Discover the essential AI characteristics doctors rely on when utilizing artificial intelligence for medical diagnosis. Gain insights from an IBM AI Fundamentals Exam expert to enhance your understanding and advance your career.
Table of Contents
Question
When doctors use AI to help make a medical diagnosis, it is important that the AI has which of the following?
Select the two that apply.
A. Indexability
B. Examinability
C. Interpretability
D. Explainability
Answer
When doctors use AI to help make a medical diagnosis, it is crucial that the AI possesses the following two attributes:
C. Interpretability
D. Explainability
Explanation
Interpretability and explainability are vital for AI systems used in medical diagnosis because they enable doctors to understand how the AI arrived at its conclusions and recommendations.
Interpretability refers to the ability to comprehend the internal workings and decision-making processes of an AI system. In the context of medical diagnosis, interpretability allows doctors to grasp the factors and reasoning behind the AI’s suggestions. This understanding is essential for doctors to assess the validity and reliability of the AI’s output and to integrate it with their own expertise and judgment.
Explainability goes hand in hand with interpretability and involves the AI system’s capacity to provide clear, understandable explanations for its decisions and recommendations. An explainable AI system can articulate the key features, patterns, and relationships it identified in the patient’s data that led to its diagnostic suggestions. This transparency helps doctors to evaluate the AI’s reasoning, identify potential biases or limitations, and make informed decisions about the patient’s care.
Having interpretable and explainable AI systems in medical diagnosis is crucial for several reasons:
- Trust and confidence: Doctors can trust and have confidence in the AI’s recommendations when they understand how the system arrived at its conclusions.
- Accountability and responsibility: Interpretability and explainability enable doctors to take responsibility for the final diagnosis and treatment decisions, as they can assess the AI’s reasoning and integrate it with their own expertise.
- Collaboration and communication: Clear explanations facilitate effective collaboration between doctors and AI systems, as well as improved communication with patients about the diagnostic process and treatment plans.
- Continuous improvement: Understanding how the AI system works allows for the identification of potential flaws, biases, or areas for improvement, leading to the development of more accurate and reliable AI tools for medical diagnosis.
In summary, interpretability and explainability are essential attributes for AI systems used in medical diagnosis. These characteristics empower doctors to understand, evaluate, and effectively utilize AI recommendations, ultimately leading to better patient care and outcomes.
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