counterfactual curiosity (i.e., the search for information about forgone options that is not useful for improving future outcomes) has especially been observed after outcomes perceived as negative and, consequently, attributed to forms of regret management. In three online experiments (N = 620), we extended the study of counterfactual curiosity about economically incentivized decisions in younger and older adults. Participants played independent rounds of a card-drawing game by choosing one of two decks to turn over the top, covered card, which could increase, decrease, or have no effect on an initial endowment. Following that, they could examine the top card of the other deck to see if and how the outcome could have differed. Experiment 1 featured identical decks, making the choice between them random. In Experiment 2, participants made a deliberate choice between a riskier and a safer deck, each varying in the extremity of potential wins and losses. In Experiment 3, the decks were identical to those in Experiment 2, but access to counterfactual information was contingent upon participants forfeiting part of their endowment. Results showed a relevant portion of both younger and older adults displayed curiosity for non-instrumental counterfactual information, especially when it was free and likely to reveal that the forgone option would have been better than the chosen one. Older adults exhibited a higher level of curiosity than younger counterparts only when choices were deliberate and counterfactual information was free. These findings are discussed in relation to current perspectives on the regret-management function of counterfactual curiosity.

For the sake of curiosity: Humans but not capuchins (Sapajus apella) collect counterfactual information on a computerized gambling task

Counterfactuals are alternative outcomes to past events. Curiosity for the counterfactual acts as an important driver of learning under uncertainty and helps to improve on past behaviors by informing future choices. Humans have demonstrated the desire to collect counterfactual information when it is perceived as useful, during times of uncertainty, and even when it comes at a cost. The comparative literature on counterfactual use and curiosity is small but suggests that rhesus macaques may possess similar tendencies to humans. The goal of the current study was to add a new species, capuchin monkeys (Sapajus apella), to the comparative counterfactual literature and to test capuchins and humans on nearly identical tasks. This study involved a three-choice gambling task that consisted of one hidden and two visible reward values. Visible reward values were always equivalent but had differently colored borders to indicate whether participants would view the counterfactual information associated with the gamble or not on trials when they chose not to gamble. Only humans showed evidence of counterfactual curiosity and collected the information at levels different than chance. Humans also collected counterfactual information significantly more than capuchins, indicating a species difference. However, it is not clear whether this difference is simply due to the capuchins’ lack of curiosity surrounding this particular task or whether there is a broader species difference for seeking counterfactuals resulting from different evolutionary histories of these species.

Distinct roles of the orbitofrontal cortex, ventral striatum, and dopamine neurons in counterfactual thinking of decision outcomes.

Individuals often assess past decisions by comparing what was gained with what would have been gained had they acted differently. Thoughts of past alternatives that counter what actually happened are called "counterfactuals." Recent theories emphasize the role of the prefrontal cortex in processing counterfactual outcomes in decision-making, although how subcortical regions contribute to this process remains to be elucidated. Here we report a clear distinction among the roles of the orbitofrontal cortex, ventral striatum and midbrain dopamine neurons in processing counterfactual outcomes in monkeys. Our findings suggest that actually gained and counterfactual outcome signals are both processed in the cortico-subcortical network constituted by these regions but in distinct manners and integrated only in the orbitofrontal cortex in a way to compare these outcomes. This study extends the prefrontal theory of counterfactual thinking and provides key insights regarding how the prefrontal cortex cooperates with subcortical regions to make decisions using counterfactual information.

Does emergency policy mend the fold after the sheep have been stolen?- an empirical study on the Baiyin Cross-country race and its subsequent circuit breaker mechanism

This study examines the biggest disaster in the history of international trail running—the Huangshi Cross-Country Race in Baiyin city, China—as an example to quantitatively evaluate this large-scale sporting event's impact on the local economy. After calculating the city stock market returns based on the improved worst-case Value-at-Risk (WCVaR) designed for this study, this study proposes a hybrid forecasting method combining time series modelling and neural network autoregression (NNAR) models to quantify the net effect of the race disaster, through counterfactual information. The study discoveres that although the event's pre-publicity period positively stimulated Baiyin city's economy, it still could not offset the negative impact of unexpected events during the race. Then, the study further explores the net economic effect of the circuit breaker mechanism as a strategic tool in an attempt to quell the above-mentioned negative effects after the cross-country race, through applying a difference-in-differences method to regress and analyse the stock market yield panel data of Baiyin and its control cities before and after the policy's implementation. Subsequently, it was revealed that the circuit breaker mechanism could not effectively curb the spread of the disaster's negative influence, in other word, the circuit breaker exists only to ‘mend the fold’ after the ‘sheep’ are endangered and it is already too late.

The impact of digital information treatment on the evaluation of service performance of agricultural extension agents

A randomized survey experiment was used to investigate the influence of digital information treatment on the subjective attitudes of agricultural extension agents. The objective was to explore the influence and mechanism of the digital economy on agricultural extension performance. This paper sets up the digital economy as a counterfactual information treatment. The sample was split into two groups using group randomization according to the location and type of unit where the agricultural extension agents were stationed. When responding to questions about the issues encountered, the randomly chosen treatment participants were informed of the numerous changes and implications the digital economy would bring to agricultural extension. In contrast, the control group answered the same questions without receiving the treatment information. The empirical results indicate that digital information treatment significantly affected agricultural extension agents’ preferred choice of extension service supply. Also, the recognition of the impact of actions to innovate the service mode and enhance the service capability of agricultural extension agents was much enhanced by the use of digital information treatment. The type of units dispatched and the scale of production of service recipients have significant moderating effects. Digital information treatment has a greater influence on the attitude of specialists from universities and research institutes and those whose service recipients are small farmers. The paper highlights the important role of government in the development of the digital economy by actively providing digital public goods for agricultural extension services.

Social Reference Points and Risk Taking

Social reference points have been identified to be important determinants of individuals’ welfare. We investigate the consequences of social reference points for risk taking in a laboratory experiment. In the main treatments, risk-taking subjects observe the predetermined earnings of peer subjects when making a risky choice. We exogenously manipulate peers’ earnings and find a significant treatment effect: decision makers make less risk-averse choices in the case of larger peers’ earnings. The treatment effect is consistent with an application of prospect theory to social reference points and cannot be explained by reference points based on counterfactual information, anchoring, and experimenter demand effects. In additional analyses, we show that diminishing sensitivity seems to play an important role in subjects’ risky choices. We explore also whether inequity aversion and expectations-based reference points can account for our findings and conclude that they do not provide plausible alternative explanations for them. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: This research was financially supported by the Bonn Graduate School of Economics and the Center for Economics and Neuroscience in Bonn. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4698 .

Intracranial subsecond dopamine measurements during a "sure bet or gamble" decision-making task in patients with alcohol use disorder suggest diminished dopaminergic signals about relief.

To the authors' knowledge, no data have been reported on dopamine fluctuations on subsecond timescales in humans with alcohol use disorder (AUD). In this study, dopamine release was monitored in 2 patients with and 2 without a history of AUD during a "sure bet or gamble" (SBORG) decision-making task to begin to characterize how subsecond dopamine responses to counterfactual information, related to psychological notions of regret and relief, in AUD may be altered. Measurements of extracellular dopamine levels were made once every 100 msec using human voltammetric methods. Measurements were made in the caudate during deep brain stimulation electrode implantation surgeries (for treatment of movement disorders) in patients who did (AUD, n = 2) or did not (non-AUD, n = 2) have a history of AUD. Participants performed an SBORG decision-making task in which they made choices between sure bets and 50%-chance monetary gamble outcomes. Fast changes were found in dopamine levels that appear to be modulated by "what could have been" and by patients' AUD status. Positive counterfactual prediction errors (related to relief) differentiated patients with versus without a history of AUD. Dopaminergic encoding of counterfactual information appears to differ between patients with and without AUD. The current study has a major limitation of a limited sample size, but these data provide a rare insight into dopaminergic physiology during real-time decision-making in humans with an addiction disorder. The authors hope future work will expand the sample size and determine the generalizability of the current results.

“It Could Be Better” Can Make It Worse: When and Why People Mistakenly Communicate Upward Counterfactual Information

Imagine you are a real estate agent and are showing a prospective buyer a house with a lake view, but it is foggy, and the view is less than ideal. Are you inclined to tell the prospective buyer, “Unfortunately, it is foggy outside. If it were not foggy, the view would be even better!”? Eight studies, spanning diverse domains, reveal a novel discrepancy: most presenters (e.g., the seller) choose to communicate such upward counterfactual information (UCI) to experiencers (e.g., the prospective buyer), believing it will enhance experiencers’ impressions (e.g., of the house)—yet UCI actually worsens their impressions. This discrepancy arises because presenters insufficiently account for the fact that they possess more knowledge about the presented target than experiencers do; they fail to realize that noting an imperfection reveals it. Accordingly, when experiencers are knowledgeable about the target, either because the imperfection is obvious or because they can easily envision the upward counterfactual, the discrepancy attenuates. Finally, the presenter–experiencer discrepancy occurs only when the counterfactual information is upward, such that presenters do not overcommunicate downward counterfactual information, which rules out a desire to share any information as an alternative mechanism for presenters’ communication decisions. Together, this research highlights the prevalence and costs of sharing UCI.

Counterfactual curiosity: motivated thinking about what might have been.

Counterfactual information, information about what might have been, forms the content of counterfactual thoughts and emotions like regret and relief. Recent research suggests that human adults and children, as well as rhesus monkeys, demonstrate 'counterfactual curiosity': they are motivated to seek out counterfactual information after making decisions. Based on contemporary theories of curiosity and information seeking and a broad range of empirical literature, we suggest multiple heterogeneous psychological processes that contribute to people's motivation for counterfactual information. This includes processes that are identified in the curiosity literature more generally-the potential use of counterfactual information for adaptive decision making (its long-term instrumental value) and the drive to reduce uncertainty. Additionally, we suggest that counterfactual information may be particularly alluring because of its role in causal reasoning; its relationship with prediction and decision making; and its potential to fulfil emotion regulation and self-serving goals. Some future directions have been suggested, including investigating the role of individual differences in counterfactual curiosity on learning and wellbeing. This article is part of the theme issue 'Thinking about possibilities: mechanisms, ontogeny, functions and phylogeny'.

How do managers evaluate individual contributions to team production? A theory and empirical test

AbstractResearch SummaryOrganizations rely on subjective evaluations to reward employees for team‐based performance. However, it is unclear how supervisors determine individuals' contributions to collective output. We theorize that supervisors rely on the covariance between employees' presence and their teams' productivity. If teams are more productive when an employee is present, the supervisor may infer a greater contribution from the employee. Using data from a manufacturing firm, we find that covariation between an employee's presence and her team's output has a positive effect on her evaluation. This relationship is stronger when supervisors have more opportunities to observe an employee across various teams and when the employee has more authority to direct team production, supporting counterfactual information as an important component of evaluations for individuals engaged in team production.Managerial SummaryIt is notoriously difficult to evaluate the individual performance of employees when the only available metric is team‐based output. We suggest that supervisors help solve this problem by observing how team output correlates with changes in team membership. We construct a measure of the covariance between an employee's presence in a team and the team's productivity, and find a positive relationship between this measure and the employee's annual subjective performance evaluation. Our results indicate that subjective evaluations reflect individual contributions to team production fairly well for employees who (a) have sufficient authority to direct team production and (b) are frequently rotated beyond a single team. We discuss what kinds of organizations might benefit from this measure as an input to their performance evaluation processes.

Optimizing Adaptive Notifications in Mobile Health Interventions Systems: Reinforcement Learning from a Data-driven Behavioral Simulator

Mobile health (mHealth) intervention systems can employ adaptive strategies to interact with users. Instead of designing such complex strategies manually, reinforcement learning (RL) can be used to adaptively optimize intervention strategies concerning the user’s context. In this paper, we focus on the issue of overwhelming interactions when learning a good adaptive strategy for the user in RL-based mHealth intervention agents. We present a data-driven approach integrating psychological insights and knowledge of historical data. It allows RL agents to optimize the strategy of delivering context-aware notifications from empirical data when counterfactual information (user responses when receiving notifications) is missing. Our approach also considers a constraint on the frequency of notifications, which reduces the interaction burden for users. We evaluated our approach in several simulation scenarios using real large-scale running data. The results indicate that our RL agent can deliver notifications in a manner that realizes a higher behavioral impact than context-blind strategies.

‘Truth’, technology and transmedial theatre in Europe

Recent scholarship has expanded upon the concept of populism as performance to include a focus on how it employs digital technologies. However, what happens when theatrical performances appropriate far-right populist discourse to potentially parody how it frames its nationalist rhetoric as an appeal to ‘the people’? How do the relationships between performers and spectator-participants in such artistic works differ from those forged through the public manifestations of populist politics? How have artists who engage with populism employed technology to increase the reach and interactivity of their performances, and how does this engagement seek to undermine, and/or generate a troubling ‘belief’ in, the supposed ‘reality’ of such projects? This article critically reassesses the transmedial theatre of the late German artist Christoph Schlingensief and the Tallinn-based theatre company, Theatre NO99, in relation to current understandings of populism within an increasingly digitized, post-truth society. Schlingensief and NO99 might be seen to employ strategies of ‘subversive affirmation’ and ‘over-identification’ in their aims to resist the rise of far-right populism. Yet, we argue that these approaches can be dangerous: artists can reinforce far-right populist agendas if audiences fail to self-reflexively decode and reject subtle yet effective forms of mass manipulation – which is more likely when the components of such projects are dispersed across multiple media platforms through which counterfactual information also increasingly circulates.

Bandit Linear Optimization for Sequential Decision Making and Extensive-Form Games

Tree-form sequential decision making (TFSDM) extends classical one-shot decision making by modeling tree-form interactions between an agent and a potentially adversarial environment. It captures the online decision-making problems that each player faces in an extensive-form game, as well as Markov decision processes and partially-observable Markov decision processes where the agent conditions on observed history. Over the past decade, there has been considerable effort into designing online optimization methods for TFSDM. Virtually all of that work has been in the full-feedback setting, where the agent has access to counterfactuals, that is, information on what would have happened had the agent chosen a different action at any decision node. Little is known about the bandit setting, where that assumption is reversed (no counterfactual information is available), despite this latter setting being well understood for almost 20 years in one-shot decision making. In this paper, we give the first algorithm for the bandit linear optimization problem for TFSDM that offers both (i) linear-time iterations (in the size of the decision tree) and (ii) O(sqrt(T)) cumulative regret in expectation compared to any fixed strategy, at all times T. This is made possible by new results that we derive, which may have independent uses as well: 1) geometry of the dilated entropy regularizer, 2) autocorrelation matrix of the natural sampling scheme for sequence-form strategies, 3) construction of an unbiased estimator for linear losses for sequence-form strategies, and 4) a refined regret analysis for mirror descent when using the dilated entropy regularizer.

Information on Averted Infections Increased Perceived Efficacy of Regulations and Intentions to Follow Them

The coronavirus 2019 (COVID-19) pandemic presented policymakers with the need to change people’s behavior in a fundamental way and for an extended period of time. Changing habits is difficult and requires sustained effort, and sustaining effort is especially difficult when it does not seem to yield conspicuous results. The COVID-19 pandemic presented exactly this difficulty, as numbers of infected people continued to rise despite the public’s efforts. In a representative sample from Israel (N = 600), collected online during the first outbreak of the pandemic, we found that compared to control conditions in which information on only actual infection cases was presented, counterfactual information on the number of averted cases enhances the perceived effectiveness of following the guidelines, which, in turn, enhances perceived importance and intention of doing so (e.g., intention to restrict mobility), but only among those who understood the information. The findings align with self-regulation theories and have practical implications for policymakers.

The Lure of Counterfactual Curiosity: People Incur a Cost to Experience Regret

After you make a decision, it is sometimes possible to seek information about how things would be if you had acted otherwise. We investigated the lure of this counterfactual information, namely, counterfactual curiosity. In a set of five experiments (total N = 150 adults), we used an adapted Balloon Analogue Risk Task with varying costs of information. At a cost, people were willing to seek information about how much they could have won, even though it had little utility and a negative emotional impact (i.e., it led to regret). We explored the downstream effects of seeking information on emotion, behavior adjustment, and ongoing performance, showing that it has little or even negative performance benefit. We also replicated the findings with a large-sample (N = 361 adults) preregistered experiment that excluded possible alternative explanations. This suggests that information about counterfactual alternatives has a strong motivational lure—people simply cannot help seeking it.

The Effect of Counterfactual Information on Outcome Value Coding in Medial Prefrontal and Cingulate Cortex: From an Absolute to a Relative Neural Code

Adaptive coding of stimuli is well documented in perception, where it supports efficient encoding over a broad range of possible percepts. Recently, a similar neural mechanism has been reported also in value-based decision, where it allows optimal encoding of vast ranges of values in PFC: neuronal response to value depends on the choice context (relative coding), rather than being invariant across contexts (absolute coding). Additionally, value learning is sensitive to the amount of feedback information: providing complete feedback (both obtained and forgone outcomes) instead of partial feedback (only obtained outcome) improves learning. However, it is unclear whether relative coding occurs in all PFC regions and how it is affected by feedback information. We systematically investigated univariate and multivariate feedback encoding in various mPFC regions and compared three modes of neural coding: absolute, partially-adaptive and fully-adaptive.Twenty-eight human participants (both sexes) performed a learning task while undergoing fMRI scanning. On each trial, they chose between two symbols associated with a certain outcome. Then, the decision outcome was revealed. Notably, in one-half of the trials participants received partial feedback, whereas in the other half they got complete feedback. We used univariate and multivariate analysis to explore value encoding in different feedback conditions.We found that both obtained and forgone outcomes were encoded in mPFC, but with opposite sign in its ventral and dorsal subdivisions. Moreover, we showed that increasing feedback information induced a switch from absolute to relative coding. Our results suggest that complete feedback information enhances context-dependent outcome encoding.SIGNIFICANCE STATEMENT This study offers a systematic investigation of the effect of the amount of feedback information (partial vs complete) on univariate and multivariate outcome value encoding, within multiple regions in mPFC and cingulate cortex that are critical for value-based decisions and behavioral adaptation. Moreover, we provide the first comparison of three possible models of neural coding (i.e., absolute, partially-adaptive, and fully-adaptive coding) of value signal in these regions, by using commensurable measures of prediction accuracy. Taken together, our results help build a more comprehensive picture of how the human brain encodes and processes outcome value. In particular, our results suggest that simultaneous presentation of obtained and foregone outcomes promotes relative value representation.

Mathematics and Explanatory Generality: Nothing but Cognitive Salience

We demonstrate how real progress can be made in the debate surrounding the enhanced indispensability argument. Drawing on a counterfactual theory of explanation, well-motivated independently of the debate, we provide a novel analysis of ‘explanatory generality’ and how mathematics is involved in its procurement. On our analysis, mathematics’ sole explanatory contribution to the procurement of explanatory generality is to make counterfactual information about physical dependencies easier to grasp and reason with for creatures like us. This gives precise content to key intuitions traded in the debate, regarding mathematics’ procurement of explanatory generality, and adjudicates unambiguously in favour of the nominalist, at least as far as explanatory generality is concerned.

Debiasing of gambling beliefs and behaviors using a digital gambling accelerator.

Problem gamblers tend to adhere to rigid rules about the chances of winning and are resistant to counterfactual information. To promote a more accurate understanding of the odds of scratch-off ticket gambling, we created a brief debiasing intervention consisting of a digital gambling accelerator program that offers demonstrations of the long-term outcomes of gambling. Using a sample of nontreatment seeking scratch-off lottery gamblers recruited from the community (42 subclinical and 45 probable pathological gamblers), we compared the accelerator intervention to brief motivational interviewing (MI) and a control condition. Participants rated their chances of winning, urge to gamble, and readiness to change before and after the interventions. Self-reported dollar amount spent on scratch-off tickets and number of days gambled were assessed at baseline and again at 2- and 4-week follow-ups. Following the active interventions, gamblers in both conditions reported greater readiness to change than controls, and those in the accelerator condition also gave lower ratings of their chances of winning and urge to gamble. Marginal models showed participants in the accelerator condition gambled fewer days at the 2-week follow-up and spent less money at both the 2- and 4-week follow-ups compared to controls; no other between-subjects differences achieved statistical significance. Digital gambling accelerators can impact several clinically relevant domains of gambling and may be useful as stand-alone or adjunct interventions to treat gambling problems. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

For Better of For Worse: The Effect of Counterfactual Thinking and Relative Performance Information on Escalation Tendencies

For Better of For Worse: The Effect of Counterfactual Thinking and Relative Performance Information on Escalation Tendencies

Constructing effective personalized policies using counterfactual inference from biased data sets with many features

This paper proposes a novel approach for constructing effective personalized policies when the observed data lacks counter-factual information, is biased and possesses many features. The approach is applicable in a wide variety of settings from healthcare to advertising to education to finance. These settings have in common that the decision maker can observe, for each previous instance, an array of features of the instance, the action taken in that instance, and the reward realized—but not the rewards of actions that were not taken: the counterfactual information. Learning in such settings is made even more difficult because the observed data is typically biased by the existing policy (that generated the data) and because the array of features that might affect the reward in a particular instance—and hence should be taken into account in deciding on an action in each particular instance—is often vast. The approach presented here estimates propensity scores for the observed data, infers counterfactuals, identifies a (relatively small) number of features that are (most) relevant for each possible action and instance, and prescribes a policy to be followed. Comparison of the proposed algorithm against state-of-art algorithms on actual datasets demonstrates that the proposed algorithm achieves a significant improvement in performance.