Preserving Evidence, Empathy, and Trust in an AI Era
Preserving Evidence, Empathy, and Trust in an AI Era
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Artificial intelligence is rapidly reshaping healthcare, transforming how dietitians communicate with clients, document, develop education materials, manage workflows, and more. At the same time, national consumer research shows that people are trusting institutions and experts less, placing more confidence in AI tools for answers. The speed of AI adoption has raised ethical, practical, and professional questions for dietitians, and this shift represents a critical moment for our profession.
In this session, speakers will explore how dietitians can maintain and rebuild trust in an era where AI is impacting client expectations, health information, and clinical decision-making. We will share a balanced examination of AI's benefits, limitations, and ethical implications to help dietitians navigate and engage with AI tools intentionally and responsibly.
Through real-world case examples and facilitated discussion, attendees will learn how to leverage AI tools without compromising their credibility, ethics, or values. Attendees will leave with practical strategies and guardrails to navigate AI thoughtfully, communicate transparently, uphold evidence and empathy, and strengthen trust within the communities they serve.
CPEU: 1.50 (Valid Until September 15, 2029)
Learning Objectives
- Analyze how AI influences client expectations, information-seeking behaviors, and engagement in nutrition care, and apply strategies to maintain trust, credibility, and client-centered practice.
- Explain the ethical, regulatory, and professional considerations required for responsible AI use to reduce risk and ensure alignment with professional standards and evidence-based practice.
- Implement practical guidelines, safeguards, and decision-making frameworks to use AI responsibly, ethically, and effectively across clinical and non-clinical workflows.
Performance Indicators
- 1.3.2 Uses an ethical framework to guide decisions.
- 5.2.2 Understands impact of own values, beliefs and professional and personal biases on decision making.
- 6.3.5 Understands emerging technologies (e.g., AI, machine learning) and associated ethical considerations, including bias, data ownership, transparency, and the responsible use of data by healthcare professionals or clients.
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