AWS Certified AI PractitionerResponsible AIMedium
A startup is developing an AI-powered chatbot for mental health support. Given the sensitive nature of the data and the potential for harm, they are establishing a framework to clearly define who is responsible for model errors, data breaches, or unintended negative consequences. Which Responsible AI concept are they primarily focusing on?
- ASafety
- BPrivacy
- CTransparency
- DAccountability
Show answer & explanationAnswer & explanation
Correct answer: D. Accountability
Defining 'who is responsible for model errors, data breaches, or unintended negative consequences' directly aligns with the concept of accountability in Responsible AI, which establishes clear ownership and responsibility for AI system outcomes.
Why the other options are wrong
- A. Safety aims to prevent harm from the AI's operation, but accountability defines who is responsible when harm occurs.
- B. Privacy deals with protecting sensitive data, while accountability deals with consequences of breaches or other failures.
- C. Transparency focuses on understanding how the AI works, not assigning responsibility for its effects.
AI Accountability
AI accountability involves establishing clear responsibility for the design, development, deployment, and outcomes of AI systems, especially in cases of error, harm, or misuse.
- Crucial for trust and legal compliance.
- Requires clear governance structures.
- Encompasses both technical and ethical considerations.
Memory trick: A.C.T. F.A.I.R. AI