Submitted by Marianna Shershneva on

Masters K. Ethical use of artificial intelligence in health professions education: AMEE Guide No. 158. Med Teach. 2023;45(6):574-584.

Abstract

Health Professions Education (HPE) has benefitted from the advances in Artificial Intelligence (AI) and is set to benefit more in the future. Just as any technological advance opens discussions about ethics, so the implications of AI for HPE ethics need to be identified, anticipated, and accommodated so that HPE can utilise AI without compromising crucial ethical principles. Rather than focussing on AI technology, this Guide focuses on the ethical issues likely to face HPE teachers and administrators as they encounter and use AI systems in their teaching environment. While many of the ethical principles may be familiar to readers in other contexts, they will be viewed in light of AI, and some unfamiliar issues will be introduced. They include data gathering, anonymity, privacy, consent, data ownership, security, bias, transparency, responsibility, autonomy, and beneficence. In the Guide, each topic explains the concept and its importance and gives some indication of how to cope with its complexities. Ideas are drawn from personal experience and the relevant literature. In most topics, further reading is suggested so that readers may further explore the concepts at their leisure. The aim is for HPE teachers and decision-makers at all levels to be alert to these issues and to take proactive action to be prepared to deal with the ethical problems and opportunities that AI usage presents to HPE.

Questions

  1. What was the most important insight or new understanding you gained from this article about the ethical use of AI in health professions education? How might it influence your future teaching or institutional practices?
  2. How important is it for educators to understand how AI algorithms work before integrating them into curriculum or assessment practices? What level of transparency is ethically necessary?
  3. The article suggests that AI may challenge or even reshape human ethical frameworks. What are the implications of this possibility for health professions education and how should educators prepare?

Comments

Emil Mosley replied on

I would prioritize platforms that clearly explain how data is collected and used, and I would communicate geometry dash lite details openly to students. Institutionally, I believe policies must be developed proactively rather than reactively, ensuring that privacy, fairness, and equity are built into AI adoption strategies from the start.
 

Emil Mosley replied on

Chester Coffey replied on

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Chester Coffey replied on

cakorib cakorib replied on

one takeaway for me is that “transparency” in ai for hpe isn’t a single switch; it’s about being clear on purpose, data provenance, and who is accountable when outputs are wrong. i don’t think every educator needs to understand the math, but we do need enough literacy to ask what data trained it, what biases were tested, and what evidence supports its use in assessment. in practice i’d push for an ai use statement in every course and a human-override pathway for any ai-supported decision affecting progression. i’ve also seen how easy it is for irrelevant links to creep into student-facing spaces, and i had to remove https://indianrespin.com/casinos/ from a resource list because it undermined trust in the rest of our guidance.

cakorib cakorib replied on

Jeffree Star replied on

 

This article highlights how AI in health professions education brings not only innovation but also complex ethical responsibilities, especially around privacy, bias, and data ownership. It’s a good reminder that educators must be proactive and transparent when integrating AI into teaching. Just like in games such as Golf Hit, where strategy and control matter, using AI effectively also requires thoughtful decision-making to achieve the best outcomes without compromising integrity.

Jeffree Star replied on