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April 16, 2025

Artificial Intelligence has made its way in everyday life. From Ghibli art to search engines to weapon systems, the technology's penetration is nearly complete. Trends show that organisations are rewiring to cope with the new reality. Governments are using private players to gain AI supremacy, while allowing them a greater say in public policy. India has entered the race late, but plans to develop its own model this year. What are the societal, legal and environmental challenges posed by the AI revolution?

- ROHINI KRISHNAMURTHY

ARTIFICIAL YOURS

SHUBHAM ARORA, a graphic designer based in Jodhpur, Rajasthan, is worried about her job. “Artificial intelligence (AI) is now embedded in the software we use, making the work easy enough for a novice,” she says. “Through a one-line command in English, the software can produce the first draft of an idea. Our work now is to just fine tune that draft. What happens if AI of the future can provide a finished product? Many graphic designing jobs have already become redundant in the past few years,” says Arora.

“In the next decade, AI could allow computer programming possible in natural language like English, instead of programming languages like Python or Java. It will cut IT sector jobs. Even today, AI has equipped non-IT professionals to build apps, reducing the need for a big team of coders,” says a Gurugram-based IT professional, requesting anonymity.

Employees across sectors are anxious by the disruption caused by AI—a technology that provides machines the ability to engage in cognitive activities, such as reasoning, learning and problem-solving, in a way similar to the human brain but at a much faster rate and without fatigue (see ‘Machine language’ on p26).

Five years ago, the leading AI models could barely “write” a coherent paragraph in response to a command. Then, in 2022, OpenAI, a US-based AI research company, launched ChatGPT (Generative Pre-trained Transformer)—a “generative AI” tool that could create new content in response to a prompt and reuse its learnings to solve new problems.

Generative AIs have been in existence since the 1960s (see ‘Synthetic minds’ on p30), but not like ChatGPT, which has better comprehension and minimised biases. It has made generative AI technology a household name and triggered the launch of numerous similar tools—Microsoft’s Copilot, Meta’s Llama, and Google’s Gemini, to name a few.

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