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Artificial Intelligence Resources for Admission and Selection Processes

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Principles for Responsible AI in Medical School and Residency Selection

Based on the AAMC's Principles for Responsible AI in Medical School and Residency Selection, the AAMC developed resources to support programs in putting these principles into practice. These tools help institutions determine AI readiness, evaluate vendors, and navigate key terminology for effectively integrating AI into their selection processes.

AI Resources for Medical Schools and Residency and Fellowship Programs

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Essential AI Terms and Definitions for Implementing AI in Selection

Gain a clear understanding of key AI terminology with this concise glossary, tailored for admissions and residency selection teams. This resource promotes seamless communication and informed decision-making throughout the AI implementation process.

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Guide to Assessing Your Institution’s Readiness for Implementing AI in Selection

Evaluate your institution's AI readiness with this comprehensive guide. Identify capabilities, gaps, and key team members. Foster collaborative discussions that build consensus on priorities and next steps for implementation.

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Guide to Evaluating Vendors on AI Capabilities and Offerings

Make informed decisions when selecting AI solutions with this structured guide. Compare vendors objectively using targeted questions and detailed rating scales. Tailor the process to your institution's priorities and needs.

Responsible AI in Medical School and Residency Selection
Guide to Leverage LLMs for AAMC Resources

Learn effective strategies for using large language models (LLMs) to better understand and implement the AAMC's AI toolkit for medical education selection.

Responsible AI in Medical School and Residency Selection
Guide to Navigating AI Use Cases in Medical Education Selection

Explore practical AI implementation scenarios for medical school and residency selection processes, with implementation steps and resource requirements.

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