Algorithmic Knowledge: Generative AI and the Transformation of Scientific Communication
DOI:
https://doi.org/10.55738/journal.v14i1p.183-196Abstract
This article explores the impact of generative artificial intelligence (AI) on academic and scientific communication, analysing how the automation and mediation of AI-generated writing destabilises authorship, authenticity and the credibility of scientific communication. Drawing on existing literature and a qualitative methodology based on case study analysis of synthetic bibliographic references, the algorithmic reuse of retracted scientific literature, and the degradation of synthetic data, the study seeks to understand the impact of AI on the academic and scientific environment. It further discusses the epistemological and ethical implications of the dependence on generative models in the construction and validation of knowledge. It is argued that AI should be understood not merely as a support tool for research, but as a new communication infrastructure, within which what we term "synthetic scientific memory" is constructed — created through probabilistic means of knowledge generation and recombination.