When AI Goes Wild: The Unspoken Challenges Facing Modern American Medicine (Top 3 Favorites)

CME Credit Available:

This activity offers 0.50 1A AOA

Important: CME credit for lectures included in this package cannot be claimed more than once. If you previously claimed CME credit for any of these lectures through attendance at ACOI2025, either online or in person, you are not eligible to claim credit for those lectures again.

Note: ACOI reports credits to the AOA at the beginning of each month.

Learning Objectives:

In this session, you'll learn how to:

• Identify the three foundational flaws—bias, generalizability, and opacity—that create a "cracked foundation" for medical AI.
• Discuss how the legal concept of the "standard of care" is being disrupted, creating a "legal double bind" for clinicians who can be sued for both using and not using AI.
• List and explain the key actions a frontline clinician should take to mitigate personal and professional risk, such as interrogating vendor data, documenting clinical dissent, and engaging with institutional leadership and liability insurers.

Conflict of Interest Disclosures:

ACOI requires each planner and presenter to identify all conflicts of interest and mitigates risk of bias using a series of strategies for relevant conflicts. Unless otherwise noted below, the ACOI, ACOI staff and planners for this activity have no relevant financial relationships with ineligible companies to disclose.

Stephen J. Ruffenach, DO, MS, FACOI, faculty for this activity, has no relevant relationships with ineligible companies to disclose. 

Release & Review Date:

This activity is valid from January 1, 2026, until January 1, 2029.