‘There’s a lot of desperation’: skilled older workers turn to AI training to stay afloat

2026-04-07 · Source: AI (artificial intelligence) | The Guardian · Field: Business & Management — Human Resources & Workforce Development, Artificial Intelligence & Machine Learning, Economic Analysis & Policy · Depth: Fundamental Awareness, long

Summary

Skilled older workers, including a 60-year-old information management professional named Patrick Ciriello, are increasingly turning to AI training as a "last refuge" in a challenging job market. Despite having extensive experience and advanced degrees, many face significant hurdles in finding traditional employment, with workers over 60 taking 50% longer to secure new jobs than younger counterparts. This emerging work, known as data annotation, involves labeling and evaluating information to train AI models like OpenAI's ChatGPT and Google's Gemini. While some top experts can earn over $180 an hour, many, like Ciriello, earn $20-$26 an hour, often without benefits, covering basic living expenses but offering little financial stability or retirement prospects. The work provides a "bridge job" for professionals like former emergency physician Rebecca Kimble and a PhD-holding academic named Anne, allowing them to apply their expertise in a flexible, intellectually engaging, but often unstable, gig-economy environment.

Key takeaway

For HR professionals and policymakers concerned with workforce transitions, this trend highlights the critical need for robust social safety nets and retraining programs. As AI reshapes job markets, you should consider how to support skilled older workers who are often displaced and underemployed, ensuring they have access to stable, well-compensated roles rather than precarious gig work. Proactive measures can mitigate the economic and personal devastation experienced by those caught in technological shifts.

Key insights

AI training offers a "bridge job" for skilled older workers facing age discrimination and job market difficulties.

Principles

• Age bias prolongs job searches for older workers.
• Economic shocks disproportionately impact older professionals.
• AI training provides a temporary income source.

Method

Data annotation involves human experts reviewing and correcting AI model outputs to improve accuracy and reliability, leveraging their subject matter expertise to refine system behavior.

In practice

• Explore AI training platforms for temporary income.
• Utilize subject matter expertise for specialized annotation tasks.

Topics

• AI Training
• Data Annotation
• Older Workers
• Job Market Challenges
• Gig Economy

Best for: HR Professional, Policy Maker, General Interest

Related on AIssential

• Newsflash: If you think you're going to keep your job because you "learnt AI", you are in for a rough time. — AI's core purpose is job replacement, not enhancement, leading to economic collapse and societal destitution.
• The jobs most at risk may still find a way forward — AI's labor market impact is uneven, with worker adaptability and mobility being key factors, not just job exposure.
• The AI bots are coming and the young are booing, not applauding — Widespread anxiety among young workers about AI's job displacement potential highlights a critical societal adaptation challenge.
• Gig workers are endlessly exploited. AI could make more of us share their fate — AI adoption is driving a broad "gigification" of the workforce, eroding traditional employment benefits for cost savings.
• Your Employees Aren’t Ready For AI — And It’s A Problem — Employee AI readiness is a critical bottleneck for productivity and ROI, despite widespread AI investments.
• Pro-Worker AI — Pro-worker AI augments human expertise and creates new tasks, offering a counter-narrative to job displacement.

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by AI (artificial intelligence) | The Guardian.