Learn what “Explainable AI” refers to in the context of artificial intelligence. Discover if it means AI that can speak multiple languages, teach complex subjects, justify decisions, or explain jokes and humor.
Table of Contents
Question
In the context of AI, what does the term “explainable AI” refer to?
A. AI that can speak multiple languages
B. AI that can teach complex subjects
C. AI systems that can justify their decisions to humans
D. AI that explains jokes and humor
Answer
C. AI systems that can justify their decisions to humans
Explanation
Explainable AI (XAI) is a crucial aspect of artificial intelligence focused on creating AI systems that can provide clear, understandable explanations for their decisions and actions. This transparency is essential for several reasons:
- Trust and Accountability: Users and stakeholders need to trust AI systems. If an AI can explain its decisions, it becomes easier to trust and hold it accountable.
- Debugging and Improvement: AI researchers and developers can identify and correct issues within AI systems more effectively if they can understand the reasoning behind AI decisions.
- Regulatory Compliance: Many industries, particularly those heavily regulated like finance and healthcare, require AI systems to be explainable to meet legal and ethical standards.
By ensuring AI systems can justify their decisions, explainable AI enhances the usability, reliability, and integration of AI technologies across various sectors.
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