The algorithm of silence: artificial intelligence, archival bias and the ethical reconstruction of digital memory

Purpose This study critically examines the epistemological and ethical implications of artificial intelligence in digital archival systems. It introduces the concept of the “algorithm of silence” to interrogate how automated processes reproduce historical exclusions through biased data structures. Through a systematic literature review and conceptual modeling, the research proposes a framework for ethically responsive archival curation, grounded in auditability, explainability, reversibility and informational justice. The article aims to reconceptualize digital archives as contested epistemic spaces, advocating for inclusive algorithmic governance and the redefinition of curatorial authority in the age of computational memory. Design/methodology/approach This research employs a systematic literature review across interdisciplinary databases, integrating conceptual modeling and visual schematization to interrogate algorithmic bias in digital archival systems. Using Boolean logic and strategic refinement, 28 peer-reviewed sources were selected and analyzed via Rayyan. Generative AI tools were utilized to construct visual frameworks that enhance interpretative clarity and methodological transparency. The approach foregrounds auditability, reproducibility and epistemic rigor, positioning artificial intelligence not as a neutral tool but as a cognitive extension subject to ethical scrutiny within archival epistemologies. Findings The study identifies three critical findings: (1) the “algorithm of silence” as a conceptual tool to expose how AI systems perpetuate historical exclusions under the guise of neutrality; (2) a paradigmatic rupture in archival mediation, now governed by opaque algorithmic processes; and (3) the imperative for ethical-algorithmic governance grounded in auditability, explainability, reversibility and cultural inclusiveness. These insights reframe digital archives as contested epistemic spaces and advocate for a justice-oriented curatorial paradigm responsive to sociotechnical asymmetries. Originality/value This article offers a novel theoretical framework, the “algorithm of silence”, to critically interrogate how artificial intelligence perpetuates archival exclusions. By integrating digital ethics, critical epistemology and information science, it reconceptualizes digital archives as contested spaces of memory and power. The study's originality lies in its ethical reframing of algorithmic curation, challenging technocratic neutrality and advocating for inclusive, auditable and culturally responsive archival models. It contributes to the emerging field of critical archival AI by proposing a paradigm of curatorial justice in the age of computational memory.