This study aims to define the “AI footprint” within the educational and cultural spheres, analyzing inherent privacy and fairness risks while proposing robust, responsible governance models. It investigates the conceptual reliability of large language models (LLMs) as a foundational requirement for ensuring the integrity of human-centered digital libraries (DLs). Using a transdisciplinary approach, this research combines a systematic literature review with empirical stress-testing of LLMs in domain-specific knowledge organization. This methodology aims to quantify latent risks to information integrity and conceptual security within the Cultural-Critical Cyber Ecosystem (CCCE) framework.
This research adopts a transdisciplinary approach, merging a systematic literature review with a targeted empirical investigation. The core methodology involves stress-testing LLM performance in domain-specific knowledge organization tasks. These tests are conducted within the CCCE framework to quantify latent risks to conceptual security and information integrity. This study evaluates the current generation of generative agents (up to 2025), focusing on identifying specific points of failure in semantic consistency and the effectiveness of privacy-enhancing technologies in mitigating these risks.
The empirical evidence reveals significant “semantic decay” and conceptual inconsistencies in LLM outputs, which risk fueling manipulated narratives if left unverified. However, this study finds that these risks can be mitigated by positioning DLs as “Trust-Anchors.” Findings suggest that “interactional footprints” can be successfully converted into “living metadata” to enhance discovery without compromising privacy. The results also highlight a critical lack of formalized metrics for evaluating AI reliability within unified cultural ecosystems, necessitating a transition from viewing data as a threat to treating it as heritage.
This study’s primary contribution lies in the conceptual metamorphosis of the “AI footprint” from a surveillance-oriented byproduct into a “Legacy of Provenance.” By reframing this footprint as an anthropological artifact, the research offers a novel perspective that bridges the gap between theoretical FATE principles and the practical resilience of cultural heritage memory. It provides a unique roadmap for library curators and educators to transition from “data-as-threat” to “data-as-heritage,” promoting an equitable digital future that safeguards collective knowledge against the risks of a “digital dark age” through human-centered integrity.
