A truly explainable AI (XAI) requires knowledge discovery methods that are machine-usable and explainable to __________ or even __________.a.a domain expert, a laypersonb.a layperson and developers of applicationc.European Union framework, a laypersond.law , a layperson

Q.No.3. Explainable AI (XAI) techniques aim to make machine learning models more ____

Explain an application or use-case of AI that fascinates YOU.It may or may not be something that is mentioned in the course.5 pointsYour answer cannot be more than 10000 characters.

Ask AI to explain concepts

Which of the following is not an examples of explainable AI?A.Provides the best solution for environment and climate changeB.Used in diagnosing diseases or suggesting treatment options by helping physicians understand the basis of their recommendationsC.Plays a crucial role in financial decision-making, providing transparency and facilitating trust among stakeholdersD.Assists in understanding the decisions made by AI, contributing to improved safety and reliability in autonomous vehiclesE.Offer personalized learning paths, helping educators understand how AI analyzes students' performance and learning styles

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.