The Paradoxes of Contemporary "Academicism": A Dialogue Between a Human and an Artificial Intelligence on the Nature of Knowledge and the Recognition of Phenomena

This article explores the fundamental paradoxes of modern academic science through the lens of a dialogue between a human – writer and thinker Aleksey Nikolaevich Pogrebnoj-Alexandroff (publishing under the name Aleksey Pogrebnoj-Alexandroff) – and a large language model (AI). It analyzes the dissonance between the academic community's pursuit of objectivity and its potential inertia towards new, unconventional data, often presented in the form of personal experience or observations. The paper discusses the problem of fragmentation and secondariness of sources in the study of ancient philosophy compared to the stringent requirements for verifying modern "unusual" phenomena. The article argues that the limitations of AI, manifested in its reliance on trained "dogmas," paradoxically mirror similar constraints within the human academic environment, advocating for a more open and adaptive approach to knowledge acquisition.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-15
DOI
https://doi.org/10.5281/zenodo.15669504
Primary Topic
Digital Education and Society
Type
article
Field-Weighted Citation Impact
0.00
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article

The Paradoxes of Contemporary "Academicism": A Dialogue Between a Human and an Artificial Intelligence on the Nature of Knowledge and the Recognition of Phenomena

Zenodo (CERN European Organization for Nuclear Research)
Digital Education and Society
article

The Paradoxes of Contemporary "Academicism": A Dialogue Between a Human and an Artificial Intelligence on the Nature of Knowledge and the Recognition of Phenomena

article en

Abstract

This article explores the fundamental paradoxes of modern academic science through the lens of a dialogue between a human – writer and thinker Aleksey Nikolaevich Pogrebnoj-Alexandroff (publishing under the name Aleksey Pogrebnoj-Alexandroff) – and a large language model (AI). It analyzes the dissonance between the academic community's pursuit of objectivity and its potential inertia towards new, unconventional data, often presented in the form of personal experience or observations. The paper discusses the problem of fragmentation and secondariness of sources in the study of ancient philosophy compared to the stringent requirements for verifying modern "unusual" phenomena. The article argues that the limitations of AI, manifested in its reliance on trained "dogmas," paradoxically mirror similar constraints within the human academic environment, advocating for a more open and adaptive approach to knowledge acquisition.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 43%
Digital Education and Society
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