Learn how the principle of Transparency in responsible AI ensures users understand the limitations and testing of AI applications. Explore its role in building trust and ethical AI systems.
Table of Contents
Question
The Root, a gardening store, is exploring how they can use machine learning to build an application.
They want to publish this application, but they also want to include documentation to make sure users understand its limitations and how it was tested.
Which principle of responsible Al is The Root following?
A. Accountability
B. Inclusiveness
C. Reliability and Safety
D. Transparency
Answer
D. Transparency
Explanation
Transparency is a core principle of responsible AI that ensures users can understand how an AI system works, including its limitations, decision-making processes, and testing methods. By providing clear documentation and explanations, organizations like The Root can foster trust and accountability in their AI applications. Transparency enables stakeholders to evaluate the system’s reliability, identify potential biases, and make informed decisions about its use.
In the context of The Root’s gardening store, their focus on publishing documentation about the application’s limitations and testing aligns directly with the principle of transparency. This practice ensures that users are aware of how the application operates, its constraints, and the processes involved in its development.
Why Not Other Options?
A. Accountability: While accountability involves ensuring those responsible for AI systems take ownership of their outcomes, it does not specifically address providing documentation or explaining system limitations.
B. Inclusiveness: Inclusiveness focuses on designing AI systems that are accessible and beneficial to diverse groups of people but does not emphasize explaining limitations or testing.
C. Reliability and Safety: This principle ensures that AI systems operate safely and consistently but does not involve making the system’s limitations explicitly understandable to users.
Transparency is essential for ethical AI practices as it promotes trust, reduces misuse, and helps users make informed decisions about the technology they interact with.
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