#manual-substitutions

#manual-substitutions

Japan's push into AI-powered robotics is driven less by competitive ambition than by demographic arithmetic. The country's population declined for a 14th consecutive year in 2024, with working-age citizens comprising just 59.6% of the total population.

If the Strait of Hormuz remains closed, I'll be happy if they only stayed at $4 a gallon. This situation is bound to impact budgets for commuters significantly.

This article was produced by Harvard Business School Working Knowledge and features the insights of faculty member Suraj Srinivasan.

The idea of people gathering in one place to do work for one employer is a comparatively recent idea, introduced when the Industrial Revolution brought workers in from farms and small-scale artisan workshops to work in factories in the interests of scale and efficiency.

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.

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.

In a note on Saturday, he recalled economist Robert Solow's quip from the 1980s as PCs were transforming the economy: "You can see the computer age everywhere but in the productivity statistics." The same thing can be said today about AI, Slok wrote, noting that data on employment, productivity and inflation are still not showing signs of the new technology.

The soaring valuations of AI companies aren't just a bet on better software. They're a wager on who will control human labor in the future, according to Roman Yampolskiy, a University of Louisville computer science professor who was one of the first academics to warn about AI's risks. As artificial intelligence moves from tools to increasingly autonomous agents, Yampolskiy said markets are pricing in a radical shift: machines providing "free labor" at scale.