The AI revolution reshaped everything in India, from healthcare to agriculture to the corporate industry. The transformative opportunity that India got with the advent of Artificial Intelligence has only made India stand at a crossroads. The million-dollar question lurking around the corner is – How do we regulate AI without killing the very innovation that could propel us into technological leadership?
The challenge
If we end up putting too much regulation on AI, then we can end up strangling startups in red tape while global counterparts take the lead. On the other hand, if we put too little regulation, then we can risk algorithmic discrimination, data privacy, and unchecked corporate power. India has to follow a “balanced” approach, which will feature policies that promote responsible innovation and prevent real harm.
4 pillars for responsible AI growth
If India wants AI to grow responsibly, then the regulatory focus must be transparent on 4 major areas:
Data governance and privacy
Data is the foundation of any AI-based system. India generates a massive amount of data every day, from Aadhar to UPI transactions to health records. We need clear rules about the kind of data that companies are allowed to collect. We should also have governing policies regarding how companies store data and whether they can sell it or not. Indians should know when their information can be used to train AI systems, and they should have the right to refuse it.
The proposed Digital Personal Data Protection Act is the beginning, but it needs AI-specific provisions. Let’s say a hospital uses patient data to train diagnostic AI; patients deserve transparency about that use and assurance that their privacy remains protected.
Algorithmic transparency
Imagine applying for a loan and being denied, as per the decision of AI. This is something dreadful. We should steer clear of any possibility that algorithms will make decisions affecting people’s lives. Whether it is job applications, credit approvals, or insurance rates, people deserve to know the reason behind their approvals and rejections and not be dependent on blunt AI decisions.
India needs “explainable AI” when it comes to high-stakes decisions. While we do not expect companies to divulge trade secrets but they must provide meaningful explanations. In case AI rejects your loan application, you should know the reason behind it.
Mitigating bias
As AI learns from past data, it can pick up bias, whether gender, caste, language, region, etc., if historical data has it. This means AI systems must be tested for bias, and there should be strict regulations that mandate bias audits before deploying AI in critical areas such as hiring, education, policing, lending, and so on. Companies and institutions, whether educational or legal, must provide proof that their systems are unbiased.
Accountability
This pertains to the fact that whenever AI makes any mistake, someone must be held accountable. Whether it is the misdiagnosis of diseases, maligning the reputation of someone, or if it causes an accident, companies cannot just blatantly say that the “algorithm did it.”
India needs transparent liability frameworks. If a facial recognition system wrongly identifies someone or if a self-driving car crashes, there must be repercussions and remedies. This does not refer to the complete banning of AI, but ensuring that companies build it responsibly or else they will face repercussions.
