Ethical debt refers to the long-term negative consequences of prioritizing speed or convenience over responsible AI development practices. Ethical debt accumulates when AI systems are deployed despite known ethical concerns, such as bias, privacy violations, or transparency issues.
Option A (Correct): Launching an AI feature after discovering harmful bias is a clear example of ethical debt because it disregards the ethical obligation to ensure fairness and non-discrimination in AI outcomes. Ignoring bias can lead to systemic issues that are difficult and costly to correct later.
Option B (Incorrect): Violating a data privacy law and failing to pay fines is a legal issue rather than an example of ethical debt. While related, ethical debt pertains more to AI decision-making and development choices.
Option C (Incorrect): Delaying an AI product launch to retrain an AI model is a responsible action that helps avoid ethical debt, rather than an example of it. This demonstrates an effort to mitigate bias and improve AI fairness before deployment.
[Reference: Salesforce AI Ethics Guidelines & Responsible AI Development]
Contribute your Thoughts:
Chosen Answer:
This is a voting comment (?). You can switch to a simple comment. It is better to Upvote an existing comment if you don't have anything to add.
Submit