Comment

The use of typological conceptions of race in science is not based in evidence. A recent report from the National Academy of Sciences, Engineering, and Medicine, USA clarifies how human populations should be described in genetics and genomics research. It makes twelve recommendations that are highly relevant to behavioural genetics.

Most scientific prizes and medals are named after men, and most of these are also awarded to men. The very few awards named after women or not named after a person at all are more frequently awarded to women, although parity between the gender of recipients is still not achieved. We call on the scientific community to rethink the naming of academic awards, medals and prizes, their nomination and selection criteria, and to diversify awarding committees and procedures to ensure greater inclusivity.

Large language models can be construed as ‘cognitive models’, scientific artefacts that help us to understand the human mind. If made openly accessible, they may provide a valuable model system for studying the emergence of language, reasoning and other uniquely human behaviours.

Large language models (LLMs) are impressive technological creations but they cannot replace all scientific theories of cognition. A science of cognition must focus on humans as embodied, social animals who are embedded in material, cultural and technological contexts.

Algorithms are designed to learn user preferences by observing user behaviour. This causes algorithms to fail to reflect user preferences when psychological biases affect user decision making. For algorithms to enhance social welfare, algorithm design needs to be psychologically informed.

The current debate surrounding the use and regulation of artificial intelligence (AI) in Brazil has social and political implications. We summarize these discussions, advocate for balance in the current debate around AI and fake news, and caution against preemptive AI regulation.

Social and behavioural science offers a valuable toolkit for combating pandemics, but has not been broadly applied to tackle the rising pandemic of antimicrobial resistance.

Large language models (LLMs) do not distinguish between fact and fiction. They will return an answer to almost any prompt, yet factually incorrect responses are commonplace. To ensure our use of LLMs does not degrade science, we must use them as zero-shot translators: to convert accurate source material from one form to another.

State-of-the-art generative artificial intelligence (AI) can now match humans in creativity tests and is at the cusp of augmenting the creativity of every knowledge worker on Earth. We argue that enriching generative AI applications with insights from the psychological sciences may revolutionize our understanding of creativity and lead to increasing synergies in human–AI hybrid intelligent interfaces.

Generative artificial intelligence (AI) tools have made it easy to create realistic disinformation that is hard to detect by humans and may undermine public trust. Some approaches used for assessing the reliability of online information may no longer work in the AI age. We offer suggestions for how research can help to tackle the threats of AI-generated disinformation.

If mistakes are made in clinical settings, patients suffer. Artificial intelligence (AI) generally — and large language models specifically — are increasingly used in health settings, but the way that physicians use AI tools in this high-stakes environment depends on how information is delivered. AI toolmakers have a responsibility to present information in a way that minimizes harm.

Social media data enable insights into human behaviour. Researchers can access these data via platform-provided application programming interfaces (APIs), but these come with restrictive usage terms that mean studies cannot be reproduced or replicated. Platform-owned APIs hinder access, transparency and scientific knowledge.

We need human behavioural change to decarbonize our buildings. This requirement arises from our needs, lifestyle energy choices and interactions with buildings, and is an underexploited, yet essential demand-side opportunity for rapid and sustainable decarbonization. We propose a sufficiency-oriented approach that fosters equitable building decarbonization, while maintaining planetary boundaries.

On the basis of decades of cognitive science research into the nature of lexical concepts, we argue that gender categories that reflect the reality of the experiences of transgender people are more useful and cognitively natural than sex-based category definitions.

Hopelessness and despair threaten health and longevity. We urgently need strategies to counteract these effects and improve population health. Prosociality contributes to better mental and physical health for individuals, and for the communities in which they live. We propose that prosociality should be a public health priority.

The rise of generative AI requires a research agenda grounded in the African context to determine locally relevant strategies for its development and use. With a critical mass of evidence on the risks and benefits that generative AI poses to African societies, the scaled use of this new technology might help to reduce rising global inequities.

Progress in the burgeoning field of misinformation research requires some degree of consensus about what constitutes an effective intervention to combat misinformation. We differentiate between research designs that are used to evaluate interventions and recommend one that measures how well people discern between true and false content.

Effective HIV prevention and treatment are widely available, but services are underused and underdelivered. Behavioural economics offers insights into why this is and shows us cost-effective interventions to change behaviours. We call for investment in scaling up behavioural economics approaches to aid in progress towards ending HIV.

New medications that target biological mechanisms to address obesity, diabetes and related cardiometabolic conditions are widely popular. As not everyone is eligible, willing or able to take medications, structural and behavioural solutions remain essential to treat and decrease the risk of cardiometabolic diseases.

Off-task behaviours, such as media multitasking, are frequent in social science experiments and are especially common during online data collection. Such off-task behaviour can affect the quality of research data, making it crucial to understand the nature of this behaviour and to account for its influences.