Table 1.

Sub-themes and exemplar quotes generated from analysing qualitative responses to focus group questions. We asked the following: ‘How will AI be applied to medicine in the future? & What would you like to learn about AI that might prepare you for a future in which AI plays an important part in medicine?’ We gathered data from 128 students through online surveys and focus groups carried out at the 69th IFMSA General Assembly in Rwanda, March 2020.

Sub-themes	Exemplar quotes
General Concepts	‘We should be taught a healthy skepticism for AI … All AI is not created equal, and garbage in = garbage out … we need to be given the knowledge and the tools to make this assessment.’ – Student from Australia ‘The basis of how AI operates, risks and sources of errors in AI … what can AI be used for, what are the limits? What hardware is needed?’ – Student from Germany ‘What limits and opportunities AI gives us … How can we use AI to do good, and not harm, as a tool.’ – Student from Norway
Applications in clinical medicine	‘monitoring ICU patient stats … predicting patient outcomes … use of machine learning in order to easily diagnose a patient through imaging … surgical planning and intra-operative guidance.’ – Student from Hong Kong ‘within Primary health care… triaging who needs what level of care, follow up on NCDs and other chronic illnesses … online consultations’ – Student from Sweden ‘detection of diseases at stages where they were previously undetected … to predict … arthritis in the next five years by looking at … MRIs’ – Student from Pakistan it has the potential to recruit massive populations for studies … shown in Apple Heart Study’ – Student from Ireland ‘how it can be used with precision’ – Student from Ethiopia
AI in LMIC	‘low- and middle-income countries should have access to technology first … Some regions still don't have access to internet’ – Student from Morocco ‘reach out to the majority of the community’ – Student from Ethiopia ‘I also think that AI will be used to increase healthcare access/reach in underserved populations …’ – Student from Australia
Patient Safety	‘reduce medical error … identifying … skin lesions etc.’ – Student from Ireland
Computer science	‘how to code … build AI health related algorithms’ – Student from Burkina Faso ‘how the algorithms are developed and trained to understand … the results, and also how to mitigate … bias.’ – Student from the UK ‘the methods used to develop AI algorithms … [to] critically think about the outputs.’ – Student from the United States ‘how the system integrates and works in the medical system’ – Student from India
Scepticism	‘It could be used for general diagnosis … but a health care worker (physician) will still always be required to assess the border line cases ….’ – Student from Iceland ‘to ensure that they do not unintentionally cause discrimination or worsening of health outcomes for vulnerable populations … There is great potential for good but also great potential for harm.’ – Student from Australia
Big Data	‘How to use technology to stock information, to organize data and to analyse it.’ – Student from Morocco