Annual review of psychology最新文献

Recent progress in artificial intelligence (AI) is exciting, but can AI models tell us about the human mind? AI models have a long history of being used as theoretical artifacts in cognitive science, but one key difference in the current generation of models is that they are stimulus computable, meaning that they can operate over stimuli that are similar to those experienced by people. This advance creates important opportunities for deepening our understanding of the human mind. We argue here that the most exciting of these is the use of AI models as cognitive models, wherein they are trained using human-scale input data and evaluated using careful experimental probes. Such cognitive models constitute a substantial advance that can inform theories of human intelligence by helping to explain and predict behavior.

Cognitive biases significantly influence decision-making by distorting how individuals perceive and evaluate outcomes over time. This systematic review synthesizes research from various domains, including behavioral economics, psychology, and health, to explore six time-related biases affecting intertemporal judgments and trade-offs. We analyze the underlying mechanisms of each bias, map their interrelationships, and uncover their impacts on both individual choices and societal decisions. Drawing upon empirical evidence, we propose tailored strategies to mitigate the adverse effects of these biases. Our findings contribute to the literature not only by enhancing the understanding of time-related cognitive biases but also by providing practical insights for improving decision-making and policy design aimed at promoting long-term well-being. The review concludes by highlighting critical gaps in the literature and outlining a future research agenda to further investigate and address biases in intertemporal decision-making.

The mechanistic underpinnings of sustained attention, vigilance, and the ability to continue responding to critical stimuli over time, despite decades of research, are not well understood. Although sustained attention is vital for survival and is studied in many taxa, a lack of comparative work and a greater research focus on the high-level psychological aspects of human sustained attention performance have hindered progress in our understanding of it. We posit that an interdisciplinary approach between the biological and psychological fields, involving research on humans and nonhuman animals, will illuminate the biological mechanisms involved. A key obstacle to a comparative approach is the vast terminology used to illustrate similar phenomena across disciplines. We compare the research on sustained attention in humans and animals, showing that the comparative gap is not insurmountable. To resolve the communication issue, we outline the different terms used and suggest future directions to encourage productive engagement between the two fields. Additionally, we propose that an interdisciplinary perspective will be advantageous for developing countermeasures to declining sustained attention.

Many psychologists rely on surveys, questionnaires, and measurement scales because psychological constructs like depression, motivation, or extraversion cannot be directly measured with physical instruments. Scale validation crucially provides evidence that scores from such scales capture their intended target. The prevailing scale validation approach involves comparing factor-analytic model fit indices to suggested benchmarks, and it is so engrained in psychological research that the article proposing the benchmarks is among the most cited works across any scientific discipline. However, methodological research finds that psychologists overgeneralize the benchmarks so that they no longer function as originally intended. This has widespread implications for psychologists and casts some doubt on conclusions regarding the validity of our measurement scales. This review covers the history and origin of scale validation benchmarks, how benchmarks rose to prominence and became overgeneralized, recently proposed alternatives to traditional benchmarks, and future directions in this methodological area that affects many subfields of psychology.

Looking back on our life and work, we reflect on the changes in our thinking due to three scientific and technological revolutions. These are information processing, computers, and brain imaging, and together they ousted behaviorism from its dominant position in experimental psychology. We champion a model of the mind that is hierarchically organized with both a robust unconscious and a harder-to-pin-down conscious mode of operation. Our studies were inspired by disorders that made us realize that cognitive processes at all levels of the information processing hierarchy impact social interactions. We locate the influence of culture at the highest level of this processing hierarchy. Here we see the interface between different minds and the importance of norms when regulating the opposing trends in our complex and even contradictory social nature.