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Thinking Outside the Black Box: Seven Guidelines for GenAI Use in the Ecological Sciences
Nina C Ferrari1, Emily E Conklin1, Amelia A Fitch1
1Department of Forest Ecosystems and Society Oregon State University Corvallis Oregon USA.
Ecology and Evolution
|August 13, 2026
Summary
Generative artificial intelligence (GenAI) offers ecological research new tools but risks undermining core principles if uncritically adopted. Responsible use requires balancing efficiency with rigor, creativity, and inclusivity for sound ecological inquiry.
Area of Science:
- Ecology
- Artificial Intelligence
Background:
- Generative artificial intelligence (GenAI) is rapidly being integrated into ecological research workflows.
- This integration spans hypothesis generation, data collection, analysis, and manuscript preparation.
Purpose of the Study:
- To examine the opportunities and challenges of GenAI in ecological research.
- To identify risks to core principles of ecological inquiry.
- To provide guidelines for responsible GenAI use in ecology.
Main Methods:
- The study involves a critical discussion of GenAI's impact on ecological principles.
- It identifies potential adverse effects on reproducibility, transparency, and theory-driven research.
- Actionable guidelines for responsible GenAI integration are proposed.
Main Results:
- Uncritical GenAI adoption may erode ecological inquiry's epistemological foundations.
- Overemphasis on scale and speed risks shifting research from theory to data-mining.
- Potential negative impacts include reduced reproducibility and reinforced inequities.
Conclusions:
- GenAI offers benefits like expanded access and cross-disciplinary synthesis when used thoughtfully.
- Responsible integration requires prioritizing rigor, creativity, inclusivity, and societal relevance.
- A concerted effort for reflective and intentional GenAI use is crucial for the future of ecology.
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