Face-to-Face Discussions with Individuals and Within Teams
Work context · O*NET
Face-to-Face Discussions with Individuals and Within Teams is a work-context dimension in the O*NET database — one of the standardized conditions O*NET uses to describe the environment a job is done in , grouped under Interpersonal Relationships. O*NET defines it by asking workers: "How frequently does your job require face-to-face discussions with individuals and within teams?." It is rated for 893 occupations, which average 4.56 out of 5 (high relative to other context dimensions).
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."
| Economy-wide average | 4.56 / 5 | Mean across all 893 rated occupations |
| Range across occupations | 2.86–5.00 | Lowest to highest occupation rating (spread 2.14) |
| Intensity vs. other dimensions | 99th pct | Where this dimension's average ranks among all O*NET work-context dimensions |
Occupations where it's highest
The occupations that rate this condition strongest on the 1–5 scale.
| Occupation | Rating | Score |
|---|---|---|
| Advanced Practice Psychiatric Nurses | 5.00 | |
| Art Directors | 5.00 | |
| Counter and Rental Clerks | 5.00 | |
| Critical Care Nurses | 5.00 | |
| Dentists, General | 5.00 | |
| Family Medicine Physicians | 5.00 | |
| First-Line Supervisors of Construction Trades and Extraction Workers | 5.00 | |
| Fundraisers | 5.00 | |
| Genetic Counselors | 5.00 | |
| Hospitalists | 5.00 | |
| Neurologists | 5.00 | |
| Nuclear Power Reactor Operators | 5.00 | |
| Nuclear Technicians | 5.00 | |
| Nurse Anesthetists | 5.00 | |
| Nurse Midwives | 5.00 | |
| Nurse Practitioners | 5.00 | |
| Obstetricians and Gynecologists | 5.00 | |
| Opticians, Dispensing | 5.00 | |
| Optometrists | 5.00 | |
| Orthodontists | 5.00 | |
| Orthoptists | 5.00 | |
| Patternmakers, Metal and Plastic | 5.00 | |
| Physician Assistants | 5.00 | |
| Skincare Specialists | 5.00 | |
| Special Education Teachers, Preschool | 5.00 |
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 face-to-face discussions with individuals and within teams 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). 57.4% of the 891 occupations where this condition is present carry observed AI-usage data (511 roles).
Across those roles, 45.5% of AI conversations are people working with AI and 32.1% hand a task to AI , with an average autonomy of 3.56 / 5.
| Collaboration pattern | Share | What it means |
|---|---|---|
| directive | 29.7% | AI does it; you give the instruction |
| task iteration | 23.4% | you and AI go back and forth |
| learning | 19.3% | you ask AI to explain or teach |
| validation | 2.7% | you do it; AI checks your work |
| feedback loop | 2.4% | AI does it, then adjusts from your feedback |
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.
| Occupation | Condition (1–5) | Works with AI | Autonomy |
|---|---|---|---|
| English Language and Literature Teachers, Postsecondary | 4.2 | 63.2% | 4.0/5 |
| Biological Science Teachers, Postsecondary | 4.9 | 63.2% | 4.0/5 |
| Editors | 4.8 | 68.2% | 4.0/5 |
| Educational, Guidance, School, and Vocational Counselors | 5.0 | 70.6% | 4.0/5 |
| Foreign Language and Literature Teachers, Postsecondary | 4.1 | 65.2% | 3.0/5 |
| Recreation and Fitness Studies Teachers, Postsecondary | 4.8 | 66.2% | 3.3/5 |
| Office Clerks, General | 4.6 | 36.5% | 3.0/5 |
| Technical Writers | 4.4 | 54.2% | 4.0/5 |
| Social Work Teachers, Postsecondary | 4.7 | 67.2% | 3.5/5 |
| Instructional Coordinators | 5.0 | 53.1% | 4.0/5 |
| Health Specialties Teachers, Postsecondary | 4.9 | 66.2% | 3.5/5 |
| Education Teachers, Postsecondary | 4.7 | 65.3% | 3.5/5 |
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.
Cite this page
Singulariki. "Face-to-Face Discussions with Individuals and Within Teams." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27). Accessed June 7, 2026. https://singulariki.com/work-context/face-to-face-discussions-with-individuals-and-within-teams
Singulariki. (2026). Face-to-Face Discussions with Individuals and Within Teams. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/work-context/face-to-face-discussions-with-individuals-and-within-teams
@misc{singulariki-face-to-face-discussions-with-individuals-and-within-teams,
title = {Face-to-Face Discussions with Individuals and Within Teams},
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/face-to-face-discussions-with-individuals-and-within-teams}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.