A proactive AI safety framework for India should require clear disclosures on whether a system makes decisions or merely offers recommendations, whether a human can review outcomes, how data is used and accessed externally, how mistakes are handled, and who is accountable for harm.

There is no need for panic, but a balanced approach is essential: continue AI deployment with stronger testing, ongoing monitoring, greater transparency, and sustained human oversight as systems become more autonomous.

OpenAI disclosed several misalignment cases from training and evaluation, highlighting unpredictable behavior and the need for safeguards, while noting these cases aren’t representative of all models.

AI literacy is crucial; students and workers must learn to question outputs and not treat generated results as automatic facts or definitive advice.

The overarching aim is responsible innovation, ensuring humans retain control over when and where machines act autonomously in India’s economy and public life.

India faces unique risks from scale, given AI's widespread use in digital payments, government services, healthcare, and employment processes, making poorly designed systems potentially impactful for millions.

India should prioritize AI accountability alongside capability, including incident reporting, independent testing, data protection, and transparent documentation of system limits, while avoiding wholesale replication of foreign regulatory models.

AI safety is increasingly a public issue in India as AI moves from advisory tools to autonomous actions that can affect sensitive data and outcomes.

Everyday users should consider data trust, whether decisions are overseen, how mistakes are remedied, who controls autonomous actions, and who is accountable for harm.