Perspectives on psychological science : a journal of the Association for Psychological Science
37462616
Technological innovations have become a key driver of societal advancements. Nowhere is this more evident than in the field of machine learning (ML), which has developed algorithmic models that shape our decisions, behaviors, and outcomes. These tool...
Induction-the ability to generalize from existing knowledge-is the cornerstone of intelligence. Cognitive models of human induction are largely limited to toy problems and cannot make quantitative predictions for the thousands of different induction ...
Normative and descriptive models have long vied to explain and predict human risky choices, such as those between goods or gambles. A recent study reported the discovery of a new, more accurate model of human decision-making by training neural networ...
BACKGROUND: Artificial intelligence (AI) has rapidly permeated various sectors, including healthcare, highlighting its potential to facilitate mental health assessments. This study explores the underexplored domain of AI's role in evaluating prognosi...
Applied psychology. Health and well-being
39168488
Demystifying machine learning (ML) approaches through the synergy of psychology and artificial intelligence can achieve a balance between predictive and explanatory power in model development while enhancing rigor in validation and reporting standard...
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
39278252
Episodic memories are experienced as belonging to a self that persists in time. We review evidence concerning the nature of human episodic memory and of the sense of self and how these emerge during development, proposing that the younger child exper...
Automated moral inference is an emerging topic of critical importance in artificial intelligence. The contemporary approach typically relies on language models to infer moral relevance or moral properties of a concept. This approach demands complex p...
BACKGROUND: Depressive symptoms in adolescents can significantly affect their daily lives and pose risks to their future development. These symptoms may be linked to various factors experienced during both childhood and adolescence. Machine learning ...
Childhood abuse represents one of the most potent risk factors for the development of psychopathology during childhood, accounting for 30-60% of the risk for onset. While previous studies have separately associated reductions in gray matter volume (G...
Models are often evaluated when their behavior is at its closest to a single, sometimes averaged, set of empirical results, but this evaluation neglects the fact that both model and human behavior can be heterogeneous. Here, we develop a measure, -di...