ArticleBMC medical ethics2025
From chaos to symbiosis: exploring adaptive co-evolution strategies for generative AI and research integrity systems.
Article in BMC medical ethics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Authors and funding
13 authors.
Funding
Abstract
objectiveThe information age has transformed technologies across disciplines. Generative artificial intelligence (GenAI), as an emerging technology, has integrated into scientific research. Recent studies identify GenAI-related scientific research integrity concerns. Using Complex Adaptive Systems (CAS) theory, this research examines risk factors and preventive measures for each agent within the scientific research integrity management system during GenAI adoption, providing new perspectives for integrity management.
methodThis study applies CAS theory to analyze the scientific research integrity management system, identifying four core micro-level agents: researchers, research subjects, scientific research administrators, and academic publishing institutions. It examines macro-system complexity, agent adaptability, and the impact of agent interactions on the overall system. This framework enables analysis of GenAI's effects on the research integrity management system.
resultsThe scientific research integrity management system exhibits structural, hierarchical, and multidimensional complexities, with internal circulation of policy, funding, and information elements. In response to GenAI integration, four micro-level agents-researchers, research subjects, scientific research administrators, and academic publishing institutions-adapt their behaviors to systemic changes. Through these interactions, behavioral outcomes emerge at the macro level, driving evolution of the research integrity management system.
conclusionsRisks of scientific misconduct permeate the entire research process and require urgent governance. This study recommends that scientific research administrators promptly define applicable boundaries for GenAI in research to guide researchers. Concurrently, they should collaborate with relevant departments to establish regulatory frameworks addressing potential GenAI-related misconduct. Academic publishing institutions must assume quality assurance responsibilities by strengthening review and disclosure protocols. Furthermore, research integrity considerations should be systematically integrated into GenAI's technological development and refinement. HIGHLIGHTS: ● Develops an analytical framework grounded in Complex Adaptive Systems (CAS) theory to map evolving interactions among researchers, research subjects, scientific research administrators, and academic publishing institutions within GenAI-integrated research ecosystems. ● Identifies self-reinforcing dynamics between GenAI adoption and integrity governance, wherein adaptive rule adjustments by agents reshape system-wide integrity thresholds. ● Proposes adaptive governance mechanisms that balance innovation safeguards with integrity guardrails, emphasizing context-sensitive policy calibration over universal solutions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.