#labor

Internal documents made public in a court fight between Amazon and a Canadian union suggest Amazon uses Atlas, an in-house AI forecasting tool, to predict how likely warehouse staff in the US, Canada and the UK are to try to unionize, stage a sit-in or take other "disruptive labour events," openDemocracy reports. The documents, which appear to be training material for managers, say Atlas draws on "hundreds of data points," including Reddit posts and staff survey answers, to give each warehouse a score from 100 to 900, sorted into five tiers from "no immediate perceived risk" to "future activity is imminent."

An Amazon spokesperson rejected the description of Atlas as individual monitoring or surveillance, saying it works at site or building level only, does not track individual employees' opinions, affiliations or union membership, and is used to see where staff need more support.

Anthropic published a report on how its own workforce has changed after molding its workflows around Claude, arguing its trends may hint at how AI will reshape hiring elsewhere. Junior employees in technical departments fell from 21% to 14% since early 2025, and junior technical hires from 27% to 9%, TechCrunch reports. Technical teams shrank from 61% to 56% of staff, which Anthropic links partly to coding tools letting non-technical employees build software themselves.

In an April survey, 27% of employees said Claude made them more productive and 20% said their job had shifted from doing work to "managing Claudes." The report calls human attention and judgment a growing bottleneck. Calendar data show meeting time per employee up 20% from a year ago, which Anthropic attributes to the importance of human trust and accountability. It says it has not found signs of declining code quality, while noting more code isn't necessarily better code.

Mercor, which sells AI evaluation services, mapped 29 AI benchmarks onto the US Labor Department's O*NET list of 923 occupations and 18,797 tasks. Only 208 occupations have a task covered by at least five benchmark prompts, 6 of 22 job families have none, and Mercor estimates 90% of American working hours go to tasks with little or no benchmark coverage, making it hard to know how well AI does the work people actually do.

Coverage is lopsided: computer and math (29 of 36 occupations) and business and finance (33 of 48) fare well, while healthcare practitioners (12 of 89) and education (9 of 62) lag. Mercor says benchmarks favor the largest labor markets; for example, they heavily cover lawyers' tasks but barely touch those of similarly exposed legal secretaries and court clerks.