Could AI make as many jobs as it takes?

Key Concepts

• Generative AI: Artificial intelligence capable of generating new content (text, images, code, etc.).
• Job Displacement: The loss of jobs due to automation, including AI.
• Cost Arbitrage: Taking advantage of lower labor costs in different regions.
• Outsourcing: Contracting work to external companies, often in other countries.
• Red Teaming: A security practice where ethical hackers attempt to find vulnerabilities in a system, in this case, AI models.
• Agentic AI: AI systems capable of autonomous action and decision-making.
• Jobless Growth: Economic growth that doesn't lead to significant job creation.
• Reskilling/Upskilling: Training employees in new skills to adapt to changing job market demands.

The Impact of AI on Jobs: A Comparative Look at the US and India

This episode of Tech Latest from NIK Asia explores the evolving impact of Artificial Intelligence (AI), specifically generative AI, on the job market in the United States and India. The discussion, featuring host Katie Creel and reporters Eion and Chakaborti, reveals a contrasting landscape of job losses and gains, driven by the rapid adoption of AI technologies.

US Job Market: Uncertainty and Layoffs

Eion, reporting from Silicon Valley, paints a concerning picture of the US job market. Despite a seemingly positive stock market performance, there’s widespread anxiety due to significant layoffs across both large tech companies and startups. Over 100,000 tech employees have been laid off in the current year alone, with expectations of further cuts. November saw over 70,000 job cuts, a 25% increase year-over-year, following a staggering 150,000 cuts in October – almost double the same period last year.

While AI isn’t solely responsible for these losses, studies suggest over 50,000 job losses since 2023 are directly attributable to AI adoption. A particularly alarming prediction from Anthropic’s CEO suggests AI could eliminate roughly 50% of all entry-level white-collar jobs within the next one to five years, potentially leading to a US unemployment rate of 10-20%. The term "jobless growth" is used to describe this phenomenon.

However, Eion notes a reluctance among companies to explicitly attribute layoffs to AI due to negative public perception, often framing them as efficiency improvements or corrections after overhiring during 2020-2021. Executives often emphasize AI as a “work companion” and promise reskilling initiatives, but the specifics of these new job opportunities remain unclear.

India’s Job Market: An Outsourcing Boom and Adapting Roles

Chakaborti, reporting from Bengaluru, presents a more optimistic outlook for India, drawing parallels to the tech outsourcing boom of the early 1990s. India is experiencing a surge in demand for roles related to AI’s foundational element: data. This is projected to become a $7 billion industry by the end of the decade.

The new jobs being created don’t necessarily require highly specialized technical skills. Roles like data preparation, model testing, prompt design, AI quality assurance, and agentic system oversight are accessible to college graduates in humanities, commerce, and other non-technical fields with some training. This is particularly significant in India, where the proportion of white-collar jobs has been shrinking (from 24% around the pandemic to 22%).

The outsourcing boom is driven by both cost arbitrage (lower labor costs in India) and a high density of talent – over 30 million college students seeking employment. While these jobs may not offer the same financial rewards as high-level tech or finance positions, they provide a crucial entry point into the corporate world for Indian youth.

While job losses are occurring in India (particularly in content creation, marketing, telecalling, and recruitment due to increased efficiency), the overall impact appears to be a net gain, with companies like Tata Consultancy Services focusing on retraining rather than mass layoffs.

Adapting to the Changing Landscape: Red Teaming and Maintenance

Chakaborti highlights the evolving nature of outsourcing work. Initially focused on tasks like annotating images for autonomous vehicles, the focus is now shifting towards generative AI and agentic AI. A key example is “red teaming,” where companies test AI models by attempting to circumvent their safety protocols (e.g., asking an AI about the gender of an unborn child through indirect questioning).

Another emerging area is the maintenance of AI-powered systems, such as those used in automated checkout stores. Indian teams are tasked with scanning videos to identify and correct errors made by these systems, addressing “corner cases” or “edge cases” that require human intervention. Industry executives believe outsourcing will continue as long as AI engines aren’t fully accurate and require human oversight.

The Human Factor and Long-Term Outlook

Both reporters acknowledge the importance of the human factor. Eion points out that companies are hesitant to publicly blame AI for layoffs, while Chakaborti emphasizes the enduring need for human oversight and the potential for long-term outsourcing relationships.

The long-term sustainability of the outsourcing boom in India will depend on cost competitiveness and the continued need for human input. As AI technology advances, the nature of the work may change, but the fundamental principle of outsourcing – leveraging specialized skills and lower costs – is likely to remain relevant. Katie Creel concludes that the human element will remain crucial, providing reassurance and a point of contact for resolving issues that AI cannot handle.

Notable Quotes

• Eion: “We don’t know if AI is the sole contributor to the job losses. It’s probably not. But according to some studies uh there has been over 50,000 job lost directly contribute to AI since 2023.”
• Anthropic CEO (as reported by Eion): “AI could wipe out roughly 50% of all entry-level white collar jobs in the next five [years].”
• Chakaborti: “Outsourcing overall is never going to stop…until the AI engines become completely accurate and there are the doubts if they can be.”
• Katie Creel: “I think at the end of the day, most people do want to know that if something were to go wrong or if there were an issue, somewhere in the system is a human they can talk to and say, you know, help me.”

Conclusion

The episode reveals a complex and evolving relationship between AI and the job market. While the US faces significant uncertainty and layoffs, India is experiencing a surge in AI-related outsourcing opportunities. The key takeaway is that the impact of AI is not uniform, and the future of work will likely involve a combination of automation and human expertise, with a continued need for adaptability, reskilling, and a focus on tasks that require uniquely human skills like critical thinking, problem-solving, and emotional intelligence. The long-term outlook depends on factors like cost competitiveness, technological advancements, and the enduring value of human oversight.