Statistics from Altmetric.com
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.
How do we teach medical students to protect patients? My initial reaction to the question posed by Taylor and Goodwin was like first glimpsing ‘Jaws’: we’re going to need a bigger boat. The authors’ answer makes two important claims: first, that safety should be ethically sourced by better integration between teaching of safety and ethics; second, that teaching should encourage students to think about organisational failure rather than focusing on individual blame and personal responsibility to whistleblow.1
On the first, they highlight how ethics teaching often sits apart from that on safety. For the second, they use the concept normalisation of deviance, with its contained idea of structural secrecy, to depict organisational failure that is argued as largely immune to whistleblowing.
Why wouldn’t these challenges warrant a bigger boat? On their first claim: it is not just for safety, but throughout the curriculum that ethics teaching needs to be integral. Given coming challenges, it should become the cake rather than the icing. Consider, for example, that artificial intelligence (AI) stands to transform many knowledge-based professions, medicine among them. Tomorrow’s doctors will have a surfeit of data and automated decision aids at their fingertips. So, as far as they remain necessary, doctors will …
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Provenance and peer review Commissioned; internally peer reviewed.
Read the full text or download the PDF:
Other content recommended for you
- Biased intelligence: on the subjectivity of digital objectivity
- Ethical issues in computational pathology
- Artificial intelligence (AI) and global health: how can AI contribute to health in resource-poor settings?
- Medicine and the rise of the robots: a qualitative review of recent advances of artificial intelligence in health
- Before and beyond trust: reliance in medical AI
- Use of artificial intelligence in imaging in rheumatology – current status and future perspectives
- Public perceptions on the application of artificial intelligence in healthcare: a qualitative meta-synthesis
- Artificial intelligence projects in healthcare: 10 practical tips for success in a clinical environment
- Use of artificial intelligence for image analysis in breast cancer screening programmes: systematic review of test accuracy
- Urban monitoring, evaluation and application of COVID-19 listed vaccine effectiveness: a health code blockchain study