Microsoft Azure AI Fundamentals (AI-900)Describe AI workloads and considerationsMedium
A company is developing an AI-powered recruitment platform that uses facial recognition to assess candidate engagement during video interviews. To ensure that the system does not produce biased outcomes due to variations in lighting, skin tone, or facial features across different candidates, which Responsible AI principle should be prioritized?
- AInclusiveness
- BAccountability
- CTransparency
- DPrivacy and Security
Show answer & explanationAnswer & explanation
Correct answer: A. Inclusiveness
Inclusiveness ensures that AI systems are designed to be accessible and usable by the widest possible range of people, considering diverse backgrounds, abilities, and characteristics. Addressing variations in facial recognition across different individuals directly aligns with this principle.
Why the other options are wrong
- B. Accountability deals with assigning responsibility for AI outcomes, not the technical performance across diverse users.
- C. Transparency is about understanding how the AI works, not ensuring its equitable performance for all users.
- D. Privacy and Security focuses on data protection, not ensuring the system works equally well for diverse faces.
Responsible AI: Inclusiveness
The principle that AI systems should empower everyone, engage people, and consider the diverse needs and characteristics of all users.
- Aims to make AI accessible and usable by a wide range of people.
- Addresses issues like varying abilities, backgrounds, and physical characteristics.
- Promotes equitable access and experience for diverse user groups.
Memory trick: AI should INCLUDE everyone, like a big, welcoming circle.