Say you are building an AI system to help make diagnoses from X-ray scans. Which of the following statements about explainability of AI do you agree with?1 pointLack of explainability can hamper users’ willingness to trust and adopt an AI system.Explainability is usually achieved through building a chatbot to talk to the user to explain its outputs.Most AI systems are highly explainable, meaning that it’s easy for a doctor to figure out why an AI system gave a particular diagnosis.AI systems are intrinsically “black box” and cannot give any explanation for their outputs.
Question
Say you are building an AI system to help make diagnoses from X-ray scans. Which of the following statements about explainability of AI do you agree with?1 pointLack of explainability can hamper users’ willingness to trust and adopt an AI system.Explainability is usually achieved through building a chatbot to talk to the user to explain its outputs.Most AI systems are highly explainable, meaning that it’s easy for a doctor to figure out why an AI system gave a particular diagnosis.AI systems are intrinsically “black box” and cannot give any explanation for their outputs.
Solution
The statement I agree with is: "Lack of explainability can hamper users’ willingness to trust and adopt an AI system."
Explainability in AI is crucial, especially in sensitive fields like healthcare. If an AI system can't explain how it arrived at a particular diagnosis, it can be difficult for doctors to trust its judgment. This lack of trust can hinder the adoption of such systems.
The other statements are not entirely accurate. Explainability is not usually achieved through building a chatbot. While a chatbot can be used to communicate the AI's outputs, the explainability itself comes from the design of the AI system.
Also, it's not true that most AI systems are highly explainable. Many advanced AI systems, like deep learning models, are often referred to as "black boxes" because their internal workings are not easily understandable.
Lastly, while some AI systems can be difficult to interpret, it's not accurate to say that AI systems are intrinsically "black box" and
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