AI is transformative. It is becoming ubiquitous and influential. Therefore, the issue of its regulation arises. Can it be regulated like banking and healthcare? However, AR is unique and evolving rapidly. AI systems learn and adapt. Rigid regulation can stifle it. It can hinder progress. There cannot be prescriptive regulation here.

AI has to experiment and innovate. It has got to be better trained. Restrictive regulations could cripple AI. The pace of innovation is the driving force for the success of AI. Boundaries get pushed. New apps are being explored. We do need cutting edge algorithms. AI should have guardrails, rather than strict regulations. Guardrails should ensure ethical and responsible development of AI.

Guardrails provide guidelines and principles to encourage AI developers to put a premium on fairness, transparency and accountability. Of course, there are ethical challenges. There is the issue of bias in AI’s algorithms. There is an issue of reskilling the workforce.

The bias emerges from complex and opaque algorithms which regulators do not comprehend.

Organisations must rationalise AI-driven decisions. They should disclose their data usage practices. The assessments should lead to identification and rectification of biases. There should be regular audits.

Guardrails should nurture a culture of responsible AI development. Ethical considerations should be at the forefront.

‘One-size fits all’ approach of regulations is not suitable for AI since it is applied to diverse sectors. It is better to have flexible guardrails.

AI is a global phenomenon. GDPA of Europe imposes strict data protection rules. It safeguards individuals. However, these become challenging for AI development. Here for robust development of AI, data sharing is necessary. China has a top-down approach. AI guardrails can allow adaptation to local and global contexts.

AI guardrails could be collaborative. There could be inputs from tech experts, policy makers, ethicists and the general public.

There cannot be red-tapism in AI as it will be a death blow to AI.

There should be a balance between regulation and innovation. There should be a flexible approach.