From LLMs to ethical research: beyond technological enframing

Abstract This paper develops a philosophical framework for understanding Large Language Model (LLM) integration in social science and professional research through the lens of ethical responsibility and existential engagement. We argue that contemporary research practice has fallen into what Heidegger identifies as technological “enframing,” where efficiency metrics override genuine inquiry into human experience. Drawing on Heidegger’s analysis of technological breakdown, Levinas’s ethics of responsibility to the Other, and Juarrero’s theory of enabling constraints, we examine how LLM-based tools make use of what we call “Requisite Experienced Cogency” (REC) for functioning as computational tools, but fundamentally lack the experiential cogency needed for understanding human awareness or producing substantive meaningful insights. Through an extended case study of healthcare research conducted by Thomas, a researcher with personal health challenges, we demonstrate how technological limitations can become enabling constraints when researchers maintain existential engagement with their subject matter while acknowledging what LLM-based tools cannot provide: theoretical depth, ethical sensitivity, and genuine understanding of human complexity. We engage critically with the substantial literature on LLM limitations while arguing that appropriate integration within clear boundaries can serve rather than undermine authentic inquiry.

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Publication Details

Journal
Discover Artificial Intelligence
Published
2025-10-10
DOI
https://doi.org/10.1007/s44163-025-00535-y
Citations
1
Primary Topic
Law, AI, and Intellectual Property
Type
article
Field-Weighted Citation Impact
2.48
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article

From LLMs to ethical research: beyond technological enframing

Michael Lissack, Hugo Letiche
1 citations
Discover Artificial Intelligence
Law, AI, and Intellectual Property
2.48
article

From LLMs to ethical research: beyond technological enframing

Michael Lissack, Hugo Letiche
article en
1 citations

Abstract

Abstract This paper develops a philosophical framework for understanding Large Language Model (LLM) integration in social science and professional research through the lens of ethical responsibility and existential engagement. We argue that contemporary research practice has fallen into what Heidegger identifies as technological “enframing,” where efficiency metrics override genuine inquiry into human experience. Drawing on Heidegger’s analysis of technological breakdown, Levinas’s ethics of responsibility to the Other, and Juarrero’s theory of enabling constraints, we examine how LLM-based tools make use of what we call “Requisite Experienced Cogency” (REC) for functioning as computational tools, but fundamentally lack the experiential cogency needed for understanding human awareness or producing substantive meaningful insights. Through an extended case study of healthcare research conducted by Thomas, a researcher with personal health challenges, we demonstrate how technological limitations can become enabling constraints when researchers maintain existential engagement with their subject matter while acknowledging what LLM-based tools cannot provide: theoretical depth, ethical sensitivity, and genuine understanding of human complexity. We engage critically with the substantial literature on LLM limitations while arguing that appropriate integration within clear boundaries can serve rather than undermine authentic inquiry.

Discover Artificial IntelligenceVol. 5(1)
Tongji University (CN), Institut des Sciences de la Terre de Paris (FR)
Openalex Percentile: Top 8%
Law, AI, and Intellectual Property
2.48
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