# Political Scientists

> Study the origin, development, and operation of political systems. May study topics, such as public opinion, political decisionmaking, and ideology. May analyze the structure and operation of governments, as well as various political entities. May conduct public opinion surveys, analyze election results, or analyze public documents.

- **SOC code:** 19-3094.00
- **Canonical URL:** https://singulariki.com/roles/role-19-3094-00
- **Also known as:** Citizen Participation Specialist, Government Affairs Researcher, Government Affairs Specialist, Health Policy Analyst, Legislative Affairs Specialist, Legislative Analyst, Legislative Liaison, Legislative Policy Analyst
- **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):
- Teach political science.
- Develop and test theories, using information from interviews, newspapers, periodicals, case law, historical papers, polls, or statistical sources.
- Maintain current knowledge of government policy decisions.
- Disseminate research results through academic publications, written reports, or public presentations.
- Advise political science students.
- Collect, analyze, and interpret data, such as election results and public opinion surveys, reporting on findings, recommendations, and conclusions.
- Interpret and analyze policies, public issues, legislation, or the operations of governments, businesses, and organizations.
- Identify issues for research and analysis.
- Serve on committees.
- Forecast political, economic, and social trends.
- Consult with and advise government officials, civic bodies, research agencies, the media, political parties, and others concerned with political issues.
- Evaluate programs and policies, and make related recommendations to institutions and organizations.

## Skills, tools, capabilities

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

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

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft Outlook _(hot technology, in demand)_
- Microsoft PowerPoint _(hot technology, in demand)_
- Microsoft Word _(hot technology, in demand)_
- Adobe Acrobat _(hot technology)_
- IBM SPSS Statistics _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft Active Server Pages ASP _(hot technology)_
- Microsoft SharePoint _(hot technology)_
- Microsoft Visio _(hot technology)_
- Python _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 97th percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 97th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 81st percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 99th percentile (High) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 21st percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -3.1% growth (Declining); 0.5k annual openings; 6.5k → 6.3k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $139,380; 5,950 employed.

## How people actually use AI here

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

- **Automation vs augmentation:** 22% automation, 73% augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** learning.

**Tasks most handed to AI here:**
- Teach political science. _(9.6% of measured AI use; learning)_
- Interpret and analyze policies, public issues, legislation, or the operations of governments, businesses, and organizations. _(5.1% of measured AI use; learning)_
- Write drafts of legislative proposals, and prepare speeches, correspondence, and policy papers for governmental use. _(2.7% of measured AI use; task iteration)_
- Develop and test theories, using information from interviews, newspapers, periodicals, case law, historical papers, polls, or statistical sources. _(1.8% of measured AI use; learning)_
- Collect, analyze, and interpret data such as election results and public opinion surveys, reporting on findings, recommendations, and conclusions. _(0.7% of measured AI use; learning)_
- Identify issues for research and analysis. _(0.7% of measured AI use; directive)_
- Disseminate research results through academic publications, written reports, or public presentations. _(0.7% of measured AI use; learning)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me teach political science.
- Help me interpret and analyze policies, public issues, legislation, or the operations of governments, businesses, and organizations.
- Help me write drafts of legislative proposals, and prepare speeches, correspondence, and policy papers for governmental use.
- Help me develop and test theories, using information from interviews, newspapers, periodicals, case law, historical papers, polls, or statistical sources.
- Help me collect, analyze, and interpret data such as election results and public opinion surveys, reporting on findings, recommendations, and conclusions.

## 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-19-3094-00_