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Artificial intelligence (AI) has been heralded as one of the key technological innovations of the 21st century. Within healthcare, much attention has been placed upon the ability of deductive AI systems to analyse large datasets to find patterns that would be unfeasible to program. Generative AI, including generative adversarial networks, are a newer type of machine learning that functions to create fake data after learning the properties of real data. Artificially generated patient data has the potential to revolutionise clinical research and protect patient privacy. Using novel techniques, it is increasingly possible to fully anonymise datasets to the point where no datapoint is traceable to any real individual. This can be used to expand and balance datasets as well as to replace the use of real patient data in certain contexts. This paper focuses upon three key uses of synthetic data: clinical research, data privacy and medical education. We also highlight ethical and practical concerns that require consideration.

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Purpose Understanding the factors that influence prosocial behaviour during the COVID-19 pandemic is essential due to the disruption to healthcare provision. Methods We conducted an in-depth, mixed-methods cross-sectional survey, from 2 May 2020 to 15 June 2020, of medical students at medical schools in the United Kingdom. Data analysis was informed by Latané and Darley’s theory of prosocial behaviour during an emergency. Results A total of 1145 medical students from 36 medical schools responded. Although 947 (82.7%) of students were willing to volunteer, only 391 (34.3%) had volunteered. Of the students, 92.7% understood they may be asked to volunteer; however, we found deciding one’s responsibility to volunteer was mitigated by a complex interaction between the interests of others and self-interest. Further, concerns revolving around professional role boundaries influenced students’ decisions over whether they had the required skills and knowledge. Conclusion We propose two additional domains to Latané and Darley’s theory that medical students consider before making their final decision to volunteer: ‘logistics’ and ‘safety’. We highlight modifiable barriers to prosocial behaviour and provide suggestions regarding how the conceptual framework can be operationalized within educational strategies to address these barriers. Optimizing the process of volunteering can aid healthcare provision and may facilitate a safer volunteering process. Key messages  What is already known on this topic:  There is a discrepancy between the number of students willing to volunteer during pandemics and disasters, and those who actually volunteer. Understanding the factors that influence prosocial behaviour during the current COVID-19 pandemic and future pandemics and disasters is essential. What this study adds:  We expanded on Latané and Darley’s theory of prosocial behaviour in an emergency and used this to conceptualize students’ motivations to volunteer, highlighting a number of modifiable barriers to prosocial behaviour during the COVID-19 pandemic. How this study might affect research, practice, or policy:  We provide suggestions regarding how the conceptual framework can be operationalized to support prosocial behaviours during emergencies for the ongoing COVID-19 pandemic and future crises.