Breaking bias: The role of artificial intelligence in improving clinical decision-making

As we incorporate artificial intelligence (AI) tools into clinical decision-making there are many potential benefits, including improved diagnostic accuracy and addressing human factors contributing to medical errors. For example, AI systems may support a real-time interpretation of medical imaging and assist clinicians in generating a differential diagnosis in ensuring that critical diagnoses are considered. However, it is vital to be aware of the potential pitfalls associated with the use of AI, such as automation bias, input data quality issues, limited clinician training in interpreting AI methods, and the legal and ethical considerations associated with their use.

We recently published a report drawing attention to the utility of AI clinical decision-support tools in overcoming human cognitive biases. The paper also emphasizes the importance of clinicians developing skills needed to steward the adoption of AI tools in healthcare and serve as patient advocates, ensuring safe and effective use of health data.