# Transit and Railroad Police

> Protect and police railroad and transit property, employees, or passengers.

- **SOC code:** 33-3052.00
- **Canonical URL:** https://singulariki.com/roles/role-33-3052-00
- **Also known as:** Patrolman, Railroad Police, Railroad Police Officer, Transit Police Officer, Law Enforcement Officer, Patrol Man, Patrol Officer, Police Captain
- **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):
- Prepare reports documenting investigation activities and results.
- Monitor transit areas and conduct security checks to protect railroad properties, patrons, and employees.
- Apprehend or remove trespassers or thieves from railroad property or coordinate with law enforcement agencies in apprehensions and removals.
- Direct security activities at derailments, fires, floods, or strikes involving railroad property.
- Patrol railroad yards, cars, stations, or other facilities to protect company property or shipments and to maintain order.
- Investigate or direct investigations of freight theft, suspicious damage or loss of passengers' valuables, or other crimes on railroad property.
- Examine credentials of unauthorized persons attempting to enter secured areas.
- Enforce traffic laws regarding the transit system and reprimand individuals who violate them.
- Provide training to the public or law enforcement personnel in railroad safety or security.
- Direct or coordinate the daily activities or training of security staff.
- Interview neighbors, associates, or former employers of job applicants to verify personal references or to obtain work history data.
- Plan or implement special safety or preventive programs, such as fire or accident prevention.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Public Safety and Security _(knowledge)_
- Law and Government _(knowledge)_
- English Language _(knowledge)_
- Customer and Personal Service _(knowledge)_
- Problem Sensitivity _(ability)_
- Active Listening _(essential_skill)_
- Speaking _(essential_skill)_
- Oral Comprehension _(ability)_
- Oral Expression _(ability)_
- Critical Thinking _(essential_skill)_
- Inductive Reasoning _(ability)_
- Speech Clarity _(ability)_

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

**Tools & technology:**
- Microsoft Active Server Pages ASP _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Word _(hot technology)_
- Crime mapping software
- Integrated Automated Fingerprint Identification System IAFIS
- Law enforcement information databases
- MapInfo Professional
- MapInfo StreetPro
- National Crime Information Center (NCIC) database

## AI exposure & outlook

- **AI task-overlap index:** 29th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 25th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 39th percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 25th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 49th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 3.0% growth (About average); 0.2k annual openings; 3.1k → 3.2k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $82,320; 3,000 employed.

## 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-33-3052-00_