AWS Certified AI PractitionerResponsible AIMedium
A smart city initiative is deploying AI-powered surveillance cameras for public safety. While the system promises to reduce crime rates, concerns have been raised by privacy advocates about the continuous collection of facial recognition data in public spaces and potential misuse of this information. To address these concerns, the project team is investigating techniques like federated learning and differential privacy. Which Responsible AI concept are they primarily focusing on?
- AAI fairness
- BAI interpretability
- CAI privacy
- DAI accountability
Show answer & explanationAnswer & explanation
Correct answer: C. AI privacy
The use of techniques like federated learning and differential privacy, in response to concerns about facial recognition data collection, directly addresses AI privacy by protecting sensitive information.
Why the other options are wrong
- A. AI fairness concerns equitable outcomes, not data protection from surveillance.
- B. AI interpretability is about understanding model decisions, not safeguarding collected data.
- D. AI accountability is about assigning responsibility, not technical data protection methods.
AI Privacy
AI privacy involves designing and implementing AI systems in a way that respects and protects individuals' personal and sensitive data throughout its lifecycle.
- Crucial for sensitive applications like surveillance or healthcare.
- Techniques include federated learning, differential privacy, and anonymization.
- Aims to prevent unauthorized access, use, or disclosure of data.
Memory trick: Keep AI's eyes confidential.