ΑΙhub.org
 

Using artificial intelligence in health sciences education requires interdisciplinary collaboration and risk assessment


by
19 April 2022



share this:
stethoscope and laptop

By Elif Bilgic, McMaster University and Jason M. Harley, McGill University

Over the past five years, there has been an increase in research and development related to the use of artificial intelligence (AI) in health sciences education in fields such as medicine, nursing and occupational therapy. AI-enhanced technologies have been shown to have educational value and offer flexibility for students. For example, learning scenarios can be repeated and completed remotely, and educational experiences can be standardized.

However, AI’s applications in health sciences education need to be explored further.

To better understand advances in research and applications of AI as a part of the education of health sciences students, we conducted a comprehensive literature review. We also hosted a virtual panel consisting of scholars across Canadian institutions and educational technology companies who are actively involved in AI and health sciences education.

Our panel investigated three themes: current applications of educational theories, performance assessment, and current advances; the role of educational associations and industry; and legal and ethical considerations.

Interdisciplinary collaboration

One of our key findings was that it is important to develop interdisciplinary partnerships and collaborative environments. The effective development and implementation of AI-enhanced educational technologies require different capabilities. These include: possessing the technical know-how required to build and develop AI, understanding the needs of students and educators, applying educational theories to content development and assessment, and considering any legal and ethical issues.

Based on our work, majority of the published studies do not have interdisciplinary teams, hence the call for interdisciplinary collaborations. However, one example that was successful in bringing together individuals from different disciplines is an intelligent tutoring system designed to help medical students with their diagnostic reasoning skills through virtual patient cases.

Therefore, an interdisciplinary team would be able to produce and deliver AI-enhanced education effectively. To achieve this, partnerships should include industry, educational societies, hospitals and universities. Collaborative teams would include researchers and practitioners from health sciences, law, ethics, education, computer science, engineering and other fields.

Enhancing education with educational societies

Educational societies not only play an important role in supporting research and development, but also the use of AI-enhanced educational technologies across health sciences programs.

Future health scientists will require new skills in technology and AI, and the ability to apply them during training and clinical duties. These include understanding issues related to privacy, discrimination, ethical and legal concerns and inherent biases that may create health inequities.

For example, the Royal College of Physicians and Surgeons of Canada, which oversees the training of medical specialists in Canada, has a role in creating new initiatives and support systems to address these emerging needs. The college could add an additional component to the medical curriculum that focuses on core information necessary to use these AI-enhanced technologies. Practising physicians will also need the support of the college to develop technology-supported clinical skills.

Ultimately, if we want to enhance research and applications of AI in health sciences education, collaboration across different fields is key. This is so that both effective and equitable AI technologies can be developed, and that in the future, health scientists can use these technologies while understand their risks and benefits.The Conversation

Elif Bilgic, Assistant Professor, Pediatrics, McMaster University and Jason M. Harley, Assistant Professor, Medicine and Health Sciences, McGill University

This article is republished from The Conversation under a Creative Commons license. Read the original article.




The Conversation is an independent source of news and views, sourced from the academic and research community and delivered direct to the public.
The Conversation is an independent source of news and views, sourced from the academic and research community and delivered direct to the public.




            AIhub is supported by:


Related posts :



Generative AI is already being used in journalism – here’s how people feel about it

  21 Feb 2025
New report draws on three years of interviews and focus group research into generative AI and journalism

Charlotte Bunne on developing AI-based diagnostic tools

  20 Feb 2025
To advance modern medicine, EPFL researchers are developing AI-based diagnostic tools. Their goal is to predict the best treatment a patient should receive.

What’s coming up at #AAAI2025?

  19 Feb 2025
Find out what's on the programme at the 39th Annual AAAI Conference on Artificial Intelligence

An introduction to science communication at #AAAI2025

  18 Feb 2025
Find out more about our forthcoming training session at AAAI on 26 February 2025.

The Good Robot podcast: Critiquing tech through comedy with Laura Allcorn

  17 Feb 2025
Eleanor and Kerry chat to Laura Allcorn about how she pairs humour and entertainment with participatory public engagement to raise awareness of AI use cases

Interview with Kayla Boggess: Explainable AI for more accessible and understandable technologies

  14 Feb 2025
Hear from Doctoral Consortium participant Kayla about her work focussed on explanations for multi-agent reinforcement learning, and human-centric explanations.

The Machine Ethics podcast: Running faster with Enrico Panai

This episode, Ben chats to Enrico Panai about different aspects of AI ethics.

Diffusion model predicts 3D genomic structures

  12 Feb 2025
A new approach predicts how a specific DNA sequence will arrange itself in the cell nucleus.




AIhub is supported by:






©2024 - Association for the Understanding of Artificial Intelligence


 












©2021 - ROBOTS Association