To provide equitable and culturally safe care that is free from discrimination, it is essential for nurses to understand how personal attributes and societal contexts influence patient outcomes. Because AI systems have learned from historical data that reflects past discrimination and bias, inherent bias can exist within AI data sets and algorithms. This may impact patient care by resulting in the perpetuation rather than the elimination of bias.
Through continuous education in determinants of health, cultural safety, cultural humility and anti-racism, nurses can identify inherent issues with the use of AI and make reasonable efforts to address such biases when working with diverse communities, including Indigenous Peoples and equity-deserving groups. When using AI in practice, nurses need to be aware of and use caution in interpreting content/output by taking into consideration patient demographics and contextual factors to inform decisions and next steps.
When considering the use of AI in your practice, reflect on:
- Have I accounted for potential bias of the data produced by AI? How do I report suspected biases?
- Where could there be biases in the data? Can I determine if the data represents current demographics and perspectives?
- What can I learn about data bias in AI so I can be aware of possible historical or social inequities?
- Have I considered the practice context and if the use of AI is appropriate?
- Who will be impacted by the AI? How will they be impacted? Who’s and what interests are represented and how?
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