Microsoft Azure AI Fundamentals (AI-900)Describe AI workloads and considerationsEasy
An e-commerce company is developing an AI-powered recommendation engine that suggests products to customers based on their past purchases and browsing history. The company is concerned that the AI might inadvertently reinforce existing biases in the data, leading to a narrow range of recommendations for certain demographic groups. Which Responsible AI guiding principle is most relevant to address this concern?
- AFairness
- BReliability and Safety
- CAccountability
- DInclusiveness
Show answer & explanationAnswer & explanation
Correct answer: A. Fairness
The concern about the AI reinforcing existing biases and leading to a narrow range of recommendations for certain demographic groups directly relates to the principle of Fairness, which aims to ensure AI systems treat all people equitably.
Why the other options are wrong
- B. Reliability and Safety focuses on the AI system performing as intended without harm, not bias in recommendations.
- C. Accountability refers to establishing responsibility for AI system outcomes, not the elimination of bias itself.
- D. Inclusiveness ensures AI systems empower everyone and engage diverse perspectives, but Fairness specifically targets bias in outcomes.
Responsible AI: Fairness
Fairness in Responsible AI means that AI systems should treat all people equitably and not discriminate against individuals or groups based on sensitive attributes.
- Aims to prevent AI systems from perpetuating or amplifying societal biases.
- Involves ensuring equitable outcomes and representation across different user groups.
- Requires careful data selection, model design, and bias detection/mitigation techniques.
Memory trick: F.I.T.R.A.P. - Fair, Inclusive, Transparent, Reliable, Accountable, Private.