Towards better healthcare: What could and should be automated?

•First study to combine automatability and desirability of work automation into a single model.•First comprehensive quantitative evidence of healthcare practitioners’ preferences regarding the automation of their work activities.•Quantitative evidence based on the combination of two Bayesian machine learning methods, for precise estimates and quantification of model uncertainty.•Summary of results in a succinct four-quadrant model to facilitate policy making of governments and strategic guidance of organizations.•Healthcare professionals desire a surprisingly high proportion of their own work activities to be fully automated, while being less optimistic about the current automation potential than technical experts.•Significant correlation between automatability and desirability of automation of work activities. While artificial intelligence (AI) and other automation technologies might lead to enormous progress in healthcare, they may also have undesirable consequences for people working in the field. In this interdisciplinary study, we capture empirical evidence of not only what healthcare work could be automated using current technology, but also what should be automated. We investigate these research questions by utilizing probabilistic machine learning models trained on thousands of expert ratings, provided by both healthcare practitioners and automation experts. To the best of our knowledge, the present study is the first to analyze the desirability of automating healthcare work activities (human workforce preferences) in combination with current technological capabilities. We present a succinct four quadrant model, the Automatability-Desirability Matrix, based on our findings. It can be used to support policymakers and organizational leaders in developing practical strategies on how to harness the positive power of AI, while accompanying change and empowering stakeholders in a participatory fashion. Furthermore, we observe that healthcare professionals desire a surprisingly high proportion of their work activities to be fully automated, while being less optimistic about the current automation potential of healthcare work than technical experts. Our results represent the first detailed quantitative empirical evidence of healthcare practitioners’ preferences regarding the automation of work and the first direct comparison of the potential for automation as based on the perspectives of technical experts and those working as healthcare practitioners.