Making probability judgments of future product failures: The role of mental unpacking

When consumers mentally unpack (i.e., imagine) the reasons for product failure, their probability judgments of future product failures are higher than when no mental unpacking is undertaken. However, increasing the level of mental unpacking does not lead to monotonically increasing effects on probability judgments but results in inverted U-shaped relationships. Using a two-factor structure, we propose that when consumers undertake mental unpacking, there will be two conflicting processes; while imagining causes for an event will lead to greater perceived probability, the greater difficulty in generating reasons for an event will lead to lower perceived probability.     

Non-bayesian inference: causal structure trumps correlation

The study tests the hypothesis that conditional probability judgments can be influenced by causal links between the target event and the evidence even when the statistical relations among variables are held constant. Three experiments varied the causal structure relating three variables and found that (a) the target event was perceived as more probable when it was linked to evidence by a causal chain than when both variables shared a common cause; (b) predictive chains in which evidence is a cause of the hypothesis gave rise to higher judgments than diagnostic chains in which evidence is an effect of the hypothesis; and (c) direct chains gave rise to higher judgments than indirect chains. A Bayesian learning model was applied to our data but failed to explain them. An explanation-based hypothesis stating that statistical information will affect judgments only to the extent that it changes beliefs about causal structure is consistent with the results.     

The where and when of likely and unlikely events

Do people think likelihood is distributed evenly or do they have an intuition about the types of contexts in which likely and unlikely events tend to occur? Drawing on a probability-as-distance framework, the current research suggests that people relate probability to other distance dimensions, expecting unlikely events to more often happen in distant contexts and likely events in near contexts. Evidence for this association emerges using within-subject designs where participants directly assign low and high likelihood events to near and distant contexts (Studies 1 and 2), as well as between-subjects designs that focus on a variety of related judgments, including willingness to bet on favorites and long-shots (Study 3), decisions about insurance purchases (Study 4), and expectations regarding games of chance (Study 5). Results appear consistent across outcomes of differing valence (Study 5). Implications and future research directions are discussed.     

Feelings of dread and intertemporal choice

It frequently has been observed that people discount future rewards relative to present rewards. However, the literature on intertemporal choices involving emotional upsets and losses is fraught with inconsistencies, with some studies finding similar discounting of gains and losses, and others reporting that participants elect to undergo negative experiences sooner rather than later. To help resolve these contradictions, time preferences for different types of aversive experiences (social rejection, embarrassment, pain, monetary and property loss) were examined in five studies. Most participants preferred to postpone monetary and property losses, but intertemporal choices for other unpleasant experiences showed highly variable responses, with some participants deferring them as long as possible, and many electing to experience them immediately. Time preferences for these negative experiences were correlated, but were independent of time preference for rewards. It is argued (following Loewenstein, 1987 ) that anticipation of dread plays a key role in many people's choices about timing of aversive experiences. This interpretation was supported by choices about when to learn of a very unpleasant event whose timing was fixed (Study 3), and by a novel preference reversal (Study 4). Study 5 examined how actual and hypothetical experiences of dread unfolded over time; the results were consistent with a dread‐based interpretation of choices in the preceding studies. Copyright © 2010 John Wiley & Sons, Ltd.     

Can probability neglect bias promote social distancing during the COVID-19 pandemic?

The effectiveness of a stay-at-home order depends on the speed of behavioral changes that are triggered by risk perception. Probability neglect bias, one of the cognitive biases, may lead people to engage in social distancing. However, there is no empirical evidence of the relationship between probability neglect bias and social distancing. This study aims to examine the relationship between individual differences in susceptibility to probability neglect bias and the level of social distancing practice during the early stages of the COVID-19 outbreak in Japan. The level of engagement in social distancing was defined as the narrowing of life-space mobility. We conducted a web-based questionnaire survey among 1000 adults living in central Tokyo, Japan, at the beginning of the pandemic outbreak. Our results show that people had a strong fear of infection in the early pandemic stages. Approximately 60% of our subjects were influenced by probability neglect bias. People susceptible to probability neglect bias engaged in social distancing more intensely than those who were not susceptible after the state of emergency was lifted.     

Weighing Outcomes by Time or Against Time? Evaluation Rules in Intertemporal Choice

Models of intertemporal choice draw on three evaluation rules, which we compare in the restricted domain of choices between smaller sooner and larger later monetary outcomes. The hyperbolic discounting model proposes an alternative‐based rule, in which options are evaluated separately. The interval discounting model proposes a hybrid rule, in which the outcomes are evaluated separately, but the delays to those outcomes are evaluated in comparison with one another. The tradeoff model proposes an attribute‐based rule, in which both outcomes and delays are evaluated in comparison with one another: People consider both the intervals between the outcomes and the compensations received or paid over those intervals. We compare highly general parametric functional forms of these models by means of a Bayesian analysis, a method of analysis not previously used in intertemporal choice. We find that the hyperbolic discounting model is outperformed by the interval discounting model, which, in turn, is outperformed by the tradeoff model. Our cognitive modeling is among the first to offer quantitative evidence against the conventional view that people make intertemporal choices by discounting the value of future outcomes, and in favor of the view that they directly compare options along the time and outcome attributes.     

What is “Intervention”?

I begin by noting that several theologians and others object to special divine action (divine intervention and action beyond conservation and creation) on the grounds that it is incompatible with science. These theologians are thinking of classical Newtonian science; I argue that in fact classical science is in no way incompatible with special divine action, including miracle. What is incompatible with special divine action is the Laplacean picture, which involves the causal closure of the universe. I then note that contemporary, quantum mechanical science doesn't even initially appear to be incompatible with special divine action. Nevertheless, many who are well aware of the quantum mechanical revolution (including some members of the Special Divine Action Project) still find a problem with special divine action, hoping to find an understanding of it that doesn't involve divine intervention. I argue that their objections to intervention are not sound. Furthermore, it isn't even possible to say what intervention is, given the quantum mechanical framework. I conclude by offering an account of special divine action that isn't open to their objections to intervention.     

Knowledge and man

Collective Intelligence (CI) can be formalized as a specific1 computational process through the use of a molecular model of computations and mathematical logic, in terms of interacting information_molecules, which are chaotically or quasi-chaotically displacing and running natural-based inference processes in their own environment. The formal definition of Collective Intelligence as a property of a social structure of beings of any nature is surprisingly short and abstract (which is astonishing) from definitions of Life. The formal definition of Collective Intelligence proposed by the author in the last few years seems to be valid for the whole spectrum of beings, in human social structures to ants in colonies, and even for bacterial colonies. It has recently been found that the CI definition also has an engineering value. The theory of CI can also be used to better understand Evolution because it allows us to locate and relate Life and Intelligence in Evolution. Moreover, this approach presents Evolution as something more complex than can be concluded from Darwinism. Probably the most surprising fact is that a simple extrapolation of the definition of Collective Intelligence brings us to the conclusion that most probably the first elementary Collective Intelligence emerged on Earth in the "chemical soup of primeval molecules," much before Life emerged. Collective Intelligence can be defined with fewer and weaker conditions than Life requires. Perhaps the emergence of that early elementary Collective Intelligence provided the basic momentum to build Life as we now know it. Thus Evolution caused Intelligence to create Life. Our hypothesis is consistent with biochemistry theories that "primeval biochemical molecules" started to interact, "firing" the Collective Intelligence of their "elementary chemical social structure" for survival. This successful action boosted further growth of complexity in that "elementary social structure," which finally resulted in the emergence of "well-defined Life." Furthermore, it provided a self-propagating cycle of growth of individual and collective Intelligence and individual and collective Life. The Collective Intelligence of ants, wolves, humans, and so forth today is only a higher level of Collective Intelligence development. Thus the present Evolution is a computational process of unidentified complexity where Life, Intelligence, and perhaps other as yet undiscovered components play temporary roles. In this paper we provide formalization and a proposed partial proof for this hypothesis.     

Additivity neglect in probability estimates: Effects of numeracy and response format

When people are asked to estimate the probabilities for an exhaustive set of more than two events, they often produce probabilities that add up to more than 100%. Potential determinants for such additivity neglect are explored in four experiments. Additive responses vary between experimental conditions, mainly as a result of response format, with a scale format leading to fewer additive responses than a list format with self-generated, written probabilities. Participants with high numeracy scores produced more additive responses, especially after being primed with a numeracy scale. Additivity neglect for 100% sums appears to be unrelated to other subadditive judgments, like non-additive disjunctions. We conclude that additivity neglect is caused by a case-based approach, which comes natural in real-life situations where the full set of outcomes is not available.     

Female Prairie Deer Mice Prefer Conspecific Flesh Over Contraspecific Flesh

Hungry adult female deer mice were presented with freshly asphyxiated conspecifics and house mice. The deer mice showed a reliable preference for the conspecific flesh during the first 2 hr of testing, but this preference was attenuated during the following 20 hr of testing. Previous research has shown that male deer mice prefer contraspecific flesh. The preference of female deer mice for conspecific flesh is attributed to their tendency to be more aggressive toward living conspecifics than are male deer mice and their tendency to avoid living contraspecifics more than do male deer mice.