The exact text we saved

This is the version exactly as it was saved, character for character. The SHA-256 hash below is a 64-character code worked out from that text. Run the same text through SHA-256 and you get the same code; change a single letter and the code comes out completely different. Each version also stores the previous version’s hash, which chains them together so no version can be swapped out quietly.

TRUVACE RECORD VERSION
record: TRV-2026-2872
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-13T00:02:06.157612Z
status: published
lens: p_space
sector: labor
headline: Men Are Experiencing More Job Growth Than Women in AI-Exposed Occupations
dek: Men's employment grew faster than women's in occupations most exposed to AI, a gap driven largely by workers without a bachelor's degree.
gain_title: (none)
problem_title: A Pew Research Center analysis of Current Population Survey data found that among workers with a high school diploma or less, women's employment fell 9.5% for each 1-point rise in occupational AI exposure while men's grew 8.8%, comparing 2017-19 with January 2023-June 2026.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: A Pew Research Center analysis of Current Population Survey data found that among workers with a high school diploma or less, women's employment fell 9.5% for each 1-point rise in occupational AI exposure while men's grew 8.8%, comparing 2017-19 with January 2023-June 2026.
problem_evidence: Among workers with a high school diploma or less, men’s employment grew by 8.8% for each 1-point increase in AI exposure, while women’s fell by 9.5%.
quick_read: A Pew Research Center analysis of government data found that employment in occupations more exposed to generative AI grew much faster for men than for women between 2017-19 and January 2023-June 2026. For each 1-point increase in an occupation's AI exposure score, men's employment grew by 6.3% while women's barely changed at 0.2%.

The gap is concentrated among workers without a bachelor's degree. Among those with a high school diploma or less, men's employment rose 8.8% per exposure point while women's fell 9.5%. For workers with a bachelor's degree or higher, neither group's employment changed significantly with exposure.

Women without degrees often work as secretaries, receptionists and customer service representatives, which sit in the middle to upper part of the exposure scale. Men without degrees mostly work in low-exposure jobs such as truck driving and construction labor, so the male growth applies to a small share of them. Pew cautions that other changes in the period may also have affected employment.
limitation: Pew says the link between AI exposure and job growth is not necessarily direct, because other changes between the two periods may also have affected employment.
tag: Evidence-backed problem
key_points: Pew scored 480 occupations from 0 to 3.5 on generative AI exposure, using task data from the Labor Department's O*NET database. | Employment data came from Current Population Survey monthly files for 2017-19 and January 2023-June 2026; 2020-22 were excluded because of the pandemic. | Men's employment grew about 24% more in the most AI-exposed occupations than in the least exposed, while women's growth was about the same across the scale. | In the least AI-exposed occupations, women's employment grew faster than men's. | For workers with some college education, the gender gap was smaller but still significant. | For workers with a bachelor's degree or higher, neither men's nor women's employment changed significantly as AI exposure increased. | Very high-exposure occupations include accountants and auditors (3.09), software developers (3.10) and financial managers (3.20).
rundown: Pew measured employment growth as the percent change in the number of people employed in an occupation, and compared men's growth with women's within each occupation. It did not compare occupations with each other and said it was not suggesting any job is inherently men's or women's work.

Exposure scores reflect how many of an occupation's most important tasks generative AI can perform or assist with. A score of zero marks the least exposed occupation in the data, not one with no AI exposure. Low-exposure examples include construction laborers (0.70) and home health aides (1.14).

Pew notes that the education split matters: men without degrees are not heavily represented in high-exposure jobs, while women with the same education often work in roles such as secretaries, receptionists and customer service representatives, where chatbots and automated support play a larger role.
sources:
- journalism | Pew Research Center | https://www.pewresearch.org/short-reads/2026/10/22/men-are-experiencing-more-job-growth-than-women-in-ai-exposed-occupations/ | 2026-10-22
prev: 0000000000000000000000000000000000000000000000000000000000000000

SHA-256 hash

1265028906b8089d1ace745ab709eb9fc820e1901bc11afeee7557d584834c3b

Previous version’s hash

0000000000000000000000000000000000000000000000000000000000000000