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A company has developed a proprietary AI model that analyzes consumer online behavior and predicts what prices consumers would be willing to pay for certain products, so that retailers may modify pricing accordingly. To test the model, the company has:
Performed an impact assessment
Conducted repeatability tests
Exposed the model to edge cases and potential malicious input
Conducted adversarial testing to identify security threats
Assessed and mitigated discrimination risks
Which additional responsible AI principle has the company failed to assess?
The correct answer is D because the company has already addressed several key responsible AI principles, including fairness through discrimination risk mitigation, robustness through adversarial and edge-case testing, and reliability via repeatability testing. However, there is no indication that the company has addressed transparency, which involves providing clear information about how the model operates, how pricing decisions are made, and how outputs may affect consumers. Transparency is a critical AI governance principle, especially in consumer-facing applications like dynamic pricing, where decisions can significantly impact individuals. Governance frameworks emphasize that users and stakeholders should be informed about AI-driven decisions and their implications. Without transparency, even technically sound and fair systems may lack trustworthiness and fail to meet regulatory or ethical expectations.