Discover the importance of explainable AI systems that enable everyday users to understand how and why predictions and recommendations are made, without requiring specialized AI training.
Table of Contents
Question
Which of the following describes an AI system, that everyday people, who do not have any special training in AI, can understand how and why the system came to a particular prediction or recommendation?
A. Transparent
B. Interpretable
C. Understandable
D. Explainable
Answer
D. Explainable
Explanation
An AI system is explainable when anyone can understand and follow how the system makes a prediction. Being able to understand how and why AI systems make predictions and recommendations is key to users trusting AI.
An explainable AI system is designed to provide clear, understandable explanations for its predictions or recommendations, making it accessible to everyday people who do not have specialized training in artificial intelligence.
Explainable AI is crucial for building trust and confidence in AI systems, as it allows users to comprehend the reasoning behind the system’s outputs. This transparency helps to demystify the AI decision-making process and ensures that the system’s actions can be interpreted and validated by a wide range of users.
While terms like “transparent,” “interpretable,” and “understandable” are related to the concept of explainable AI, they do not fully capture the essence of an AI system that can be easily understood by the general public. Explainable AI goes beyond mere transparency or interpretability, focusing on providing clear, accessible explanations that can be grasped by users with varying levels of technical expertise.
By prioritizing explainable AI, organizations can foster greater trust and adoption of AI technologies, as users feel more comfortable and confident in the systems they interact with daily.
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