Michel Gonzalez

Pure Reasoning in 12-Month-Old Infants as Probabilistic Inference

Twelve-month-old infants employ Bayesian statistics. Many organisms can predict future events from the statistics of past experience, but humans also excel at making predictions by pure reasoning: integrating multiple sources of information, guided by abstract knowledge, to form rational expectations about novel situations, never directly experienced. Here, we show that this reasoning is surprisingly rich, powerful, and coherent even in preverbal infants. When 12-month-old infants view complex displays of multiple moving objects, they form time-varying expectations about future events that are a systematic and rational function of several stimulus variables. Infants’ looking times are consistent with a Bayesian ideal observer embodying abstract principles of object motion. The model explains infants’ statistical expectations and classic qualitative findings about object cognition in younger babies, not originally viewed as probabilistic inferences.

Probabilistic Cognition in Two Indigenous Mayan Groups

Significance Correct probabilistic evaluations are one of the hallmarks of rationality. Is the human ability to make them dependent on formal education, or does it emerge regardless of instruction and culture? This paper shows that preliterate and prenumerate Mayan adults are able to solve a variety of probabilistic problems. These individuals correctly use prior and posterior information, proportions and elementary combinatorial procedures to predict the occurrence of random outcomes. And they perform like Mayan school children and Western controls. The finding that adults with no formal education are able to make suitable predictions indicates that, regardless of schooling and culture, the human mind possesses a basic probabilistic knowledge. Is there a sense of chance shared by all individuals, regardless of their schooling or culture? To test whether the ability to make correct probabilistic evaluations depends on educational and cultural guidance, we investigated probabilistic cognition in preliterate and prenumerate Kaqchikel and K’iche’, two indigenous Mayan groups, living in remote areas of Guatemala. Although the tested individuals had no formal education, they performed correctly in tasks in which they had to consider prior and posterior information, proportions and combinations of possibilities. Their performance was indistinguishable from that of Mayan school children and Western controls. Our results provide evidence for the universal nature of probabilistic cognition.

Improving public interpretation of probabilistic test results: distributive evaluations.

Health service users err in posttest probability evaluations. Here we document for the first time that users succeed when they reason about numbers of cases and make distributive evaluations. A sample of women interested in prenatal testing incorrectly evaluated the posttest probability that a given fetus had an anomaly, but regardless of their numeracy level, they correctly apportioned the cases for and against that hypothesis. This finding shows that health service users are not doomed to fail in dealing with single-case probabilities and suggests that probabilistic data can be used effectively for communicating test results.

Natural Frequencies Do Not Foster Public Understanding of Medical Test Results.

Major organizations recommend presenting medical test results in terms of natural frequencies, rather than single-event probabilities. The evidence, however, is that natural frequency presentations benefit at most one-fifth of samples of health service users and patients. Only one study reported a substantial benefit of these presentations. Here, we replicate that study, testing online survey respondents. Study 1 attributed the previously reported benefit of natural frequencies to a scoring artifact. Study 2 showed that natural frequencies may elicit evaluations that conflict with the normatively correct one, potentially hindering informed decision making. Ironically, these evaluations occurred less often when respondents reasoned about single-event probabilities. These results suggest caution in promoting natural frequencies as the best way to communicate medical test data to health service users and patients.

The Context of Available Options Affects Health Care Decisions: A Generalization Study

Background. When a given option is presented along with 2 alternatives, similar to each other, health care professionals choose it more often than when it is presented with just one of the alternatives. This inconsistent decision pattern may depend on the conflict generated from choosing between 2 highly similar options. Objective. To generalize the effect by using realistic scenarios that involve 2 alternatives displaying various degrees of similarity. Methods. One hundred fifty-five psychiatrists, 149 gynecologists, and 89 nurse managers had to indicate the treatment they would recommend in clinical scenarios containing either 3 options or just 2 of them. The similarity between the 2 alternatives varied across scenarios, ranging from a very high (psychiatric scenario) to an only moderately high (nursing management scenario) to a limited level (gynecological scenario). Results. Professionals chose the focal option more often when both alternatives were available. The paradoxical effect occurred for all scenarios—namely, when the alternatives were medication variants (psychiatric scenario), when most of the features they shared produced their effect at a different extent in the 2 cases (nursing management scenario), and some of their consequences were at variance (gynecological problem). Conclusions. The context of available options affects professionals’ choices when the alternatives are similar but also when they present diverging features. Professionals need to be aware of such a source of practice variability and are encouraged to consider each option per se before they compare the available options.