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    Provide Equitable Access to AI

    AI holds great potential for medical education and will be even more effective if used in a way that promotes equity and inclusivity. All learners need equal opportunities to realize the benefits of AI tools in their education. Institutions should ensure similar access for learners to avoid widening the opportunity gaps between learners from different socioeconomic and technical expertise backgrounds. However, it is important to acknowledge that institutions have unequal access to AI tools and resources, potentially widening the technology gap.

    With thoughtful implementation, AI can help augment the learning process and provide more personalized learning to meet the needs of individual learners. To address equity and innovation at the institutional level, institutions could partner to codevelop and assess capabilities. It is critical that the community collaborates to leverage AI in a way that promotes equity in education and health care, to ensure AI is used in the service of optimizing the delivery of high-quality patient care.

    The output of an AI tool is shaped by the data used to train it. Therefore, when there is bias in the data, AI has the potential to perpetuate that bias and contribute to inequity in learning and in health care. When AI is used as an educational tool, educators need to be mindful of potential bias within the datasets used for education and training. When AI is used for learner assessment, it should be monitored to avoid perpetuating educational disparities.

    From Principle to Practice 

    Apply this principle to your practice using the following strategies: 

    • Address equity through education and training. Provide education and training to educators, staff, and learners that increases awareness about the risks to equity posed by AI tools. Provide guidance about how to employ AI in ways that can help mitigate bias.
    • Engage learners in the process. Learners should be involved in the implementation and monitoring of AI tools being used in the learning environment. To mitigate potential disparities and ensure innovative practices are achieved, learner input should be invited in the development process. Coproduction with learners, particularly those with specialized interest in AI tool development, might be appropriate in some settings and conditions.
    • Ensure equitable access for all learners and educators. Institutions should be mindful of learner and educator access to AI tools. Institutions should consider addressing financial barriers to access through institutional sponsorship or financial assistance. Educators, staff, and learners bring differing technological experiences, and institutions should consider providing education and training to lower the threshold for successful engagement with AI tools. In addition, institutions should consider partnering to share experiences and resources. This can lessen the burdens, improve the benefit for all, and help minimize differences in access to AI tools across institutions.
    • Adapt to learner needs. AI has tremendous potential through its multimodal capabilities to provide precision medical education (i.e., the right educational intervention to the right learner at the right time). By effectively employing AI tools, educators can better meet the needs of individual learners and promote equity in the learning process.
    • Monitor the process and outcomes. The use of AI requires vigilant monitoring of its performance and impact on learning processes and outcomes. Recognizing the potential for bias in the data used for education and training, the output of AI needs to be monitored to prevent perpetuations of this bias. As with any tool, educators should monitor AI’s impacts to ensure it is meeting the intended goals. Refer to the Monitor and Evaluate principle for more information.

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