Exploring the sense of responsibility regarding involving Artificial Intelligence in mammography interpretation

Prabhathi Basnayake1, Jocelyn Lippey1, Louise Keogh2, Helen Frazer3

1 St Vincent Institute for Medical Research and Melbourne School of Population and Global Health, University of Melbourne, Australia

2 Centre for Health EquityMelbourne School of Population and Global Health, University of Melbourne, Australia

3 St Vincent Hospital Melbourne and Melbourne School of Population and Global Health, University of Melbourne, Australia 


Background and purpose: There is a significant body of literature that has explored clinician’s perceptions of the use of artificial intelligence (AI) in health care (Laï et al. 2020; Sarwar et al.2019). In recent years, AI has been increasingly used in processes related to aspects of health care such as interpreting x-rays and mammograms and it’s adoption is often based on its capacity to reduce cost and improve health care outcomes (Shaheen, 2021). We explore the potential role of AI in mammography from the perspective of health care professionals currently involved in a population-based breast screening program in Melbourne, Australia.  

Method: We recruited health professionals working in BreastScreen Victoria and conducted 7 focus groups and interviews exploring their views of the potential role of AI in reading mammograms. Thematic analysis was employed to analyse data to determine the broad themes that emerged in the discussions. 

Results: 27 health care professionals participated in the focus groups and interviews. The analysis revealed overall support and enthusiasm about involving AI in general. Their concerns stemmed from limitations of AI programs that they are currently using and the risk it poses to their professional standards and safety and responsibility towards their patients. They raised ethical and medico-legal concerns with the involvement of AI such as accountability of error. Radiologists acknowledged the potential benefit of AI in freeing up time to engage in more patient centred communication processes.  

Conclusion: BreastScreen health professionals ranged from enthusiastic to hesitant on the use of AI for mammography. There was concern as to whether it could be implemented while also maintaining their duty of care to patients, professional responsibility, and high-quality work standards. This project demonstrates the importance of acknowledging the divide between opportunity and their lived experience of the use of AI in radiology and highlights the importance of continuous conversation and collaboration between radiology community about AI implementation in mammography. 


Laï, MC., Brian, M. & Mamzer, MF. Perceptions of artificial intelligence in healthcare: findings from a qualitative survey study among actors in France. J Transl Med 18, 14 (2020). https://doi.org/10.1186/s12967-019-02204-y

Mohammed Yousef Shaheen. AI in Healthcare: medical and socio-economic benefits and challenges. ScienceOpen Preprints. DOI: 10.14293/S2199-1006.1.SOR-.PPRQNI1.v1

Sarwar, S., Dent, A., Faust, K. et al. Physician perspectives on integration of artificial intelligence into diagnostic pathology. npj Digit. Med. 2, 28 (2019). https://doi.org/10.1038/s41746-019-0106-0