Title The Scientist–AI System: Rethinking Research on War-Related Environmental Contamination
Author(s) Laboratory of Military Ecotones
Affiliation New Euro Vision: exhibitions, marketing, research s.r.o.
Country Czech Republic
Contribution type conceptual paper; methodological paper
Thematic area • Theory, Methodology, and Evidence
Conference framework connection • Analytical Track AT-01 — provisional title to be defined• Analytical Track AT-02 — provisional title to be defined• Analytical Track AT-03 — provisional title to be defined• Analytical Track AT-04 — provisional title to be defined• Analytical Track AT-05 — provisional title to be defined• Analytical Track AT-06 — provisional title to be defined• Analytical Track AT-07 — provisional title to be defined
Abstract Artificial intelligence is frequently discussed either as an autonomous technological capability or as a potential substitute for particular forms of human intellectual work. This contribution proposes a different unit of analysis: the scientist–AI system. The relevant methodological question is therefore not what artificial intelligence can accomplish independently, but what becomes possible when it is used by a domain expert capable of formulating meaningful questions, evaluating outputs, recognizing uncertainty, and connecting information across disciplinary boundaries.
The transition may be comparable in importance to the earlier distinction between scientific work conducted with and without computational tools. AI, however, affects more than the speed of calculation. It can assist with searching heterogeneous information, comparing sources, identifying conceptual connections, exposing gaps in existing knowledge, generating alternative hypotheses, and organizing complex research problems. At the same time, the quality of AI-assisted inquiry remains strongly dependent on the conceptual framework of the researcher. In this sense, AI partly functions as a mirror: narrow questions tend to reproduce narrow analytical spaces, while broader and better-informed questions can reveal connections that established disciplinary routines may leave unexplored.
This has particular relevance for research on war-related environmental contamination. War-transformed soil and freshwater systems are shaped by interacting chemical, hydrological, biological, spatial, historical, military, health, and social processes. No single traditional discipline can adequately represent the entire system. AI does not remove the need for expertise, field observation, sampling, laboratory analysis, or verification. It can, however, reduce the cost and time required for information integration, hypothesis development, identification of knowledge gaps, and research design.
The central proposition is therefore that AI should be evaluated not as an independent scientific actor, but as part of a new research configuration in which human expertise and machine-assisted information processing operate together. For war-contamination research, this configuration may make it possible to redirect more limited resources from repetitive information work toward observation, measurement, verification, and long-term environmental monitoring.
Key points • The appropriate unit of analysis is the scientist–AI system, rather than AI considered in isolation.
• The effectiveness of AI-assisted research depends strongly on expert knowledge and on the quality and conceptual breadth of the questions posed.
• AI can make implicit assumptions, disciplinary boundaries, information gaps, and alternative research pathways more visible.
• War-related environmental contamination is particularly suitable for such an approach because it requires integration across multiple disciplines, source types, spatial scales, and time periods.
• AI should reduce the cost of information synthesis and research design, not replace field measurement, laboratory analysis, or scientific verification. 
Keywords artificial intelligence; scientist–AI system; war-related environmental contamination; military ecotones; research methodology; information integration; freshwater systems; soil contamination; interdisciplinary research; scientific uncertainty
Main discussion question How can the scientist–AI system improve the formulation and organization of research on war-related environmental contamination without replacing empirical observation, expert judgement, and scientific verification?
OJS publication link https://pollution-diseases-ojs.org/index.php/pd/article/view/74
Note. Analytical TracksIn addition to the main thematic areas, the conference programme will include several cross-cutting analytical tracks. These tracks will be defined during the preparation of the programme, based on the submitted abstracts and the emerging links between presentations.At the preliminary stage, abstracts may be assigned to provisional analytical tracks marked as AT-01 to AT-07. Final track titles will be announced after the Scientific Committee has reviewed the submitted materials.