Bias & Equity - AI systems can reflect cultural bias in their design or data. How could this impact health equity and patient trust, especially in vulnerable or marginalized populations?
Artificial intelligence (AI) is increasingly embedded in healthcare systems, from language translation apps to clinical decision-support systems. While these tools hold promise for improving access and reducing health disparities, they also pose ethical concerns related to privacy, bias, cultural misinterpretation, and patient safety.
As nurses, we are expected to deliver care that culturally congruent, respectful, and consistent with the National CLAS Standards (National Standards for Culturally and Linguistically Appropriate Services) transcultural nursing frameworks presented in Transcultural Concepts in Nursing Care, 9th edition (Boyle, Collins, Ludwig-Beyer, & Andrews, 2025). This assignment will help you critically evaluate one AI tool’s potential role in transcultural nursing, weighing its benefits and limitations in light of theory, practice, and ethics. In this group discussion, you will explore how AI affects transcultural nursing care through critical reflection and peer exchange.
More resources
- [ ] (each student addresses one, providing a minimum of 2 scholarly references; 2 peer reviews, with a minimum of 1-2 scholarly references)
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