What current trend is observed in AI governance?

• A. The trend is shifting from standard legal compliance to ensuring AI's social responsibility
• B. A focus solely on data privacy
• C. A move toward ad hoc governance with no structure
• D. A decrease in governance due to automation

Answer: (A)

The main concept being tested is how AI governance is evolving beyond mere legal compliance to actively prioritizing the social responsibility of AI systems. Rather than stopping at ticking regulatory boxes, organizations are increasingly designing governance programs that address fairness, safety, transparency, accountability, and broader societal impact. This shift is reflected in adopting responsible AI practices, creating governance boards or committees, conducting impact and risk assessments, and aligning with established frameworks and standards (like OECD AI Principles, regulatory guidelines, and risk-management frameworks). While data privacy remains important, it is only one piece of the puzzle; governance now requires a holistic approach that considers bias, explainability, human oversight, and ongoing monitoring.

Choosing a narrow focus on data privacy misses the broader movement toward accountability for AI outcomes and societal effects. An ad hoc, unstructured approach is unlikely to satisfy regulators, stakeholders, or risk-management needs, since formal governance structures, roles, and metrics are increasingly expected. Governance is not decreasing; automation and AI deployment actually heighten the need for structured oversight, model risk management, incident response, and continuous assurance.