# Industrial Ecologists

> Apply principles and processes of natural ecosystems to develop models for efficient industrial systems. Use knowledge from the physical and social sciences to maximize effective use of natural resources in the production and use of goods and services. Examine societal issues and their relationship with both technical systems and the environment.

- **SOC code:** 19-2041.03
- **Canonical URL:** https://singulariki.com/roles/role-19-2041-03
- **Also known as:** Ecologist, Environmental Consultant, Environmental Protection Agency Counselor, Research Scientist, Researcher, Aquatic Ecologist, Eco-Industrial Development Consultant, Ecological Professional
- **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):
- Identify environmental impacts caused by products, systems, or projects.
- Identify or develop strategies or methods to minimize the environmental impact of industrial production processes.
- Analyze changes designed to improve the environmental performance of complex systems and avoid unintended negative consequences.
- Conduct environmental sustainability assessments, using material flow analysis (MFA) or substance flow analysis (SFA) techniques.
- Identify sustainable alternatives to industrial or waste-management practices.
- Review research literature to maintain knowledge on topics related to industrial ecology, such as physical science, technology, economy, and public policy.
- Redesign linear, or open-loop, systems into cyclical, or closed-loop, systems so that waste products become inputs for new processes, modeling natural ecosystems.
- Prepare technical and research reports, such as environmental impact reports, and communicate the results to individuals in industry, government, or the general public.
- Monitor the environmental impact of development activities, pollution, or land degradation.
- Examine local, regional, or global use and flow of materials or energy in industrial production processes.
- Build and maintain databases of information about energy alternatives, pollutants, natural environments, industrial processes, and other information related to ecological change.
- Perform analyses to determine how human behavior can affect, and be affected by, changes in the environment.

**Emerging tasks** (O*NET):
- Conduct life cycle assessments of products.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Mathematics _(knowledge)_
- Reading Comprehension _(essential_skill)_
- Deductive Reasoning _(ability)_
- Inductive Reasoning _(ability)_
- Engineering and Technology _(knowledge)_
- Active Listening _(essential_skill)_
- Writing _(essential_skill)_
- Speaking _(essential_skill)_
- Written Expression _(ability)_
- Critical Thinking _(essential_skill)_
- Oral Expression _(ability)_
- Problem Sensitivity _(ability)_

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

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Adobe Acrobat _(hot technology)_
- Adobe Illustrator _(hot technology)_
- Adobe Photoshop _(hot technology)_
- Apache Hadoop _(hot technology)_
- Atlassian JIRA _(hot technology)_
- Autodesk AutoCAD _(hot technology)_
- C# _(hot technology)_
- ESRI ArcGIS software _(hot technology)_
- Git _(hot technology)_
- Linux _(hot technology)_
- Microsoft Access _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 78th percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 75th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 95th percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 60th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 20th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 4.4% growth (About average); 8.5k annual openings; 90.3k → 94.3k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $80,060; 84,930 employed.

## How people actually use AI here

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

- **Automation vs augmentation:** 45% automation, 49% augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** directive.

**Tasks most handed to AI here:**
- Examine societal issues and their relationship with both technical systems and the environment. _(1.1% of measured AI use; directive)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me examine societal issues and their relationship with both technical systems and the environment.

## 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-19-2041-03_