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AI-900: What is the Principle of Accountability in AI Governance?

Learn about the principle of accountability in AI governance and how it differs from transparency and privacy and security.

Table of Contents

Question

Designers and developers of Al solutions should adhere to a framework of governance and organizational principles and ensure that the solution meets ethical and legal standards. Which principle is that?

A. Transparency
B. Privacy and Security
C. Accountability

Answer

C. Accountability

Explanation

The correct answer is C. Accountability. This principle states that designers and developers of AI solutions should be responsible for the outcomes of their solutions and be able to explain how they work and why they make certain decisions. Accountability also implies that AI solutions should be subject to appropriate levels of oversight and regulation, and that any errors or harms caused by them should be remedied.

Transparency is another principle of AI governance, but it refers to the ability of AI solutions to provide clear and understandable information about their capabilities, limitations, and processes. Transparency helps users and stakeholders to trust and evaluate AI solutions, but it does not necessarily imply accountability.

Privacy and Security is also an important principle of AI governance, but it focuses on the protection of data and systems from unauthorized access, use, or disclosure. Privacy and Security ensures that AI solutions respect the rights and preferences of data subjects and comply with relevant laws and standards, but it does not directly address accountability.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump