# Equal Opportunity Representatives and Officers

> Monitor and evaluate compliance with equal opportunity laws, guidelines, and policies to ensure that employment practices and contracting arrangements give equal opportunity without regard to race, religion, color, national origin, sex, age, or disability.

- **SOC code:** 13-1041.03
- **Canonical URL:** https://singulariki.com/roles/role-13-1041-03
- **Also known as:** Affirmative Action Officer (AA Officer), Civil Rights Investigator, Equal Employment Opportunity Officer (EEO Officer), Equal Opportunity Specialist, Civil Rights Representative, Complaint Investigations Officer, Equal Employment Opportunity Representative (EEO Representative), Action Officer
- **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):
- Investigate employment practices or alleged violations of laws to document and correct discriminatory factors.
- Prepare reports related to investigations of equal opportunity complaints.
- Interview persons involved in equal opportunity complaints to verify case information.
- Study equal opportunity complaints to clarify issues.
- Interpret civil rights laws and equal opportunity regulations for individuals or employers.
- Meet with persons involved in equal opportunity complaints to arbitrate and settle disputes.
- Develop guidelines for nondiscriminatory employment practices.
- Prepare reports of selection, survey, or other statistics and recommendations for corrective action.
- Monitor the implementation and impact of guidelines for nondiscriminatory employment practices.
- Coordinate, monitor, or revise complaint procedures to ensure timely processing and review of complaints.
- Provide information, technical assistance, or training to supervisors, managers, or employees on topics such as employee supervision, hiring, grievance procedures, or staff development.
- Meet with job search committees or coordinators to explain the role of the equal opportunity coordinator, to provide resources for advertising, or to explain expectations for future contacts.

**Emerging tasks** (O*NET):
- Develop guidelines for nondiscriminatory employment practices, such as affirmative action plans and equal opportunity employment policies.
- Train employees on equal opportunity laws, guidelines, or policies, such as discrimination, diversity, harassment, or affirmative action.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Law and Government _(knowledge)_
- Written Comprehension _(ability)_
- Active Listening _(essential_skill)_
- Oral Comprehension _(ability)_
- Reading Comprehension _(essential_skill)_
- Oral Expression _(ability)_
- Written Expression _(ability)_
- Problem Sensitivity _(ability)_
- Inductive Reasoning _(ability)_
- Speaking _(essential_skill)_
- Critical Thinking _(essential_skill)_
- Social Perceptiveness _(transferable_skill)_

**Skills in demand:**
- Active Listening _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Social Perceptiveness _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- English Language _(Common Skill)_
- Writing _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Complex Problem Solving _(Common Skill)_
- Active Learning _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft Access _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft SharePoint _(hot technology)_
- Microsoft Word _(hot technology)_
- Bashen EEOFedSoft
- Bashen EEOSoft
- Bashen LinkLine
- Berkshire Associates BALANCEaap
- Biddle Adverse Impact Toolkit

## AI exposure & outlook

- **AI task-overlap index:** 64th percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 64th percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 65th percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 67th percentile (High) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 26th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 3.0% growth (About average); 33.3k annual openings; 418k → 430.3k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $78,420; 397,770 employed.

## How people actually use AI here

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

- **Automation vs augmentation:** 25% automation, 62% augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** task iteration.

**Tasks most handed to AI here:**
- Provide information, technical assistance, or training to supervisors, managers, or employees on topics such as employee supervision, hiring, grievance procedures, or staff development. _(2.4% of measured AI use; task iteration)_
- Participate in the recruitment of employees through job fairs, career days, or advertising plans. _(0.3% of measured AI use; task iteration)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me provide information, technical assistance, or training to supervisors, managers, or employees on topics such as employee supervision, hiring, grievance procedures, or staff development.
- Help me participate in the recruitment of employees through job fairs, career days, or advertising plans.

## 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
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **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-13-1041-03_