#labor-market-projections

#labor-market-projections

For most companies, there's roughly a 12-month period where the business is at its peak value, and then it crashes out. The companies that capture generational returns are often the ones where someone spies that moment instead of assuming the good times will get even better.

Nearly two-thirds of US workers have held a retail job at some point in their career, with many starting in hourly positions at the companies they now run.

Last summer, Bank of America Research predicted a " sea change" in the economy as companies showed increasing signs of learning how to be productive with fewer workers, putting process over people. Six months later, analysts see another year of growth-in GDP, not new jobs. It rhymes with another projection, from Goldman Sachs, that " jobless growth " could become the new normal in the 2020s.

Using this methodology, they have determined that "AI is far from reaching its theoretical capability: Actual coverage remains a fraction of what's feasible." Researchers at Anthropic have introduced a whole new way to analyze AI's impact on work, arguing that there's still a huge gap between what large language models (LLMs) are capable of, and real-world deployment.

We introduce a new measure of AI displacement risk, observed exposure, that combines theoretical LLM capability and real-world usage data, weighting automated (rather than augmentative) and work-related uses more heavily. AI is far from reaching its theoretical capability: actual coverage remains a fraction of what's feasible.

The work, however, didn't vanish with them. Tasks once handled by junior engineers-like writing and testing code, fixing bugs, and contributing to development projects-were absorbed by senior staff, often with the assumption that AI would make up the difference.And while AI has sped up the velocity of shipping code and features, there are fewer people to do tasks like designing, testing, and working with stakeholders, which AI has zero grasp on.