Different approaches to AI regulation
- The Artificial Intelligence (AI) space has seen certain developments crucial to its regulation in recent years — the United Nations’s Resolution on Artificial Intelligence, the AI Act by the European Parliament, laws introduced on AI in the U.K. and China and the launch of the AI mission in India.
- These efforts to formalise AI regulations at the global level will be critical to various sectors of governance in all other countries.
Key highlights
- With the passing of the United Nations Resolution on Artificial Intelligence, the need and associated discourse on the regulation of AI has entered a new phase.
- It was recognised that unethical and improper use of AI systems would impede the achievement of the 2030 Sustainable Development Goals (SDGs), weakening the ongoing efforts across all three dimensions
- Social, environmental, and economic.
- Another controversial aspect mentioned in the UN resolution has been the plausible adverse impact of AI on the workforce.
- Thus, being the first of its kind, the Resolution has shed light on the future implications of AI systems and the urgent need to adopt collaborative action.
The EU’s approach
- The EU recently passed the AI Act, the foremost law establishing rules and regulations governing AI systems. With its risk-based approach, the Act categorises systems into four categories, namely unacceptable, high, limited, and minimal risks, prescribing guidelines for each.
- The Act prescribes an absolute ban on applications that risk citizens’ rights, including manipulation of human behaviour, emotion recognition, mass surveillance etc.
China’s stand on AI
- The country released, in phases, a regulatory framework addressing the following three issues
- Content moderation, which includes identification of content generated through any AI system
- personal data protection, with a specific focus on the need to procure users’ consent before accessing and processing their data; and algorithmic governance
- With a focus on security and ethics while developing and running algorithms over any gathered dataset.
India’s position
- Amid the global movement towards regulating AI systems, India’s response would be crucial, with the nation currently catering to one of the largest consumer bases and labour forces for technology companies.
- India will be home to over 10,000 deep tech start-ups by 2030. In this direction, a ₹10,300 crore allocation was approved for the India AI mission to further its AI ecosystem
- Through enhanced public-private partnerships and promote the start-up ecosystem.
- Amongst other initiatives, the allocation would be used to deploy 10,000 Graphic Processing Units, Large Multi-Models (LMMs) and other AI-based research collaboration and efficient and innovative projects.
Conclusion
- With its economy expanding, India’s response must align with its commitment towards the SDGs while also ensuring that economic growth is maintained.
- This would require the judicious use of AI systems to offer solutions that could further the innovation while mitigating its risks.
- A gradual phase-led approach appears more suitable for India’s efforts towards a fair and inclusive AI system.