O objetivo do artigo apresentado é analisar dilemas de efetividade na atividade de Inteligência Governamental. Explorando a literatura sobre falhas de inteligência e surpresa estratégica, avançamos em um campo pouco explorado pelos Estudos de Inteligência no Brasil: os aspectos cognitivos dos analistas de inteligência e as relações entre a comunidade política e a comunidade de inteligência. Primeiramente discorremos sobre os desafios de se avaliar a Inteligência Governamental como política pública, em especial no que se refere à dimensão da efetividade. Na segunda sessão abordamos os principais vieses cognitivos e heurísticas possíveis de ocorrer durante a análise de inteligência. A terceira sessão trata das tensões relacionais características entre a esfera política e a comunidade de inteligência e como essa relação afeta no resultado final da atividade de inteligência. Nas considerações finais apontamos para os limites e possibilidades das reformas organizacionais e procedimentais no que se refere à efetividade dos sistemas de inteligência. / The objective of this paper is to analyze the effectiveness‟ dilemmas of government intelligence activities. Exploring the literature on intelligence failures and strategic surprise, we move towards a little explored field on Brazilian Intelligence Studies: the cognitive aspects of intelligence analysts and the relations between the political community and the intelligence community. First we balance the challenges of evaluating government intelligence as public policy, particularly regarding the effectiveness dimension. In the second session, we discuss the main cognitive biases and heuristics that can occur during intelligence analysis. The third section discusses the typical relational tensions between the political sphere and the intelligence community and how that relationship affects the final result of intelligence activity. In the concluding remarks, we point to the limits and possibilities of organizational and procedural reforms on the effectiveness of intelligence systems.

This Diplomas thesis is focused on critical thinking. The main goal of this thesis is to define methods and tools leading to improvement of critical thinking in decision making and problem solving. The thesis is divided into five parts. First part is about characteristic of current world and importance of critical thinking in it. Second part defines fundamental errors in judgment and provides methods that could prevent these errors to occur. Third part is about fallacious arguments and philosophical concepts which define to which problems use of critical thinking is appropriate. These concepts could also help to simplify our decision making. Fourth part describes methods to enhance our cognitive abilities and rational thinking. Fifth part summarizes methods and tools leading to improvement of critical thinking.

Aging represents the most significant prerequisite to be influenced by disinformation or fraudulent media messages on the internet. The elderly are a group that consumes these messages and also spreads them most often. With the gradual aging of the population and enlargement of the elderly group, the society-wide problem further escalates. The topic of the diploma thesis is focused on the issues of fake news and the spread of disinformation online within the elderly group aged 65 and more years. The thesis aims to describe in detail the aspects on which the elderly evaluate the credibility of news and which signs of fake news they are able to identify. The theoretical section defines the fundamental terms relevant to fake news and describes the state of media literacy of the Czech elderly in the context of current research. In the practical section, a qualitative study is conducted in the form of semi structured interviews with the elderly to answer the research questions.

Cognitive biases have long been studied for their effects on an individual's decision-making. This study is the first of its kind to link these preferential thinking patterns to high school biology students' acceptance of evolution. At five urban high schools, 164 high school biology students were surveyed using a new instrument called the Cognitive Bias Assessment For Science Students – Evolution. The CBASS-E assesses both the level of non-acceptance of evolution, as well as how intensely participants demonstrate four specific cognitive biases. The four biases measured on the CBASS-E are anchoring, bandwagon effect, confirmation bias, and wishful thinking. This study showed that confirmation bias closely relates to a student's view of evolution. As part of this research, students were shown a video designed to teach high school students about cognitive bias and its effect on science learning. Results indicated that both cognitive bias and views on evolution are persistent, as student responses did not significantly change after watching the video. Included in this research are implications for teachers and administrators, as well as suggestions for further areas of study.

[pt] O estudo da tomada de decisões tem ganhado cada vez mais importância, desde as concepções clássicas do homem econômico até os mais recentes conceitos da racionalidade limitada e dos vieses cognitivos. Ao longo do tempo, a crescente complexidade das decisões impulsionou o desenvolvimento de tecnologias como os Sistemas de Apoio à Decisão e Modelos Preditivos, destacando-se mais recentemente a incorporação de técnicas do campo da Inteligência Artificial, e mais precisamente de Aprendizado de Máquina, para melhorar a precisão e a eficiência das tomadas de decisão. Entretanto, por maior que tenham sido os benefícios proporcionados pelos avanços no apoio computacional, as decisões são, em última análise, tomadas por humanos. E, sendo uma tarefa essencialmente humana, a influência dos vieses cognitivos em tomadas de decisão são um desafio relevante e pouco explorado. Esses vieses podem ser decorrentes de diversos fatores, incluindo preferências individuais, influências externas e derivações cognitivas inconscientes. Apesar dos esforços da área da Economia Comportamental em identificar e modelar esses vieses, seu impacto em contextos de decisões monetárias ainda é limitado. Portanto, este trabalho propõe uma arquitetura baseada em fundamentos ontológicos para identificar e analisar o impacto de vieses cognitivos em cenários de alto risco de perdas monetárias. Através da aplicação de técnicas de Ciência de Dados e Aprendizado de Máquina, o objetivo é propor uma metodologia implementada em um artefato computacional, capaz de automaticamente identificar padrões de vieses cognitivos a partir de um histórico de registros de decisões, gerando conhecimento sobre as preferências de risco dos tomadores de decisão e seus ganhos e perdas diante das suas escolhas. O viés específico explorado neste estudo é a Busca de Risco no domínio de perdas, conforme definido no Padrão Quádruplo do Kahneman. A avaliação da eficácia dessa proposta será realizada por meio de um estudo de caso utilizando um benchmark disponível na literatura, fornecendo insights sobre a aplicabilidade e os benefícios práticos da arquitetura proposta. / [en] The study of decision-making has gained more and more importance, from the classical conceptions of the economic man to the more recent concepts of bounded rationality and cognitive biases. Over time, the increasing complexity of decisions has driven the development of technologies such as Decision Support Systems and Predictive Models, highlighting more recently the incorporation of techniques from the field of Artificial Intelligence, and more precisely Machine Learning, to improve the accuracy and efficiency of decision-making. However, as great as the benefits provided by advances in computer support have been, humans are ultimately the ones to make decisions. And, being an essentially human task, the influence of cognitive biases on decision-making is a relevant and underexplored challenge. These biases can be due to various factors, including individual preferences, external influences, and unconscious cognitive derivations. Despite the efforts of the field of Behavioral Economics to identify and model these biases, their impact in contexts of monetary decisions is still limited. Therefore, this work proposes an architecture based on ontological foundations to identify and analyze cognitive biases in scenarios of high risk of monetary losses. Through the application of Data Science and Machine Learning techniques, we propose a methodology - implemented in a computational artifact - capable of automatically identifying patterns of cognitive biases from a history of decision records, generating knowledge about the risk preferences of decision makers and their gains and losses caused by their choices. The specific bias explored in this study is Risk Seeking in the loss domain, as defined in the Kahneman Quadruple Pattern. The evaluation of the effectiveness of this proposal will be carried out through a case study using a benchmark available in the literature, providing insights into the applicability and practical benefits of the proposed architecture.

A normative experimental study was undertaken to establish whether engaging in positive, negative, and neutral mental imagery affected the reaction rate of participants to positive, negative, and neutral word stimuli. The sample consisted of computer literate, English speaking participants with no history of clinical disorders. A total of 80 participants took part in the study, with 40 participants from either gender. The results of a factorial ANOVA indicated that the type of mental imagery engaged in had a significant effect on the rate at which participants responded to stimuli (p=.00023, F=8.4057), whilst the emotional valence of the stimuli did not have a significant effect (p=.30503, F=1.1877). However, the interaction between the type of mental imagery and the emotional valence of the stimuli was highly significant (p=.00794, F=3.4576), thereby indicating that engaging in positive or negative mental imagery did bias participants towards a faster reaction rate to positive or negative stimuli respectively. / M.A. (Psychology) / Psychology

Adolescent depression is a major public health problem, which is associated with educational problems, long-term psychiatric illness and suicide. One major source of stress during adolescence is peer rejection. In this thesis, I investigate the nature of the relationship between peer rejection and adolescent depression. In a review of longitudinal and experimental studies, I describe a bi-directional relationship between peer rejection and depressive symptoms. I then outline how genetic, cognitive and neural vulnerability may modify the effects of peer rejection on adolescent depression. Finally, I introduce five empirical chapters which test these hypotheses using different methodological approaches. The first study is a molecular genetic analysis of a sample of adolescents with and without a diagnosis of mood disorder. I report an interaction between diagnostic group, environmental stress (though not peer rejection specifically) and 5HTTLPR genotype on symptoms of anxiety, which supports the role of genetic factors in modifying the relationship between environmental stress and adolescent mood disorder. The second study is a behavioural study of negative attention biases in a typically developing sample of adolescents. I report a negative attention bias in adolescents with low (versus high) self-esteem. Although the data do not support a causal role for attention biases in adolescent depression, such biased cognitions could also moderate responses to peer rejection, maintaining affective symptoms. A final set of three fMRI datasets investigates how neural circuitry may influence depressed adolescents’ responses to peer rejection at three distinct stages: i) expectation of peer feedback, ii) the receipt of peer rejection, iii) emotion regulation of peer rejection. Data show distinct behavioural and neural differences between depressed patients and healthy controls during expectation and reappraisal of peer rejection, although heightened emotional reactivity immediately following the receipt of peer rejection did not differentiate behavioural or neural responses in adolescents with and without depression.

Syftet med vår undersökning har varit att, genom intervjuer med brottmålsadvokater, undersöka hur kvinnliga och manliga gärningspersoner framställs inom domstolsväsendet, samt hur detta kan förstås utifrån ett genusperspektiv som visar hur sociala konstruktioner bildas, reproduceras och cementeras utifrån kön och förväntade egenskaper vi tillskriver de olika könen. Vår undersökning är kvalitativ då vi för att besvara vårt syfte samt våra frågeställningar har genomfört semistrukturerade intervjuer med ett antal olika brottmålsadvokater som inom sin profession försvarar både kvinnliga och manliga förövare som står åtalade för brott av skiftande allvarlighetsgrad. Som bakgrund till analyserna av empirin har vi använt oss av teoretiska ramar som genus och könsroller samt stereotypisering vilket handlar om den kognitiva snedvridning som kan ske i bedömningen av gärningspersonernas brottslighet. Ett viktigt resultat i studien har visat att det i vissa fall förekommer skillnader i framställningen mellan kvinnliga och manliga gärningspersoner, samt att rättssäkerheten och den lagstadgade objektiviteten genom detta är hotad. / The purpose of this study has been to examine how female and male offenders are represented in the domain of justice substantialised through the Swedish court and legal system. Through interviews with a number of trial lawyers we are aiming for an understanding of these representations related to a gender studies perspective that shows how norms and stereotypes are reproduced and maintained on the basis of sex, gender and expected qualities and capabilities. This study raises questions about objectivity, impartial judgements and in the end justice. We are also trying to illustrate female offenders and how they are perceived in the Swedish court and legal system. Our study is qualitative and to answer our issues we have gone through semi structured interviews with trial lawyers that through their profession has defended both female and male offenders. Our scientific background and theoretical framework is gender and sex studies together with stereotypes and doing stereotypes which is a type of cognitive bias; a subject that we are also presenting. One of the most important results of this study is that there is a difference in how female offenders are represented compared to how male offenders are represented in the Swedish court and law system. Through this result we can see that the statutory objectivity is threatened.

This essay examines the presence of cognitive biases in governmental acquisitions of technical systems. The four examined biases are Prior hypotheses and focusing on limited targets, Exposure to limited alternatives, Insensitivity to outcome probabilities and Illusion of manageability. These were examined through a case study of systems purchases for governmental agencies. The essay identified parts of Försvarsmaktens handbok i studiemetodik where the text was written in such a way where there was a risk of bias being present. These were identified through a qualitative text analysis and semi-structured interviews. Because of the presence of bias found in the text, a chapter dedicated to risk of bias was recommended, as well as certain amendments to the text to prohibit biased interpretations. / Detta självständiga arbete granskar förekomsten av kognitiva bias, mentala feltänk, i myndighetsanskaffning av tekniska system. De fyra biaser som granskas är Prior hypotheses and focusing on limited targets, tidigare hypotes-bias, Exposure to limited alternatives, begränsade alternativ-bias, Insensitivity to outcome probabilities, okänslighet för sannolikhet-bias, och Illusion of manageability, illusion av hanterbarhet. Detta granskades i en fallstudie, där systeminköp för statliga myndigheter granskades. Texten identifierade delar av Försvarsmaktens handbok i studiemetodik där den var skriven på ett sådant sätt att dessa biaser kunde förekomma. Dessa identifierades genom en kvalitativ textanalys och semi-strukturerade intervjuer. På grund av förekomsten rekommenderades att ett biaskapitel införs i handboken, samt att utvalda delar av redan skriven text skrivs om eller belyser risken för påverkan av bias.

Användningen av artificiell intelligens (AI) har tredubblats på ett år och och anses av vissa vara det viktigaste paradigmskiftet i teknikhistorien. Den rådande AI-kapplöpningen riskerar att underminera frågor om etik och hållbarhet, vilket kan ge förödande konsekvenser. Artificiell intelligens har i flera fall visat sig avbilda, och till och med förstärka, befintliga snedvridningar i samhället i form av fördomar och värderingar. Detta fenomen kallas algoritmisk snedvridning (algorithmic bias). Denna studie syftar till att formulera ett ramverk för att minimera risken att algoritmisk snedvridning uppstår i AI-projekt och att anpassa det efter ett medelstort konsultbolag. Studiens första del är en litteraturstudie på snedvridningar - både ur ett kognitivt och ur ett algoritmiskt perspektiv. Den andra delen är en undersökning av existerande rekommendationer från EU, AI Sustainability Center, Google och Facebook. Den tredje och sista delen består av ett empiriskt bidrag i form av en kvalitativ intervjustudie, som har använts för att justera ett initialt ramverk i en iterativ process. / In the use of the third generation Artificial Intelligence (AI) for the development of products and services, there are many hidden risks that may be difficult to detect at an early stage. One of the risks with the use of machine learning algorithms is algorithmic bias which, in simplified terms, means that implicit prejudices and values are comprised in the implementation of AI. A well-known case is Google’s image recognition algorithm, which identified black people as gorillas. The purpose of this master thesis is to create a framework with the aim to minimise the risk of algorithmic bias in AI development projects. To succeed with this task, the project has been divided into three parts. The first part is a literature study of the phenomenon bias, both from a human perspective as well as from an algorithmic bias perspective. The second part is an investigation of existing frameworks and recommendations published by Facebook, Google, AI Sustainability Center and the EU. The third part consists in an empirical contribution in the form of a qualitative interview study which has been used to create and adapt an initial general framework. The framework was created using an iterative methodology where two whole iterations were performed. The first version of the framework was created using insights from the literature studies as well as from existing recommendations. To validate the first version, the framework was presented for one of Cybercom’s customers in the private sector, who also got the possibility to ask questions and give feedback regarding the framework. The second version of the framework was created using results from the qualitative interview studies with machine learning experts at Cybercom. As a validation of the applicability of the framework on real projects and customers, a second qualitative interview study was performed together with Sida - one of Cybercom’s customers in the public sector. Since the framework was formed in a circular process, the second version of the framework should not be treated as constant or complete. The interview study at Sida is considered the beginning of a third iteration, which in future studies could be further developed.