This Element is on new developments in the psychology of reasoning that raise or address philosophical questions. In traditional studies in the psychology of reasoning, the focus was on inference from arbitrary assumptions and not at all from beliefs, and classical binary logic was presupposed as the only standard for human reasoning. But recently a new Bayesian paradigm has emerged in the discipline. This views ordinary human reasoning as mostly inferring probabilistic conclusions from degrees of beliefs, or from hypothetical premises (...) relevant to a purpose at hand, and as often about revising or updating degrees of belief. This Element also covers new formulations of dual-process theories of the mind, stating that there are two types of mental processing, one rapid and intuitive and shared with other animals, and the other slow and reflective and more characteristic of human beings. The final topic covered is the new developments and rationality. (shrink)

The two main psychological theories of the ordinary conditional were designed to account for inferences made from assumptions, but few premises in everyday life can be simply assumed true. Useful premises usually have a probability that is less than certainty. But what is the probability of the ordinary conditional and how is it determined? We argue that people use a two stage Ramsey test that we specify to make probability judgements about indicative conditionals in natural language, and we describe experiments (...) that support this conclusion. Our account can explain why most people give the conditional probability as the probability of the conditional, but also why some give the conjunctive probability. We discuss how our psychological work is related to the analysis of ordinary indicative conditionals in philosophical logic. (shrink)

Stanovich & West distinguish between evolutionary rationality and normative rationality, and System 1 and System 2 mental processes. They hold that the main function of System 2 has to do with normative and not evolutionary rationality. We ask how System 2 could then be an adaptation, especially given S&W's own work on individual differences.

Context: Constructivist approaches to cognition have mostly been descriptive, and now face the challenge of specifying the mechanisms that may support the acquisition of knowledge. Departing from cognitivism, however, requires the development of a new functional framework that will support causal, powerful and goal-directed behavior in the context of the interaction between the organism and the environment. Problem: The properties affecting the computational power of this interaction are, however, unclear, and may include partial information from the environment, exploration, distributed processing (...) and aggregation of information, emergence of knowledge and directedness towards relevant information. Method: We posit that one path towards such a framework may be grounded in these properties, supported by dynamical systems. To assess this hypothesis, we describe computational models inspired from swarm intelligence, which we use as a metaphor to explore the practical implications of the properties highlighted. Results: Our results demonstrate that these properties may serve as the basis for complex operations, yielding the elaboration of knowledge and goal-directed behavior. Implications: This work highlights aspects of interaction that we believe ought to be taken into account when characterizing the possible mechanisms underlying cognition. The scope of the models we describe cannot go beyond that of a metaphor, however, and future work, theoretical and experimental, is required for further insight into the functional role of interaction with the environment for the elaboration of complex behavior. Constructivist content: Inspiration for this work stems from the constructivist impetus to account for knowledge acquisition based on interaction. (shrink)

Early versions of satellite and radiosonde datasets suggested that the tropical surface had warmed more than the troposphere, while climate models consistently showed tropospheric amplification of surface warming in response to human-caused increases in greenhouse gases. We revisit such comparisons here using new observational estimates of surface and tropospheric temperature changes. We find that there is no longer a serious discrepancy between modeled and observed trends in the tropics. Our results contradict a recent claim that all simulated temperature trends in (...) the tropical troposphere are inconsistent with observations. This claim was based on the use of older radiosonde and satellite datasets and on two methodological errors: the neglect of observational trend uncertainties introduced by interannual climate variability and application of an inappropriate statistical “consistency test”.This emerging reconciliation of models and observations has two primary explanations. First, because of changes in the treatment of buoy and satellite information, new surface temperature datasets yield slightly reduced tropical warming relative to earlier versions. Second, recently developed satellite and radiosonde datasets now show larger warming of the tropical lower troposphere. In the case of a new satellite dataset from remote sensing systems, enhancedRSS warming is due to an improved procedure of adjusting for inter-satellite biases. When the RSS-derived tropospheric temperature trend is compared with four different observed estimates of surface temperature change, the surface warming is invariably amplified in the tropical troposphere, consistent with model results. Even if we use data from a second satellite dataset with smaller tropospheric warming than in remote sensing systems RSS, observed tropical lapse rates are not significantly different from those in all model simulations.Our results contradict a recent claim that all simulated temperature trends in the tropical troposphere and in tropical lapse rates are inconsistent with observations. This claim was based on the use of older radiosonde and satellite datasets and on two methodological errors: the neglect of observational trend uncertainties introduced by interannual climate variability and application of an inappropriate statistical “consistency test”. (shrink)

Deep brain stimulation — a novel surgical procedure — is emerging as a treatment of last resort for people diagnosed with neuropsychiatric disorders such as severe obsessive-compulsive disorder. The US Food and Drug Administration granted a so-called humanitarian device exemption to allow patients to access this intervention, thereby removing the requirement for a clinical trial of the appropriate size and statistical power. Bypassing the rigors of such trials puts patients at risk, limits opportunities for scientific discovery, and gives device manufacturers (...) unique marketing opportunities. We argue that Congress and federal regulators should revisit the humanitarian device exemption to ensure that it is not used to sidestep careful research that can offer valuable data with appropriate patient safeguards. (shrink)