<div>Space mission-related projects are demanding and risky undertakings because of their complexity and cost. Many missions have failed over the years due to anomalies in either the launch vehicle or the spacecraft. Projects of such magnitude with undetected flaws due to ineffective process controls run into unwarranted cost, schedule overruns and account for huge losses. Such failures continue to occur despite the studies on systems engineering process deficiencies and the best systems engineering practices in place. To understand the reasons behind such failures, this work analyses some of the major contributing factors behind majority of space mission technical failures. To achieve this objective, we analyzed the failure data of space missions that happened over the last decade. Based on that information, we analyzed the launch-related failure events from a design decision-making perspective by employing failure event chain-based framework. By analyzing the failure events with this framework, we identify some dominant cognitive biases that might have impacted the overall system performance leading to unintended catastrophes. </div><div><br></div><div>The ability of any design team to achieve optimal performance is limited by communication and knowledge deficiencies between highly dissimilar subsystems. These inefficiencies work to bias each subsystem engineer to prioritize the utility provided by the subsystem they are responsible for. In order to understand how engineering design decisions are influenced by the presence of cognitive biases, the second part of this study establishes a mathematical framework for utility-based selection based on Cumulative Prospect Theory. This framework captures the effect of cognitive biases on selection of alternatives by a rational decision-maker.</div><div><br></div><div>From the first study, overconfidence and anchoring biases are identified as the two dominant contributing factors that influenced the decisions behind majority of the failures. The theoretical models developed in the second study are employed to depict the influence of biased decision-making on utility-based selection of alternatives for an earth-orbiting satellite's power subsystem. Predictions from these models show a direct correlation between the decision-maker's biased preference structure and local change in utility curve depicting the (negative) influence of cognitive biases on decision-maker's choice(s).</div>

Behavioural economics builds on psychology rather than on sociology, and on cognitive science rather than the science of culture. The same is true for new behavioural scholarship in the legal discipline, whether this is referred to as 'behavioural law and economics' or 'law and the behavioural sciences'. The result of a one-sided definition of a more realist research agenda in legal scholarship is an impoverished understanding of the 'social'. In Thaler and Sunstein's famous concept of nudging, social conformity appears as a property of the individual, which can be instrumentalized by social nudges. More generally, the cognitive strand of behavioural economics lends itself to strategies of regulatory 'debiasing', which suggests that it is possible to get down to pure preferences that are free from any distortions. While this approach neglects the endogeneity, or social contingency, of individual preferences, the social strand of behavioural economics is explicitly concerned with the dynamics of social interaction, or the effects of social interdependence. However, both strands of behavioural economics are still higher on methodological individualism, naturalism or positivism and lower on institutionalism, culturalism or constructivism than a genuinely sociological approach. More specifically, their understanding of the 'social' does not sufficiently account for the social embeddedness of both rational and irrational economic action. What is more, behavioural economics also lacks the means to reflect on the link between science and politics, which includes the question of why different models of economic man are attractive at different points in time. The conceptual move from rational to behavioural economic man bears distinctive policy implications, which are in line with the transformation of welfare capitalism towards 'less state' and 'more market'. While the overall direction of this project gets blurred in Thaler and Sunstein's branding of 'libertarian paternalism', it is evident in the adaptation of consumer policies, which proceeds under the imperative of market-conformity. Accordingly, a strategy of nudging does not put into question the wider institutional context but offers a technical solution to what is defined as a problem of individual behavioural rigidities and cognitive biases in the market environment.

This thesis investigates to what extent do cognitive biases a ect human understanding of interpretable machine learning models, in particular of rules discovered from data. Twenty cognitive biases (illusions, e ects) are analysed in detail, including identi cation of possibly e ective debiasing techniques that can be adopted by designers of machine learning algorithms and software. This qualitative research is complemented by multiple experiments aimed to verify, whether, and to what extent, do selected cognitive biases in uence human understanding of actual rule learning results. Two experiments were performed, one focused on eliciting plausibility judgments for pairs of inductively learned rules, second experiment involved replication of the Linda experiment with crowdsourcing and two of its modi cations. Altogether nearly 3.000 human judgments were collected. We obtained empirical evidence for the insensitivity to sample size e ect. There is also limited evidence for the disjunction fallacy, misunderstanding of and , weak evidence e ect and availability heuristic. While there seems no universal approach for eliminating all the identi ed cognitive biases, it follows from our analysis that the e ect of many biases can be ameliorated by making rule-based models more concise. To this end, in the second part of thesis we propose a novel machine learning framework which postprocesses rules on the output of the seminal association rule classi cation algorithm CBA [Liu et al, 1998]. The framework uses original undiscretized numerical attributes to optimize the discovered association rules, re ning the boundaries of literals in the antecedent of the rules produced by CBA. Some rules as well as literals from the rules can consequently be removed, which makes the resulting classi er smaller. Benchmark of our approach on 22 UCI datasets shows average 53% decrease in the total size of the model as measured by the total number of conditions in all rules. Model accuracy remains on the same level as for CBA.

This study explores the attitudes of social workers in relation to lesbian, gay, bisexual and transgender (LGBT) adoptions. Race, gender, generation, position and prior LGBT training are factors that can positively or negatively impact social workers’ biases towards LGBT adoptions. Researchers contacted adoption agencies whom agreed to partake in the 26-question survey, including eight demographic questions and an 18 item scale. The current study used an adapted version of the Attitude Toward Gay Men and Lesbians as Adoptive Parent Scale (APS) (α = .95). There were 28 survey respondents, however two surveys were discontinued due to incomplete informed consents. A series of Mann-Whitney U tests were conducted to find if two independent, yet similar groups of people answered questions significantly different. Results show that men answered two questions significantly different than women participants who answered the same questions, and that administrative workers answered four questions differently than front-line service providers answered the same four questions. Limitations of this study include time; sample size; and an overrepresentation of women, heterosexuals and Caucasians. Further research should be done on this population, because they may directly impact the progression of lesbian, gay, bisexual and transgender adoptions.

Cognitive theories of depression have long posited automatic interpretation biases (AIB) as a central contributor to depressed mood. The current study was first to examine AIB in a clinically defined depressed sample. While assessing AIB using a semantic association paradigm, pupillary reactivity was simultaneously recorded to build insight into the AIB process. A total of 53 individuals (25 depressed and 28 healthy control) completed the Word Sentence Association Paradigm for Depression (WSAP-D) while pupillary reactivity was recorded. Results revealed the depressed group was significantly more likely to endorse negative AIB and less likely to endorse benign AIB compared to healthy controls. The depressed group demonstrated a modest effect size difference indicating they were faster to endorse negative AIB compared to the healthy controls, but did not differ in endorsing benign AIB or in rejecting either valence. Pupillary reactivity was found to differentiate behaviorally defined AIB type from a natural processing condition when counter to theorized, group relevant AIB. The depressed group demonstrated greater initial pupillary constriction during initial presentation of ambiguous information and comparatively less pupillary dilation during and after endorsing a benign AIB. Taken together, the results suggest that theorized negative AIB and lack of benign AIB are characteristic of depression, that greater cognitive effort is required to reject interpretations consistent with theorized biases consistent with reinterpretation processes, and that depressed individuals are less engaged with benign AIB compared to healthy controls, possibly associated with hedonic deficits. Theoretical implications and future directions are discussed.

Individuals utilize heuristics in order to simplify problems, which may lead to biases in decision-making. The research question of this study is: “How does the affect heuristic impact the investment process of private equity decision-makers reviewing proposals?” Through an exploratory multi-case analysis, insight is provided into complex private equity decisions by studying biases in the investment process. This is a study of private equity groups’ (PEG) decision-making process when they consider businesses for investment. Qualitative data was generated from semi-structured interviews with twenty private equity decision-makers. The deliberative heuristics applied in the teaser review are learned from process experience and guide the deliberation on whether to proceed. Simplifying heuristics are applied in the more informal review process. Organizational learning was exhibited as the PEGs have modified their investment structures based on previous experiences. The study indicates that experience and learning lead to the construction of an affect heuristic that subsequently impacts investments. It also confirms the need for strategic decision-makers to recognize their own biases and adjust their processes accordingly. A significant practical implication of this study is the insight provided into the views of the PEG decision-makers as they anticipate the need to supplement the management team is helpful to business owners and their advisors. The study highlights the opportunities for biases in PEG decision-making processes. Accessing decision-makers at larger PEGs and approaching more middle market firms would broaden the results.

Data shows that many inventors continue to expend resources on their inventions even after they have received expert advice suggesting that they cease effort. Using a sample of inventors seeking outside advice from a Canadian evaluative agency, this paper examines how overconfidence, optimism, and illusion of control explain this fact. While overconfidence did not have a significant effect on inventor's decisions, illusion of control and optimism did have an effect. An additional interesting finding is that the more time people have spent working on inventions, the more likely they are to discount this expert advice.

I present behavioural data contributing to existing research that (implicit) self-predictions are overly reliant on current intentions at the time of the decision (Koehler & Poon, 2006). Results are consistent with previous findings that self-predictions are often insensitive to translatability cues and overly influenced by desirability cues. We show that although participants typically benefit from a reminder, it is undervalued at the time of the decision (Experiment 1 & 3a) as participants are not willing to pay for a reminder service, unless it is offered free of charge (Experiment 2). Our findings also show that participants fail to incorporate temporal delay sufficiently in their opt-in decisions, even though temporal delay was found to be a significant predictor return behaviour (Experiments 1, 2 & 3b). Instead, decisions were found to be highly influenced by desirability factors (Experiments 1 & 2) which were not significant predictors of task completion. Finally, using a construal manipulation intended to induce participants to think about the decision options in either a concrete or abstract way influenced decisions (Experiment 3a), and subsequently influenced how much participants benefitted from the reminder in task completion (Experiment 3b).

Syftet med föreliggande studie var att undersöka hur bra vi är på att bedöma ålder på omaskerade och maskerade ansikten. Syftet var även att undersöka om det fanns systematiska fel som är förknippade med åldersbedömning av maskerade ansikten. Totalt fick 60 försöksdeltagare, samtliga ungdomar, skatta åldern på 60 fotografier av 30 maskerade och 30 omaskerade män.  Fotografierna var indelade i två åldersgrupper, yngre och äldre, och samtliga stimulipersoner förekom i både den maskerade och den omaskerade varianten. Resultaten visade att försöksdeltagarna var bättre på att skatta åldern på omaskerade ansikten än på maskerade. Inga skillnader i systematiska fel fans mellan maskerade och omaskerade ansikten. Bilder av unga ansikten skattades med högre precision än bilder av äldre ansikten. / The purpose of this study was to investigate how well we are at age estimations of masked and unmasked faces. The purpose was also to investigate if there were any biases that effected age estimations of masked faces. A total of 60 participants, all juveniles, estimated the age of 60 photographs of 30 masked and 30 unmasked men. The photographs were divided into two age groups, younger and older, and all of the men, who served as stimuli, were represented in both conditions. The results showed that the participants were better at estimating the age of unmasked than masked faces. There were no differences in biases between masked and unmasked faces. Photographs of young faces were estimated with greater precision than older faces.

The profitability and the sources of the returns on momentum strategy have always been a popular subject of study in the financial field. Nevertheless, there exist significant discrepancies between the conclusions of the papers due to the difference in time period and the emphasis on average results. Thus, the purpose of this paper is to investigate momentum strategy with information uncertainty in Taiwan stock market during the period 1990-2009 given the basis on the research method of Jegardeesh and Titman(1993). The result shows that momentum strategy cannot averagely obtain significantly positive returns in the long run in Taiwan stock market and moreover it presents an enormous short-term reversal. Besides, in terms of business cycle, there is still no significant return on momentum strategy either; there will be significantly negative return when implementing momentum strategy in the recession of business cycle. On the other hand, from the view of investor psychological biases, it should be seen greater psychological biases owing to greater information uncertainty. As a result, a stronger stock price continuation may be observed under high information uncertainty stocks. However, the effect of information uncertainty is only pronounced among loser portfolios. To summarize, compared with the profitability and the stability of contrarian strategy, the findings support that there is no significant momentum phenomena in Taiwan stock market at all.