Can human intelligence safeguard against artificial intelligence? Exploring individual differences in the discernment of human from AI texts.

Artificial intelligence (AI) models can produce output that closely mimics human-generated content. We examined individual differences in the human ability to differentiate human- from AI-generated texts, exploring relationships with fluid intelligence, executive functioning, empathy, and digital habits. Overall, participants exhibited better than chance text discrimination, with substantial variation across individuals. Fluid intelligence strongly predicted differences in the ability to distinguish human from AI, but executive functioning and empathy did not. Meanwhile, heavier smartphone and social media use predicted misattribution of AI content (mistaking it for human). Determinations about the origin of encountered content also affected sharing preferences, with those who were better able to distinguish human from AI indicating a lower likelihood of sharing AI content online. Word-level differences in linguistic composition of the texts did not meaningfully influence participants' judgements. These findings inform our understanding of how individual difference factors may shape the course of human interactions with AI-generated information.

Awake targeted memory reactivation doesn't work.

Memories are pliable and can be biased by post-encoding information. In targeted memory reactivation (TMR) studies, participants encode information then sleep, during which time sounds or scents that were previously associated with the encoded images are re-presented in an effort to trigger reactivation of the associated memory traces. Upon subsequent testing, memory for reactivated items is often enhanced. Is sleep essential for this process? The literature on awake TMR is small and findings are mixed. Here, we asked English-speaking adults to learn Japanese vocabulary words. During a subsequent active rest phase, participants played Tetris while sound cues associated with the vocabulary words were presented. Results showed that when memories were reactivated, they were either disrupted (Experiment 1) or unaffected (Experiments 2, 3). These findings indicate that awake TMR is not beneficial, and may actually impair subsequent memory. These findings have important implications for research on memory consolidation and reactivation.

Digital Media and Developing Brains: Concerns and Opportunities.

Purpose of Review: The incorporation of digital technologies and their use in youth's everyday lives has been increasing rapidly over the past several decades with possible impacts on youth development and mental health. This narrative review aimed to consider how the use of digital technologies may be influencing brain development underlying adaptive and maladaptive screen-related behaviors. Recent Findings: To explore and provide direction for further scientific inquiry, an international group of experts considered what is known, important gaps in knowledge, and how a research agenda might be pursued regarding relationships between screen media activity and neurodevelopment from infancy through childhood and adolescence. While an understanding of brain-behavior relationships involving screen media activity has been emerging, significant gaps exist that have important implications for the health of developing youth. Summary: Specific considerations regarding brain-behavior relationships involving screen media activity exist for infancy, toddlerhood, and early childhood; middle childhood; and adolescence. Transdiagnostic frameworks may provide a foundation for guiding future research efforts. Translating knowledge gained into better interventions and policy to promote healthy development is important in a rapidly changing digital technology environment.