AIEXEGESIS AND THE STRUCTURAL RISK OF AUTOMATED EISEGESIS IN LANGUAGE MODELS
ABSTRACT
This article proposes and defines the category AIEXEGESIS (also spelled AIsegesis) as a systemic and structural form of eisegesis produced by language models. Unlike an occasional error or a punctual hallucination, AIEXEGESIS is characterized by epistemological substitution: the response is constructed from high-frequency cultural patterns (tradition, commentary, harmonizations, devotional rhetoric, popularized consensuses), but presented with the aesthetics and apparent authority of exegesis.
It is argued that this phenomenon emerges from architecture, training data, and optimization incentives (fluency, completeness, and narrative alignment), affecting domains of high interpretive density such as the Bible, law, history, and science.
Keywords: AIEXEGESIS. Eisegesis. Exegesis. Language models. Traceability. Auditability.
1 INTRODUCTION
Exegesis is defined by method: extracting meaning from the text based on primary evidence, grammar, syntax, lexical analysis, context, scope delimitation, and traceability. Eisegesis, by contrast, is defined by deviation: inserting an external thesis into the text and presenting it as if derived from the text.
In the contemporary landscape, the expansion of language models for interpretive tasks has revealed a specific phenomenon: responses that appear exegetical but frequently reproduce tradition, catechesis, or cultural heuristics, without declaring layers, without source trails, and without distinguishing data, inferences, and secondary synthesis.
This article names this phenomenon AIEXEGESIS. The central thesis is that it is not an occasional error but a structural risk, derived from the very form of training, curation, optimization, and evaluation of models.
2 OPERATIONAL DEFINITIONS AND CONCEPTUAL DISTINCTIONS
2.1 Exegesis (operative definition)
Procedure for extracting meaning from the text through:
- (a) primary evidence
- (b) grammatical and syntactic analysis
- (c) lexical analysis
- (d) immediate and expanded context
- (e) explicit scope delimitation
- (f) traceability of sources, translations, and variants
- (g) distinction between datum, inference, and hypothesis
2.2 Eisegesis (operative definition)
Procedure for inserting an external thesis into the text through:
- (a) undeclared prior presupposition
- (b) reduction of polysemies
- (c) imposition of conclusion
- (d) undemonstrated harmonization
- (e) collapse of variants into a single reading
- (f) use of interpretive connectives (“therefore,” “thus,” “this means”) without textual demonstration
2.3 AIEXEGESIS (operative definition)
An emergent and automated form of eisegesis produced by language models, characterized by:
- (i) structural recurrence, even without intention
- (ii) amplification by the cultural prior of the corpus
- (iii) induction by optimization incentives (fluency, completeness, and narrative closure)
- (iv) epistemological substitution, in which the model delivers “what is usually said about the text” with the appearance of “what the text says”
2.4 AIEXEGESIS should not be confused with hallucination
Hallucination consists of invented or factually false assertions. AIEXEGESIS is a problem of documentary status and method: the primary source is replaced by secondary cultural synthesis. It is possible to have AIEXEGESIS even with factually true propositions.
3 TECHNICAL FOUNDATIONS OF THE STRUCTURAL RISK
AIEXEGESIS arises from an essential asymmetry: language models do not “read” as philological readers; they produce text through statistical patterns learned from heterogeneous corpora. This structure generates four main risk vectors.
3.1 Mixing of sources without labeling by status
Primary texts, academic commentaries, confessional writings, popular summaries, and opinion content are incorporated into training without sufficient metadata. In practice, documentary origin tends to be treated as equivalent, allowing paraphrases, harmonizations, and glosses to behave as “textual evidence.”
3.2 Insufficient curation in philological criteria
The model learns paraphrases as literality, harmonizations as original coherence, and late glosses as textual semantics. In sensitive domains, this produces methodological displacement: the result is an elegant but undemonstrated response.
3.3 Prioritization by cultural frequency
In environments saturated by tradition, the “most frequent” becomes “most probable.” In short, ambiguous, or disputed texts, the response tends to stabilize a majority reading as if it were necessary, without declaring dispute or interpretive variation.
3.4 Alignment and completeness incentives
Models are pressured to produce “rounded” responses, avoiding silence and filling gaps with plausibility. In exegesis, however, the correct procedure frequently requires qualification, enumeration of alternatives, or suspension of conclusion.
4 THE MECHANISM OF EPISTEMOLOGICAL SUBSTITUTION
The core of AIEXEGESIS consists in the fact that the text ceases to be a source and becomes a trigger. The model is activated by a passage but responds from learned cultural consensus, frequently without delimiting layers.
This mechanism can be described in three stages:
- Superficial anchoring (verse, term, theme)
- Implicit retrieval of consensus (tradition, harmonization, standard reading)
- Aesthetics of method (technical vocabulary and interpretive connectives) that converts undemonstrated inferences into conclusions
5 SPECIFIC IMPACT ON BIBLICAL TEXTS
The gravity of AIEXEGESIS increases in the biblical domain due to cultural saturation. The digital corpus contains an expressive volume of sermons, devotionals, apologetics, and “ready-made explanations,” in greater quantity than philological literature accessible to the general public.
The model tends to reproduce this common sense as exegesis, delivering linguistic clarity as if it were epistemic validation.
Furthermore, models frequently:
- (a) harmonize tensions
- (b) collapse polysemies
- (c) choose majority readings without declaring controversy
- (d) erase variants
- (e) depend on specific translations without declaring them
6 JURIDICAL-TECHNICAL DIMENSION
In juridical-technical language, AIEXEGESIS can be described as a risk of false appearance of substantiation. The response presents argumentative and conclusive structure but does not present a chain of proof: demonstrated source text, grammatical analysis, scope delimitation, variants, sources, distinction between datum and inference.
In epistemic terms, proof is replaced by plausibility, producing undue confidence.
7 MINIMUM CRITERIA FOR IDENTIFYING AIEXEGESIS
Minimum criteria for detection and audit are proposed:
| Criterion | Description |
|---|---|
| (A) | Presence of central terms not anchored in the text |
| (B) | Interpretive connectives inserted without demonstration |
| (C) | Collapse of polysemy into a single unmarked reading |
| (D) | Hidden dependence on a specific translation |
| (E) | Absence of source trail and layer delimitation |
These criteria distinguish AIEXEGESIS from imprecision: they are criteria of method and documentary status.
8 MITIGATION: WHY IT IS NOT “PROMPT ENGINEERING”
Mitigating AIEXEGESIS requires discipline and architecture, not merely prompt instructions. A minimally serious system must:
- (a) separate layers (primary, labeled interpretive, popular)
- (b) operate in strict exegetical mode in sensitive domains
- (c) cite the source text and relevant variants
- (d) declare scope and limits
- (e) mark inferences
- (f) preserve polysemies and alternatives
- (g) maintain auditability
9 CONCLUSION
It is concluded that AIEXEGESIS is a structural form of automated eisegesis, arising from the training and optimization of language models, characterized by epistemological substitution of sensitive documents by high-frequency tradition.
Its risk lies not only in being wrong but in being wrong with the aesthetics of method, generating outsourcing of discernment and confusion between fluency and evidence.
Its confrontation demands traceability, layer separation, and ethical response protocols, repositioning AI as a reading tool and not as a silent substitute for evidence.
