This episode explores the future of AI model training data and its impact on the labor market, featuring Brendan Foody, co-founder and CEO of Mercor, a company specializing in recruiting individuals to train AI models. Against the backdrop of Mercor's rapid growth and $100 million funding, the discussion centers on the evolving skills needed for AI model training, ranging from software engineering to niche expertise in various fields. More significantly, the conversation delves into the use of LLMs to predict job performance, surpassing human capabilities in many areas, particularly those involving text-based evaluations. For instance, the discussion highlights the power-law distribution of talent in knowledge work and how AI models are better at identifying high-performing individuals than human recruiters. As the discussion pivoted to the evaluation of AI models themselves, the challenges of creating effective benchmarks for superhuman capabilities were addressed, emphasizing the need for industry-specific evaluations focused on economically valuable tasks. In contrast to concerns about job displacement, the conversation also highlighted the potential for AI to augment human capabilities and create new roles, such as building evaluations for AI models, potentially becoming one of the most common knowledge work jobs. What this means for the future of work is a shift towards a global, unified labor market, incorporating both human and AI agents, with a focus on developing skills adaptable to rapid technological change and a need for proactive societal responses to potential job displacement.
