What is Responsible AI?

• A. Ethical and accountable development and use of AI systems.
• B. Ethical and inclusive data labeling strategies only.
• C. Compliance with data privacy laws only.
• D. Maximizing model complexity.

Answer: (A)

Responsible AI means building and using AI systems in a way that is ethical and accountable, with attention to fairness, safety, transparency, privacy, and governance. It involves designing models and data practices that minimize bias, provide explainable decisions, and include human oversight and mechanisms to address harm or unintended consequences. This broader, governance-focused approach captures what responsible AI is about: not just how the technology works, but how it is developed, deployed, and monitored to align with human values and societal norms.

The other options are too narrow. Focusing only on data labeling ignores broader ethics, fairness, and governance. Limiting requirements to privacy laws misses ongoing accountability and safety concerns. Maximizing model complexity does not inherently improve responsibility and can even raise risks.