Kailash Nadh, the CTO of the Indian fintech company Zerodha, recently shared his concerns about the rapid progress of artificial intelligence (AI). In a blog post, Nadh revealed that Zerodha had created an AI policy to ensure that employees would not lose their jobs if an AI implementation rendered their roles obsolete. The policy includes efforts to upskill and offer new opportunities to employees whose jobs are affected by AI.
While Nadh's blog post was specific to Zerodha, his concerns are relevant to millions of organisations worldwide. He pointed out, the breakthroughs in AI over the past few months have been particularly significant. The speed with which AI can now generate code to integrate itself into existing systems is unprecedented. This, Nadh suggests, marks an inflexion point, a moment where the impact of AI on jobs and the economy may be more significant than ever before.
The concern is not just about lost jobs, but also about the nature of the jobs that will emerge to replace them. Will they be equally well-paying and secure? Will they require new skills that are accessible to everyone? Nadh's policy at Zerodha is a step in the right direction, but it's not a bulletproof solution. The reality is that the impact of AI on jobs and the economy is complex and multifaceted.
Moreover, the impact of AI on the economy is likely to be uneven. Some sectors may be more affected than others, and some regions may be more affected than others. For example, jobs in manufacturing and retail may be more susceptible to automation than jobs in healthcare and education. Regions that are heavily reliant on certain industries may be more vulnerable to job losses.
The potential impact of AI on jobs and the economy is not just a matter for businesses and employees to worry about. Governments also have a role to play. Nadh is sceptical that governments will be able to regulate AI effectively. He points to the failure of governments to address climate change as evidence that self-regulation may be the only solution.
“The fact that such a policy had to be formulated marks an inflection point, the implications of which, I am yet to comprehend. Neither blockchain, serverless, web3, big data, nor earlier AI / ML technologies brought this about. But, the specific breakthroughs in the past few months finally did. All it took was 30 minutes to integrate, during which, it generated the code to integrate itself. This time, it feels different," he said in his blog post.
Also Read
'Buying Netflix at $4 billion would've been better instead of...': Former Yahoo CEO Marissa Mayer
ChatGPT beats top investment funds in stock-picking experiment