LinkedIn is quietly moving into the AI training business

As the demand for AI training surges, LinkedIn is setting its sights on this lucrative sector. The professional networking giant is in the initial phases of developing an 'AI labor marketplace' that could allow individuals to earn as much as $150 per hour by training AI chatbots across various fields, including coding, nursing, and finance. A spokesperson for LinkedIn, which operates under the umbrella of Microsoft, stated that AI training is one of the fastest-growing job roles in the United States. The company is currently engaging in preliminary testing of this new initiative. The role of AI trainers involves human input to enhance the performance of chatbots by evaluating their responses and challenging their capabilities. This emerging gig economy trend has spurred the growth of several startups focused on AI training, catering to significant clients like Anthropic. LinkedIn currently features over a dozen job listings for AI trainers, with compensation varying by expertise. For instance, individuals skilled in Excel and finance can command rates of up to $100 per hour, while a senior software engineer specializing in AI training can achieve the highest rate of $150. Other available positions include trainers for Germanic and Nordic languages, earning up to $100, and those involved in 'red teaming'—testing AI systems—who can earn between $40 and $50 per hour. Additionally, LinkedIn has introduced a notification feature that alerts users about new AI training opportunities, positioning itself as a competitor in a field already populated by rapidly expanding startups that connect AI labs with the necessary human resources to refine their models. The rapid growth of this sector has not been without its challenges. Recent reports highlight significant cybersecurity vulnerabilities, including a major incident involving Scale AI, which exposed sensitive contractor and client data through unsecured Google Docs. Moreover, Mercor faced a serious data breach that compromised contractors' information, resulting in multiple class-action lawsuits within a week.