Consequence of Error

How it's measured

O*NET rates each occupation on this dimension on a 1–5 context-importance scale (the CX scale), where higher means the condition is a more frequent or more central part of the work. The figures on this page are those occupation-level ratings — a description of working conditions as workers report them, not a judgment about pay, difficulty, or whether a job is "good."

Occupations where it's highest

The occupations that rate this condition strongest on the 1–5 scale.

Occupations where it's lowest

The occupations that rate this condition weakest — where it is rarely part of the work.

How AI is used by roles where consequence of error is central

A working condition is not itself "being automated" — but we can look at the occupations where it is most central and ask how those people actually use AI. This rolls the Anthropic Economic Index per-role signal up across the roles that rate this condition 3 or higher (CX-rating-weighted). 47.3% of the 438 occupations where this condition is present carry observed AI-usage data (207 roles).

Across those roles, 40.9% of AI conversations are people working with AI and 28.9% hand a task to AI , with an average autonomy of 3.52 / 5.

Roles behind this signal

The occupations where this condition is most central and that also have the most AEI data. "Works with AI" is the role's share of conversations that augment rather than automate.

Source: Anthropic Economic Index (2026-01-15-v4-plus-2025-03-27-v2) over a sample of Claude.ai Free and Pro conversations — not all AI tools and not the whole workforce. This is a role-weighted projection from AEI-linked occupations where this condition is central, not a direct measurement of AI use for the condition itself. Shares are weighted by how central the condition is to each role; some conversations are left unclassified by Anthropic's taxonomy, so shares need not sum to 100.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

• O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
• Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic

Data compiled June 2, 2026. Figures are estimates, not advice.

@misc{singulariki-consequence-of-error,
  title  = {Consequence of Error},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27). Accessed June 7, 2026},
  url    = {https://singulariki.com/work-context/consequence-of-error}
}