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Knowledge resistance : how we avoid insight from others
Why do people and groups ignore, deny and resist knowledge about society's many problems? In a world of 'alternative facts', 'fake news' that some believe could be remedied by 'factfulness', the question has never been more pressing. After years of ideologically polarised debates on this topic, the book seeks to further advance our understanding of the phenomenon of knowledge resistance by integrating insights from the social, economic and evolutionary sciences. It identifies simplistic views in public and scholarly debates about what facts, knowledge and human motivations are and what 'rational' use of information actually means. The examples used include controversies about nature-nurture, climate change, gender roles, vaccination, genetically modified food and artificial intelligence. Drawing on cutting-edge scholarship as well as personal experiences of culture clashes, the book is aimed at the general, educated public as well as students and scholars interested in the interface of human motivation and the urgent social problems of today.
Book
Mindful Economics: The Production, Consumption, and Value of Beliefs
In this paper, we provide a perspective into the main ideas and findings emerging from the growing literature on motivated beliefs and reasoning. This perspective emphasizes that beliefs often fulfill important psychological and functional needs of the individual. Economically relevant examples include confidence in ones' abilities, moral self-esteem, hope and anxiety reduction, social identity, political ideology, and religious faith. People thus hold certain beliefs in part because they attach value to them, as a result of some (usually implicit) tradeoff between accuracy and desirability. In a sense, we propose to treat beliefs as regular economic goods and assets—which people consume, invest in, reap returns from, and produce, using the informational inputs they receive or have access to. Such beliefs will be resistant to many forms of evidence, with individuals displaying non-Bayesian behaviors such as not wanting to know, wishful thinking, and reality denial.
Journal Article
Health-protective behaviour, social media usage and conspiracy belief during the COVID-19 public health emergency
BackgroundSocial media platforms have long been recognised as major disseminators of health misinformation. Many previous studies have found a negative association between health-protective behaviours and belief in the specific form of misinformation popularly known as ‘conspiracy theory’. Concerns have arisen regarding the spread of COVID-19 conspiracy theories on social media.MethodsThree questionnaire surveys of social media use, conspiracy beliefs and health-protective behaviours with regard to COVID-19 among UK residents were carried out online, one using a self-selecting sample (N = 949) and two using stratified random samples from a recruited panel (N = 2250, N = 2254).ResultsAll three studies found a negative relationship between COVID-19 conspiracy beliefs and COVID-19 health-protective behaviours, and a positive relationship between COVID-19 conspiracy beliefs and use of social media as a source of information about COVID-19. Studies 2 and 3 also found a negative relationship between COVID-19 health-protective behaviours and use of social media as a source of information, and Study 3 found a positive relationship between health-protective behaviours and use of broadcast media as a source of information.ConclusionsWhen used as an information source, unregulated social media may present a health risk that is partly but not wholly reducible to their role as disseminators of health-related conspiracy beliefs.
Journal Article
The Mechanics of Motivated Reasoning
Whenever we see voters explain away their preferred candidate's weaknesses, dieters assert that a couple scoops of ice cream won't really hurt their weight loss goals, or parents maintain that their children are unusually gifted, we are reminded that people's preferences can affect their beliefs. This idea is captured in the common saying, “People believe what they want to believe.” But people don't simply believe what they want to believe. Psychological research makes it clear that “motivated beliefs” are guided by motivated reasoning—reasoning in the service of some self-interest, to be sure, but reasoning nonetheless. People generally reason their way to conclusions they favor, with their preferences influencing the way evidence is gathered, arguments are processed, and memories of past experience are recalled. Each of these processes can be affected in subtle ways by people's motivations, leading to biased beliefs that feel objective. In this symposium introduction, we set the stage for discussion of motivated beliefs in the papers that follow by providing more detail about the underlying psychological processes that guide motivated reasoning.
Journal Article
An effective conflict management method based on belief similarity measure and entropy for multi-sensor data fusion
Multi-sensor data fusion has received substantial attention thanks to its ability to integrate information from distinct sources efficiently. Nevertheless, the information collected from multi-sensors may be uncertain and imprecise, even conflicting in real applications. As a distinguished theory to handle uncertain and imprecise information, belief functions theory (BFT) is prevalent in the various fields of multi-sensor data fusion. Unfortunately, counter-intuitive behaviors may generate once facing highly conflicting pieces of evidence. To deal with the above-mentioned issue, in this paper, we study a novel belief Sørensen coefficient (BSC) to measure the conflict between the pieces of evidence based on BFT. On the top of BSC, we propose a new belief conflict coefficient, and prove some important properties, namely, non-negativity, symmetry, non-degeneracy, bounded, extreme consistency and insensitivity to refinement. In parallel, some numerical examples are employed to demonstrate the superiority of the belief conflict coefficient in quantifying the degree of conflict between the pieces of evidence. Finally, we design a new multi-sensor data fusion method based on the proposed BSC and the improved belief entropy, and verify the effectiveness and practicability of the proposed method with respect to other methods through several application cases.
Journal Article
House Price Beliefs And Mortgage Leverage Choice
We study the relationship between homebuyers’ beliefs about future house price changes and their mortgage leverage choices. Whether more pessimistic homebuyers choose higher or lower leverage depends on their willingness and ability to reduce the size of their housing market investments. When households primarily maximize the levered return of their property investments, more pessimistic homebuyers reduce their leverage to purchase smaller houses. On the other hand, when considerations such as family size pin down the desired property size, pessimistic homebuyers reduce their financial exposure to the housing market by making smaller downpayments to buy similarly-sized homes. To determine which scenario better describes the data, we investigate the cross-sectional relationship between house price beliefs and mortgage leverage choices in the U.S. housing market. We use plausibly exogenous variation in house price beliefs to show that more pessimistic homebuyers make smaller downpayments and choose higher leverage, in particular in states where default costs are relatively low, as well as during periods when house prices are expected to fall on average. Our results highlight the important role of heterogeneous beliefs in explaining households’ financial decisions.
Journal Article
Belief updating: does the 'good-news, bad-news' asymmetry extend to purely financial domains?
Bayes' statistical rule remains the status quo for modeling belief updating in both normative and descriptive models of behavior under uncertainty. Some recent research has questioned the use of Bayes' rule in descriptive models of behavior, presenting evidence that people overweight `good news' relative to `bad news' when updating ego-relevant beliefs. In this paper, we present experimental evidence testing whether this `good-news, bad-news' effect is present in a financial decision making context (i.e. a domain that is important for understanding much economic decision making). We find no evidence of asymmetric updating in this domain. In contrast, in our experiment, belief updating is close to the Bayesian benchmark on average. However, we show that this average behavior masks substantial heterogeneity in individual updating behavior. We find no evidence in support of a sizeable subgroup of asymmetric updators.
Journal Article
Determinants of College Major Choice: Identification using an Information Experiment
This article studies the determinants of college major choice using an experimentally generated panel of beliefs, obtained by providing students with information on the true population distribution of various major-specific characteristics. Students logically revise their beliefs in response to the information, and their subjective beliefs about future major choice are associated with beliefs about their own earnings and ability. We estimate a rich model of college major choice using the panel of beliefs data. While expected earnings and perceived ability are a significant determinant of major choice, heterogeneous tastes are the dominant factor in the choice of major. Analyses that ignore the correlation in tastes with earnings expectations inflate the role of earnings in college major choices. We conclude by computing the welfare gains from the information experiment and find positive average welfare gains.
Journal Article
Why People \Don't Trust the Evidence\: Motivated Reasoning and Scientific Beliefs
In this commentary, we embed the volume's contributions on public beliefs about science in a broader theoretical discussion of motivated political reasoning. The studies presented in the preceding section of the volume consistently find evidence for hyperskepticism toward scientific evidence among ideologues, no matter the domain or context—and this skepticism seems to be stronger among conservatives than liberals. Here, we show that these patterns can be understood as part of a general tendency among individuals to defend their prior attitudes and actively challenge attitudinally incongruent arguments, a tendency that appears to be evident among liberals and conservatives alike. We integrate the empirical results reported in this volume into a broader theoretical discussion of the John Q. Public model of information processing and motivated reasoning, which posits that both affective and cognitive reactions to events are triggered unconsciously. We find that the work in this volume is largely consistent with our theories of affect-driven motivated reasoning and biased attitude formation.
Journal Article