Public opposition to genetic modification (GM) technology in the food domain is widespread (Frewer et al., 2013). In a survey of U.S. residents representative of the population on gender, age, and income, 64% opposed GM, and 71% of GM opponents (45% of the entire sample) were "absolutely" opposed-that is, they agreed that GM should be prohibited no matter the risks and benefits. "Absolutist" opponents were more disgust sensitive in general and more disgusted by the consumption of genetically modified food than were non-absolutist opponents or supporters. Furthermore, disgust predicted support for legal restrictions on genetically modified foods, even after controlling for explicit risk-benefit assessments. This research suggests that many opponents are evidence insensitive and will not be influenced by arguments about risks and benefits.

Five university-based research groups competed to recruit forecasters, elicit their predictions, and aggregate those predictions to assign the most accurate probabilities to events in a 2-year geopolitical forecasting tournament. Our group tested and found support for three psychological drivers of accuracy: training, teaming, and tracking. Probability training corrected cognitive biases, encouraged forecasters to use reference classes, and provided forecasters with heuristics, such as averaging when multiple estimates were available. Teaming allowed forecasters to share information and discuss the rationales behind their beliefs. Tracking placed the highest performers (top 2% from Year 1) in elite teams that worked together. Results showed that probability training, team collaboration, and tracking improved both calibration and resolution. Forecasting is often viewed as a statistical problem, but forecasts can be improved with behavioral interventions. Training, teaming, and tracking are psychological interventions that dramatically increased the accuracy of forecasts. Statistical algorithms (reported elsewhere) improved the accuracy of the aggregation. Putting both statistics and psychology to work produced the best forecasts 2 years in a row.

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Genetically engineered food has had its DNA, RNA, or proteins manipulated by intentional human intervention. We provide an overview of the importance and regulation of genetically engineered food and lay attitudes toward it. We first discuss the pronaturalness context in the United States and Europe that preceded the appearance of genetically engineered food. We then review the definition, prevalence, and regulation of this type of food. Genetically engineered food is widespread in some countries, but there is great controversy worldwide among individuals, governments, and other institutions about the advisability of growing and consuming it. In general, life scientists have a much more positive view of genetically engineered food than laypeople. We examine the bases of lay opposition to genetically engineered food and the evidence for how attitudes change. Laypeople tend to see genetically engineered food as dangerous and offering few benefits. We suggest that much of the lay opposition is morally based. One possibility is that, in some contexts, people view nature and naturalness as sacred and genetically engineered food as a violation of naturalness. We also suggest that for many people these perceptions of naturalness and attitudes toward genetically engineered food follow the sympathetic magical law of contagion, in which even minimal contact between a natural food and an unnatural entity, either a scientist or a piece of foreign DNA, pollutes or contaminates the natural entity and renders it unacceptable or even immoral to consume.

Abstract We demonstrate that natural products are more strongly preferred when used to prevent a problem than when used to cure a problem (the prevent/cure effect). This organizing principle explains variation in the preference for natural across distinct product categories (e.g., food vs. medicine), within product categories (e.g., between different types of medicines), and for the same product depending on how it is used (to prevent or to cure ailments). The prevent/cure effect is driven by two factors: lay beliefs about product attributes and importance of product attributes. Specifically, a) consumers hold lay beliefs that natural products are safer and less potent, and b) consumers care more about safety and less about potency when preventing as compared to when curing, which leads to a stronger preference for natural when preventing. Consistent with this explanation, when natural products are described as more risky and more potent, reversing the standard inferences about naturalness, then natural products become more preferred for curing than for preventing. This research sheds light on when the marketing of “natural” is most appealing to consumers.