Science, technology and society articles from across Nature Portfolio

Hybrid intelligence — arising from the sensible, targeted fusion of human minds and cutting-edge computational systems — holds great potential for enhancing the sustainability of agriculture. Leveraging the combined strengths of both collective human and artificial intelligence helps identify and stress-test pathways towards the reconciliation of biodiversity and productivity.

Researchers have a wide variety of choices when it comes to careers. Often, post-PhD, we leave academic research for industry. But it is also possible to transition back, when done carefully. In this how-to, I outline how to transition between industry and academic research and vice versa.

Given the increasing sophistication of virtual reality systems in providing immersive nature experiences, there is the potential for analogous health benefits to those that arise from real nature experiences. We call for research to better understand the human–nature–technology interaction to overcome potential pitfalls of the technology and design tailored virtual experiences that can deliver health outcomes and wellbeing across society.

Effectively engaging with large language models is becoming increasingly vital as they proliferate across research landscapes. This Comment presents a practical guide for understanding their capabilities and limitations, along with strategies for crafting well-structured queries, to extract maximum utility from these artificial intelligence tools.

From design-for-disassembly to urban mining, industrial ecology holds key insights for transitioning towards sustainable cities. Yet, its insights into the reuse of building materials remain largely underutilized in urban design and architectural practice.

Parents’ beliefs and behavior act as both explicit and implicit ways of communicating the value of science and their confidence that their child can be successful in science-related classes. Using the NCES High School Longitudinal Survey (HSLS:09), we examined how parent beliefs and behaviors regarding their 9th grader’s science education predicted the students’ motivation in science. Using multiple regression indicates that the combination of parental education, beliefs, and involvement in science-related activities with their child are weak but significant predictors of students’ academic motivation in science (adjR² = 0.04, F(6, 14,933) = 26.32, P < 0.001). In particular, parent education and parent involvement have positive and significant effects on students’ science identity and science self-efficacy. These findings suggest that students may have a stronger academic motivation in science with parents who have higher levels of education, more confidence in their ability to help their child in science, and who engage in more science activities with their child.