Neural representations of social and non-social uncertainty in human decision making

The social landscape is filled with an intricate web of species-specific desired objects and course of actions. Humans are highly social animals and, as they navigate this landscape, they need to produce adapted decision-making behaviour. Traditionally social and non-social neural mechanisms affecting choice have been investigated using different approaches. Recently, in an effort to unite these findings, two main theories have been proposed to explain how the brain might encode social and non-social motivational decision-making: the extended common currency and the social valuation specific schema (Ruff & Fehr 2014). One way to test these theories is to directly compare neural activity related to social and non-social decision outcomes within the same experimental setting. Here we address this issue by focusing on the neural substrates of social and non-social forms of uncertainty. Using functional magnetic resonance imaging (fMRI) we directly compared the neural representations of reward and risk prediction and errors (RePE and RiPE) in social and non- social situations using gambling games. We used a trust betting game to vary uncertainty along a social dimension (trustworthiness), and a card game (Preuschoff et al. 2006) to vary uncertainty along a non-social dimension (pure risk). The trust game was designed to maintain the same structure of the card game. In a first study, we exposed a divide between subcortical and cortical regions when comparing the way these regions process social and non-social forms of uncertainty during outcome anticipation. Activity in subcortical regions reflected social and non-social RePE, while activity in cortical regions correlated with social RePE and non-social RiPE. The second study focused on outcome delivery and integrated the concept of RiPE in non-social settings with that of fairness and monetary utility maximisation in social settings. In particular these results corroborate recent models of anterior insula function (Singer et al. 2009; Seth 2013), and expose a possible neural mechanism that weights fairness and uncertainty but not monetary utility. The third study focused on functionally defined regions of the early visual cortex (V1) showing how activity in these areas, traditionally considered only visual, might reflect motivational prediction errors in addition to known perceptual prediction mechanisms (den Ouden et al 2012). On the whole, while our results do not support unilaterally one or the other theory modeling the underlying neural dynamics of social and non-social forms of decision making, they provide a working framework where both general mechanisms might coexist.

Uncertainty Management in Acquisitions: What Scenario Analysis Could Offer

This study answers to How scenario analysis could help acquiring companies to reduce uncertainty in the acquisition process? It is due to the mismatch between academic world’s caveat emptor and business world’s eagerness to pursue acquisitions that motivated this study. Acquisitions are as popular as ever, thus, managing the uncertainty surrounding these transactions is relevant. This study creates a generic theoretical model with a strategy-level scope. Thus, the study does not discuss nor does it seek answers to operational issues related in both fields. This study is explorative and constructivist in nature. It discusses briefly the concepts and relatedness of risk and uncertainty and establishes a hierarchy between these two: Risks being a “sub-section” of uncertainty, although not with clear boundaries. Acquisition theory follows the process view that understands acquisitions as a process with various levels – some strategic, some operational. Scenario analysis is presented as tool for management to enrich their strategic discussion and understand their future options. The empirical data collection is done through interviewing. The results are reflected on literature on strategic management, scenario literature, and on a consultancy’s report picturing firm’s strategies in accordance with their acquisition processes. The study has an abductive approach as it tries to combine multiple views and generates discussion between literature review, interviews, the report, and second round of literature. The model suggests three propositions: First, at the strategic decision making level, when the decision whether or not to pursue an acquisition growth strategy has been made, it provides firms new data and enriches the strategic discussion. Second, when the acquisition strategy has been created, it can be applied as a tool to measure possible acquisition targets against the backdrop of the first set of scenarios. Third, due to the scenario analysis’ requirement to include people with various backgrounds and from multiple levels of the corporate hierarchy, it could help managers to avoid biases stemming from hubris.

Framing the Gas Market Uncertainty in Russian Gas Export Policy: The Role of Underlying Ideas

Gas suppliers including Russia are facing the gas market uncertainty caused by the fast growing development of shale gas and liquefied natural gas (LNG). Given that Russia is one of the key energy suppliers in the world, Russian energy policy is intensively studied. However, the majority of the researches focus on the conventional gas sector and very few focus on the unconventional gas sector such as shale gas and LNG. In this light, this thesis aims at examining how the gas market uncertainty is framed in Russian gas export policy as well as discover how the interaction between underlying ideas and the policy frames informs policymaking. After analyzing Russian official documents, three policy frames were identified: shale gas—competition frame, LNG—cooperation frame and cooperation—competition frame. The shale gas—competition frame emphasizes the confrontation with the shale revolution in the USA. The LNG—cooperation frame rests on the idea of building cooperation with the Asia-Pacific region by the LNG trade. The cooperation—competition frame describes the oscillating Russia-EU relationship. Both the economic and ecological dimensions in the policy environment enable these three policy frames. However, the cooperation frame is constrained by the physical dimension since Russia has only one LNG facility in use. The institutional dimension underpins the idea of competition in the cooperation—competition frame. The reason is because of the divergent perspectives between Russia and the EU regarding regulations and market liberalizations. In sum, the result is different from the traditional geopolitical frame which depicts Russia as an energy superpower. Instead, this thesis suggests that Russia is shifting the priority from political interests to business interests in Russian gas export policy, particularly in the domain of shale gas and LNG.

Trajectory prediction uncertainty modelling for Air Traffic Management

The anticipated growth of air traffic worldwide requires enhanced Air Traffic Management (ATM) technologies and procedures to increase the system capacity, efficiency, and resilience, while reducing environmental impact and maintaining operational safety. To deal with these challenges, new automation and information exchange capabilities are being developed through different modernisation initiatives toward a new global operational concept called Trajectory Based Operations (TBO), in which aircraft trajectory information becomes the cornerstone of advanced ATM applications. This transformation will lead to higher levels of system complexity requiring enhanced Decision Support Tools (DST) to aid humans in the decision making processes. These will rely on accurate predicted aircraft trajectories, provided by advanced Trajectory Predictors (TP). The trajectory prediction process is subject to stochastic effects that introduce uncertainty into the predictions. Regardless of the assumptions that define the aircraft motion model underpinning the TP, deviations between predicted and actual trajectories are unavoidable. This thesis proposes an innovative method to characterise the uncertainty associated with a trajectory prediction based on the mathematical theory of Polynomial Chaos Expansions (PCE). Assuming univariate PCEs of the trajectory prediction inputs, the method describes how to generate multivariate PCEs of the prediction outputs that quantify their associated uncertainty. Arbitrary PCE (aPCE) was chosen because it allows a higher degree of flexibility to model input uncertainty. The obtained polynomial description can be used in subsequent prediction sensitivity analyses thanks to the relationship between polynomial coefficients and Sobol indices. The Sobol indices enable ranking the input parameters according to their influence on trajectory prediction uncertainty. The applicability of the aPCE-based uncertainty quantification detailed herein is analysed through a study case. This study case represents a typical aircraft trajectory prediction problem in ATM, in which uncertain parameters regarding aircraft performance, aircraft intent description, weather forecast, and initial conditions are considered simultaneously. Numerical results are compared to those obtained from a Monte Carlo simulation, demonstrating the advantages of the proposed method. The thesis includes two examples of DSTs (Demand and Capacity Balancing tool, and Arrival Manager) to illustrate the potential benefits of exploiting the proposed uncertainty quantification method.

Essays on Uncertainty, Imperfect Information, and Investment Dynamics

Understanding how imperfect information affects firms' investment decision helps answer important questions in economics, such as how we may better measure economic uncertainty; how firms' forecasts would affect their decision-making when their beliefs are not backed by economic fundamentals; and how important are the business cycle impacts of changes in firms' productivity uncertainty in an environment of incomplete information. This dissertation provides a synthetic answer to all these questions, both empirically and theoretically. The first chapter, provides empirical evidence to demonstrate that survey-based forecast dispersion identifies a distinctive type of second moment shocks different from the canonical volatility shocks to productivity, i.e. uncertainty shocks. Such forecast disagreement disturbances can affect the distribution of firm-level beliefs regardless of whether or not belief changes are backed by changes in economic fundamentals. At the aggregate level, innovations that increase the dispersion of firms' forecasts lead to persistent declines in aggregate investment and output, which are followed by a slow recovery. On the contrary, the larger dispersion of future firm-specific productivity innovations, the standard way to measure economic uncertainty, delivers the ``wait and see" effect, such that aggregate investment experiences a sharp decline, followed by a quick rebound, and then overshoots. At the firm level, data uncovers that more productive firms increase investments given rises in productivity dispersion for the future, whereas investments drop when firms disagree more about the well-being of their future business conditions. These findings challenge the view that the dispersion of the firms' heterogeneous beliefs captures the concept of economic uncertainty, defined by a model of uncertainty shocks. The second chapter presents a general equilibrium model of heterogeneous firms subject to the real productivity uncertainty shocks and informational disagreement shocks. As firms cannot perfectly disentangle aggregate from idiosyncratic productivity because of imperfect information, information quality thus drives the wedge of difference between the unobserved productivity fundamentals, and the firms' beliefs about how productive they are. Distribution of the firms' beliefs is no longer perfectly aligned with the distribution of firm-level productivity across firms. This model not only explains why, at the macro and micro level, disagreement shocks are different from uncertainty shocks, as documented in Chapter 1, but helps reconcile a key challenge faced by the standard framework to study economic uncertainty: a trade-off between sizable business cycle effects due to changes in uncertainty, and the right amount of pro-cyclicality of firm-level investment rate dispersion, as measured by its correlation with the output cycles.

Management interventions in dairy herds: exploring within herd uncertainty using an integrated Bayesian model

Knowledge of the efficacy of an intervention for disease control on an individual farm is essential to make good decisions on preventive healthcare, but the uncertainty in outcome associated with undertaking a specific control strategy has rarely been considered in veterinary medicine. The purpose of this research was to explore the uncertainty in change in disease incidence and financial benefit that could occur on different farms, when two effective farm management interventions are undertaken. Bovine mastitis was used as an example disease and the research was conducted using data from an intervention study as prior information within an integrated Bayesian simulation model. Predictions were made of the reduction in clinical mastitis within 30 days of calving on 52 farms, attributable to the application of two herd interventions previously reported as effective; rotation of dry cow pasture and differential dry cow therapy. Results indicated that there were important degrees of uncertainty in the predicted reduction in clinical mastitis for individual farms when either intervention was undertaken; the magnitude of the 95% credible intervals for reduced clinical mastitis incidence were substantial and of clinical relevance. The large uncertainty associated with the predicted reduction in clinical mastitis attributable to the interventions resulted in important variability in possible financial outcomes for each farm. The uncertainty in outcome associated with farm control measures illustrates the difficulty facing a veterinary clinician when making an on-farm decision and highlights the importance of iterative herd health procedures (continual evaluation, reassessment and adjusted interventions) to optimise health in an individual herd.

Risk management for mathematical optimization under uncertainty

We present a general multistage stochastic mixed 0-1 problem where the uncertainty appears everywhere in the objective function, constraints matrix and right-hand-side. The uncertainty is represented by a scenario tree that can be a symmetric or a nonsymmetric one. The stochastic model is converted in a mixed 0-1 Deterministic Equivalent Model in compact representation. Due to the difficulty of the problem, the solution offered by the stochastic model has been traditionally obtained by optimizing the objective function expected value (i.e., mean) over the scenarios, usually, along a time horizon. This approach (so named risk neutral) has the inconvenience of providing a solution that ignores the variance of the objective value of the scenarios and, so, the occurrence of scenarios with an objective value below the expected one. Alternatively, we present several approaches for risk averse management, namely, a scenario immunization strategy, the optimization of the well known Value-at-Risk (VaR) and several variants of the Conditional Value-at-Risk strategies, the optimization of the expected mean minus the weighted probability of having a "bad" scenario to occur for the given solution provided by the model, the optimization of the objective function expected value subject to stochastic dominance constraints (SDC) for a set of profiles given by the pairs of threshold objective values and either bounds on the probability of not reaching the thresholds or the expected shortfall over them, and the optimization of a mixture of the VaR and SDC strategies.

Intolerance of uncertainty modulates the insensitivity to reinforcer devaluation found in an avoidance task

The reinforcer devaluation paradigm has been regarded as a canonical paradigm to detect habit-like behavior in animal and human instrumental learning. Though less studied, avoidance situations set a scenario where habit-like behavior may be of great experimental and clinical interest. On the other hand, proactive intolerance of uncertainty has been shown as a factor facilitating responses in uncertain situations. Thus, avoidance situations in which uncertainty is favoured, may be taken as a relevant paradigm to examine the role of intolerance of uncertainty as a facilitatory factor for habit-like behavior to occur. In our experiment we used a free-operant discriminative avoidance procedure to implement a devaluation paradigm. Participants learned to avoid an aversive noise presented either to the right or to the left ear by pressing two different keys. After a devaluation phase where the volume of one of the noises was reduced, they went through a test phase identical to the avoidance phase except for the fact that the noise was never administered. Sensitivity to reinforcer devaluation was examined by comparing the response rate to the cue associated to the devalued reinforcer with that to the cue associated to the still aversive reinforcer. The results showed that intolerance of uncertainty was positively associated to insensitivity to reinforcer devaluation. Finally, we discuss the theoretical and clinical implications of the habit-like behavior obtained in our avoidance procedure.

Intolerance of uncertainty predisposes to avoidance habit acquisition

Many mental disorders are characterised by the presence of compulsions and incontrollable habits. Most studies on habit learning, both in animals and in humans, are based on positive reinforcement paradigms. However, the compulsions and habits involved in some mental disorders may be better understood as avoidance behaviours, which involve some peculiarities, such as anxiety states, that have been shown to promote habitual responses. Consequently, we studied habit acquisition by using a free-operant discriminated avoidance procedure. Furthermore, we checked whether intolerance of uncertainty could predispose to avoidance habit acquisition. Participants learned to avoid an aversive noise presented either to the right or to the left ear by pressing two different keys. After a devaluation phase where the volume of the noise presented to one of the ears was reduced, participants went through a test phase identical to the avoidance learning phase except for the fact that the noise was never administered. Habit acquisition was inferred by comparing the rate of responses to the stimulus signalling the devalued reinforcer and to the stimulus signalling the non-devalued reinforcer. The results showed that intolerance of uncertainty was related to the absence of differences between the referred conditions, which entail avoidance habit acquisition.

Communication of scientific uncertainty: International case studies on the development of folate and vitamin D Dietary Reference Values

Objective Transparent evidence-based decision making has been promoted worldwide to engender trust in science and policy making. Yet, little attention has been given to transparency implementation. The degree of transparency (focused on how uncertain evidence was handled) during the development of folate and vitamin D Dietary Reference Values was explored in three a priori defined areas: (i) value request; (ii) evidence evaluation; and (iii) final values. Design Qualitative case studies (semi-structured interviews and desk research). A common protocol was used for data collection, interview thematic analysis and reporting. Results were coordinated via cross-case synthesis. Setting Australia and New Zealand, Netherlands, Nordic countries, Poland, Spain and UK. Subjects Twenty-one interviews were conducted in six case studies. Results Transparency of process was not universally observed across countries or areas of the recommendation setting process. Transparency practices were most commonly seen surrounding the request to develop reference values (e.g. access to risk manager/assessor problem formulation discussions) and evidence evaluation (e.g. disclosure of risk assessor data sourcing/evaluation protocols). Fewer transparency practices were observed to assist with handling uncertainty in the evidence base during the development of quantitative reference values. Conclusions Implementation of transparency policies may be limited by a lack of dedicated resources and best practice procedures, particularly to assist with the latter stages of reference value development. Challenges remain regarding the best practice for transparently communicating the influence of uncertain evidence on the final reference values. Resolving this issue may assist the evolution of nutrition risk assessment and better inform the recommendation setting process.

Making conservation decisions under uncertainty for the persistence of multiple species

Population models for multiple species provide one of the few means of assessing the impact of alternative management options on the persistence of biodiversity, but
they are inevitably uncertain. Is it possible to use population models in multiple-speciesconservation planning given the associated uncertainties? We use information-gap decision theory to explore the impact of parameter uncertainty on the conservation decision when planning for the persistence of multiple species. An information-gap approach seeks robust outcomes that are most immune from error. We assess the impact of uncertainty in key model parameters for three species, whose extinction risks under four alternative management scenarios are estimated using a metapopulation model. Three methods are described for making conservation decisions across the species, taking into account uncertainty. We find that decisions based on single species are relatively robust to uncertainty in parameters, although the estimates of extinction risk increase rapidly with uncertainty. When identifying the best conservation decision for the persistence of all species, the methods that rely on the rankings of the management options by each species result in decisions that are similarly robust to uncertainty. Methods that depend on absolute values of extinction risk are sensitive to uncertainty, as small changes in extinction risk can alter the ranking of the alternative scenarios. We discover that it is possible to make robust conservation decisions even when the uncertainties of the multiple-species problem appear overwhelming. However, the decision most robust to uncertainty is likely to differ from the best decision when uncertainty is ignored, illustrating the importance of incorporating uncertainty into the decision-making process.

Uncertainty and reluctance in teaching taboo language: a case study of an experienced teacher of English as an additional language

Despite its ubiquitous employment by users of English to achieve authentic communicative goals, taboo language has received little attention in the education literature. Even less focus has been placed on such language in English language teaching - specifically, in teaching English as an Additional Language (EAL). Given the multiplicity of communicative struggles experienced by EAL learners surrounding the use of taboo language in authentic communication, meaningful consideration of this aspect can be seen as crucial in EAL instruction. Classroom learning could prepare learners for navigation and negotiation of taboo language use they will inevitably encounter in social interactions in target language communities of practice. However, EAL teachers' uncertainty or reluctance to introduce taboo language in classroom instruction is a key impediment in developing learners' sociocultural knowledge regarding such language use. We foreground one case of such uncertainty and reluctance surrounding the introduction of taboo language in EAL instruction derived as interview data from an experienced EAL teacher.

Aggregate uncertainty in the citizen candidate model yields extremist parties

We extend the citizen candidate model of electoral competition with sincere voting to allow for k ≥ 2 states of aggregate uncertainty. We discuss and characterize the equilibrium set in this framework. We provide conditions for the existence of two-party equilibria when k = 2 and show that the policies of the two parties in any such equilibrium are not only divergent but that the parties are extremist: when the political mood is left-wing, the left-wing party wins decisively with a platform that is to the left of the left-wing median voter, while when the political mood is right-wing, the right-wing party wins decisively with a platform that is to the right of the right-wing median voter. We then provide conditions under which such equilibria remain robust for an arbitrary value of k.

Better the devil you know than a world you don't? Intolerance of uncertainty and worldview explanations for belief in conspiracy theories

Conspiracy Theory (CT) endorsers believe in an omnipresent, malevolent, and highly coordinated group that wields secret influence for personal gain, and credit this group with the responsibility for many noteworthy events. Two explanations for the emergence of CTs are that they result from social marginalisation and a lack of agency, or that they are due to a need-to-explain-the-unexplained. Furthermore, representativeness heuristics may form reasoning biases that make such beliefs more likely. Two related studies (N = 107; N = 120) examined the relationships between these social marginalisation, intolerance of uncertainty, heuristics and CT belief using a correlational design. Overall, intolerance of uncertainty did not link strongly to CT belief, but worldview variables did - particularly a sense of the world as (socially) threatening, non-random, and with no fixed morality. The use of both representative heuristics that were examined was heightened in those participants more likely to endorse CTs. These factors seem to contribute to the likelihood of whether the individual will endorse CTs generally, relating similarly to common CTs, CTs generally historically accepted as "true", and to the endorsement of fictional CTs that the individual would find novel. Implications are discussed.