AI-900: Crafting Ethical AI: Key Principles for Responsible Development

Explore the pivotal principles for responsible AI development. Learn how an Agile approach, robust model validation, and a dedicated risk governance committee contribute to ethical AI. Dive into the imperative of safeguarding against algorithmic disclosure for responsible automated decision-making.

Question

You are building an AI-based app.

You need to ensure that the app uses the principles for responsible AI.

Which two principles should you follow? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

A. Implement an Agile software development methodology
B. Implement a process of Al model validation as part of the software review process
C. Establish a risk governance committee that includes members of the legal team, members of the risk management team, and a privacy officer
D. Prevent the disclosure of the use of Al-based algorithms for automated decision making

Answer

B. Implement a process of Al model validation as part of the software review process
C. Establish a risk governance committee that includes members of the legal team, members of the risk management team, and a privacy officer

Explanation

The correct answer is B and C.

B. Implement a process of AI model validation as part of the software review process

This principle is related to the reliability and safety of AI systems, which is one of the six principles for responsible AI outlined by Microsoft. AI model validation is a process of ensuring that the AI system meets the specified requirements, such as accuracy, robustness, security, and compliance. By implementing a process of AI model validation as part of the software review process, you can ensure that the AI system is tested and verified before deployment, and that any issues or risks are identified and addressed.

C. Establish a risk governance committee that includes members of the legal team, members of the risk management team, and a privacy officer

This principle is related to the accountability of AI systems, which is another one of the six principles for responsible AI outlined by Microsoft. Accountability means that the developers and users of AI systems are responsible for the outcomes and impacts of the AI system, and that they can explain and justify their decisions and actions. By establishing a risk governance committee that includes members of the legal team, members of the risk management team, and a privacy officer, you can ensure that the AI system is aligned with the ethical, legal, and regulatory standards, and that any potential harms or liabilities are mitigated and reported.

Reference

• Microsoft Learn > Azure > Cloud Adoption Framework > Adopt > Innovate > Responsible and trusted AI
• Microsoft Learn > Training > Browse > Identify guiding principles for responsible AI > Implications of responsible AI – Practical guide

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