Experts Train AI Systems, Raising Concerns About Job Obsolescence
A new white-collar workforce is training advanced AI models, a role that paradoxically could lead to the obsolescence of their own specialized jobs.
San Francisco – A growing number of professionals with specialized expertise are finding new work training advanced artificial intelligence models. These roles, many of which have emerged only in the last few years, require deep knowledge to test and refine AI capabilities.
Startups like Mercor are acting as intermediaries, connecting this demand for human insight with the need for AI development. The company has recruited individuals such as Lazaros-Antonios Chatzilazarou, a PhD candidate in game theory, to test how AI models apply his field's principles. This work provides a significant income stream.
The trend is supported by major tech firms that are rapidly advancing AI. Companies like Scale AI, through its Outlier network, and Turing offer various tasks, from debugging AI to creating content designed to help AI understand the world.
However, a significant concern is emerging: as these experts improve AI, they may be making their own roles redundant. The International Monetary Fund estimates that generative AI could impact up to 40% of jobs globally, particularly in white-collar sectors. This raises the question of whether these individuals are inadvertently accelerating the displacement of their own professions.
Companies such as Mercor, which has rapidly increased in valuation, are paying these experts substantial fees, with averages around $125 per hour. While this offers attractive compensation, the long-term implications of AI development could fundamentally alter the employment landscape for specialists.