# Area, Ethnic, and Cultural Studies Teachers, Postsecondary

> Teach courses pertaining to the culture and development of an area, an ethnic group, or any other group, such as Latin American studies, women's studies, or urban affairs. Includes both teachers primarily engaged in teaching and those who do a combination of teaching and research.

- **SOC code:** 25-1062.00
- **Canonical URL:** https://singulariki.com/roles/role-25-1062-00
- **Also known as:** Assistant Professor, Associate Professor, Professor, Women's Studies Professor, Adjunct Professor, American Studies Professor, Black Studies Professor, Ethnic Studies Professor
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Initiate, facilitate, and moderate classroom discussions.
- Evaluate and grade students' class work, assignments, and papers.
- Prepare and deliver lectures to undergraduate or graduate students on topics such as race and ethnic relations, gender studies, and cross-cultural perspectives.
- Prepare course materials, such as syllabi, homework assignments, and handouts.
- Keep abreast of developments in the field by reading current literature, talking with colleagues, and participating in professional conferences.
- Compile, administer, and grade examinations, or assign this work to others.
- Plan, evaluate, and revise curricula, course content, course materials, and methods of instruction.
- Conduct research in a particular field of knowledge and publish findings in professional journals, books, or electronic media.
- Maintain regularly scheduled office hours to advise and assist students.
- Maintain student attendance records, grades, and other required records.
- Collaborate with colleagues to address teaching and research issues.
- Advise students on academic and vocational curricula, and on career issues.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Education and Training _(knowledge)_
- English Language _(knowledge)_
- Reading Comprehension _(essential_skill)_
- Speaking _(essential_skill)_
- Instructing _(transferable_skill)_
- Oral Expression _(ability)_
- Written Expression _(ability)_
- Active Listening _(essential_skill)_
- Writing _(essential_skill)_
- Active Learning _(essential_skill)_
- Learning Strategies _(essential_skill)_
- Oral Comprehension _(ability)_

**Skills in demand:**
- English Language _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Instructing _(Specialized Skill)_
- Writing _(Common Skill)_
- Learning Strategies _(Specialized Skill)_
- Active Listening _(Common Skill)_
- Active Learning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Foreign Language _(Common Skill)_

**Tools & technology:**
- Google Docs _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Windows _(hot technology)_
- Microsoft Word _(hot technology)_
- Learning management system LMS _(in demand)_
- Blackboard Learn
- Collaborative editing software
- Course management system software
- Desire2Learn LMS software

## AI exposure & outlook

- **AI task-overlap index:** 87th percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 88th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 63rd percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 95th percentile (High) — source: microsoft_applicability.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 2.4% growth (About average); 1.1k annual openings; 14.5k → 14.8k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $84,290; 11,430 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 34% automation, 63% augmentation (usage-weighted).
- **Autonomy median:** 3.5 (higher = AI acts more independently).
- **Dominant collaboration mode:** directive.

**Tasks most handed to AI here:**
- Evaluate and grade students' class work, assignments, and papers. _(25.7% of measured AI use; validation)_
- Conduct research in a particular field of knowledge and publish findings in professional journals, books, or electronic media. _(13.9% of measured AI use; learning)_
- Provide professional consulting services to government or industry. _(12.8% of measured AI use; task iteration)_
- Compile, administer, and grade examinations, or assign this work to others. _(10.6% of measured AI use; directive)_
- Plan, evaluate, and revise curricula, course content, course materials, and methods of instruction. _(5.9% of measured AI use; task iteration)_
- Prepare course materials such as syllabi, homework assignments, and handouts. _(3.8% of measured AI use; directive)_
- Advise students on academic and vocational curricula, and on career issues. _(3.8% of measured AI use; task iteration)_
- Compile bibliographies of specialized materials for outside reading assignments. _(2.9% of measured AI use; directive)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me evaluate and grade students' class work, assignments, and papers.
- Help me conduct research in a particular field of knowledge and publish findings in professional journals, books, or electronic media.
- Help me provide professional consulting services to government or industry.
- Help me compile, administer, and grade examinations, or assign this work to others.
- Help me plan, evaluate, and revise curricula, course content, course materials, and methods of instruction.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-25-1062-00_