Monday, June 10, 2024

AI’s Ethical Footprint in CME

By: Milini Mingo, MPA, CHCP

The Landscape of AI in Continuing Education

The introduction of artificial intelligence (AI) into continuing education (CE) represents a technological and pedagogical shift for learners in the medical field. This shift introduces a new pathway for learning by making education more accessible and engaging than ever.¹ As AI enhances the efficiency of learning, it also brings to the forefront the need to address ethical concerns.² ³

Ethical Dilemmas in AI-driven CE

The integration of AI into CE raises several ethical considerations that need to be addressed to fully harness its potential while ensuring the integrity and fairness of educational outcomes. Some ethical considerations include, but are not limited to:

Error vs. Accuracy: Even though AI can quickly process and analyze big data, its susceptibility to errors is concerning.⁴ The balance between the innovative potential of AI and the critical need for accuracy, especially in medical education where the stakes are high, necessitates a rigorous vetting process that can minimize the risk of misinformation.⁵ ⁶
Reinforcement and Confirmation of Bias: In the technology world, there is a proverb that states, “Garbage In, Garbage Out”. This simple adage means that any low-quality data output is the direct result of low-quality input.⁷ AI systems acquire their knowledge from datasets. Therefore, if the AI output contains inherent biases, then the original input was biased. This leads to the reinforcement of bias in educational content and outcomes.⁸ Especially in the field of CE, in which diverse and equitable learning environments are crucial, this issue is particularly problematic.

Regulatory Frameworks for AI Ethics in Healthcare Education

The integration of AI in healthcare education calls for an ethical framework spanning from global to local levels. This new frontier is shaped by international guidelines and the efforts of professional bodies to align AI advancements with medical ethics.

Global Standards and Guidelines

AI in healthcare education has started a global conversation regarding ethics that has led to the development of various regulatory frameworks to safeguard the integrity of medical education. Internationally, organizations such as the World Health Organization (WHO) and the United Nations Educational, Scientific and Cultural Organization (UNESCO) have been instrumental in setting benchmarks for AI ethics in healthcare education. These benchmarks guide the integration of AI in a manner that respects ethical standards and promotes equity and fairness.⁹ ¹⁰ Additionally, global agreements and initiatives have been established to ensure that advancements in AI technology benefit all stakeholders equitably.¹¹

National Regulatory Oversight

Nationally, U.S. governmental agencies like the Food and Drug Administration (FDA) and the Department of Health and Human Services (HHS), bolstered by the White House's Executive Order on the Safe, Secure and Trustworthy Development and Use of Artificial Intelligence, have taken the lead in establishing and enforcing AI ethics regulations within medical education.¹² ¹³ ¹⁴ These agencies vet AI applications in healthcare to ensure they meet stringent ethical standards. This collective national governance works to ensure AI's benefits are maximized without compromising ethical values.

Professional Bodies and Accreditation Agencies

Many medical associations and accreditation bodies worldwide are diligently working to align AI integration with the core values of medical professionalism. For example, the American Medical Association created a policy and a framework to provide guidance on ethical AI use in healthcare education.¹⁶ ¹⁷ However, this endeavor is not without its challenges. The task of harmonizing professional ethics with the rapidly evolving capabilities of AI in educational settings presents both hurdles and opportunities for innovation in medical education.

What Is the Future of AI in Continuing Education?

AI's application to CE brings with it a host of ethical considerations. As AI continues to evolve, so should the regulation models that govern its use in healthcare education.¹⁸ The responsibility lies with educational institutions, healthcare organizations and regulatory bodies to ensure that AI enhances educational outcomes without compromising ethical standards.¹⁹ Standards established by these entities will offer a blueprint for the responsible integration of AI technologies and protection against potential ethical pitfalls.²⁰

Almanac Community Discussion: What are you (or your organization) doing to leverage AI for your learners while also addressing the accuracy and bias dilemmas discussed in Milini Mingo’s article, “AI’s Ethical Footprint in CME”? Join the discussion in the Almanac Community.

The use of Generative AI is acceptable for Almanac publications. This article used GenAI to organize references, develop the idea and check grammar.

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Milini Mingo brings years of experience in CE, with a focus on adult learning, program development and accreditation. Her insights aim to guide newcomers in navigating the complexities and opportunities of the CE profession.