Learn how to ensure accountability in AI app development for the banking sector by meeting ethical and legal standards. Explore actionable insights for responsible AI practices.
Table of Contents
Question
You need to ensure that the principle of Accountability is followed for a new AI app that is being developed by your company for the banking domain. Which of the following actions supports this requirement?
A. Ensure the solution benefits all members of society.
B. Ensure the solution is secure and provides confidentiality.
C. Ensure the working of the solution is fully understood by all users.
D. Ensure the solution meets ethical and legal standards.
Answer
D. Ensure the solution meets ethical and legal standards.
Explanation
Accountability is followed when you ensure that the solution meets ethical and legal standards. By adhering to established ethical guidelines and relevant legal regulations, developers demonstrate responsible development practices and minimize potential harm caused by the AI application.
Ensuring that the working of the solution is fully understood by all users is not related to Accountability but to Transparency. While transparency is important, it is not the primary concern for accountability. Even if users understand how the system works, the developers are still responsible for ensuring its ethical and legal compliance.
Ensuring that the solution benefits all members of society is not related to Accountability. This falls under the principle of Inclusivity.
Ensuring that the solution is secure and provides confidentiality is not directly related to Accountability. While crucial for responsible AI, security and confidentiality align more with the principle of Privacy and Security, not Accountability.
The six key principles of responsible AI include:
- Fairness: AI systems should treat all people fairly, avoiding biases based on factors such as gender and ethnicity.
- Reliability and Safety: AI systems should perform reliably and safely, with rigorous testing and deployment management to ensure expected functionality and minimize risks.
- Privacy and Security: AI systems should be secure and respect privacy, considering the privacy implications of the data used and decisions made by the system.
- Inclusiveness: AI systems should empower and engage everyone, bringing benefits to all parts of society without discrimination.
- Transparency: AI systems should be understandable, with users fully aware of the system’s purpose, functioning, and limitations.
- Accountability: People should be accountable for AI systems, working within a framework of governance and organizational principles to meet ethical and legal standards.
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