Which combination best supports responsible AI governance during development?

• A. Data quality, transparency of objectives, and ethical development.
• B. Speed, cost-cutting, and minimal stakeholder input.
• C. Marketing alignment and branding.
• D. Data sharing with competitors.

Answer: (A)

Responsible AI governance during development hinges on high-quality data, clear objectives, and ethical development practices. Data quality ensures the model learns from accurate, representative information, reducing bias and errors that can undermine trust and safety. Transparency of objectives makes what the AI is trying to achieve, along with success criteria and constraints, visible to stakeholders, enabling accountability, monitoring, and governance oversight. Ethical development embeds privacy, fairness, safety, accountability, and regulatory compliance into every step of the process, from data handling through deployment, so governance structures can function effectively and be audited. Together, these elements create the foundation for responsible, auditable, and trustworthy AI development. The other choices emphasize speed or branding or data sharing, which undermine governance by narrowing oversight, neglecting ethics and safety, or risking privacy and misuse.