# Media Aesthetics–Experience in the Age of Technogenesis — DeerFlow Daily Question
Generated: 2026-10-17 21:01:56
Clarification processing: HeHe automatic
## Question
Can Maurice Merleau-Ponty’s concept of embodied perception explain the phenomenon of generative AI mediating language and vision? — What challenge does the absence of bodily sensation between prompt and output pose to theories of perception?
## Khoj RAG References
## References (Khoj RAG Search Results)
The items below are materials from the local Khoj document database that are semantically close to the question. In the response, refer to them as a priority, but explicitly state their limitations where the evidentiary basis is weak.
### 1. Document 1 (score: 0.0941162109375)
> The argument for the coherence of the four stages of human–AI contact.txt These four stages are a process in which the three domains of the human mind—emotion, cognition, and volition—are progressively integrated.
| Stage | Primary capacity | Mode of integration |
|------|-----------|-----------|
| Generative wonder | **Affect** | Immediate response, experience prior to aesthetic judgment |
| Uncanny unfamiliarity | **Affect + cognition** | Affect induces cognitive dissonance. Tension between emotion and cognition |
| Critical reflection | **Cognition (Reflection)** | Systematic analysis, conceptual reconstruction, distancing |
### 2. Document 2 (score: 0.12475299835205078)
> Core messages: 1. A question AI can be a partner that helps design better questions, rather than a device that supplies the correct answer. 2. The core of an interpretation class lies not in producing an output, but in the process of reading, comparing, and reconstructing materials in one’s own language. 3. Reflective students can see more clearly the grounds and limits of their own judgments by reviewing sentences generated by AI.
### 3. Document 3 (score: 0.1273635474009991)
> Definition of a key concept: “Presentation materials in the age of generative AI should themselves reveal the way knowledge is arranged.” Lee Yongwook · Lee Humanities academic 03
### 4. Document 4 (score: 0.12988173961639404)
> Case analysis: Situation: A student drafts with AI. Issue: Possibility of submission without understanding the issue. Activity: Confirm the thinking process through the question log. Lee Yongwook · Lee Humanities lecture 06
### 5. Document 5 (score: 0.13119781017303467)
> Today’s question: Is AI a tool, or is it part of the learning environment? Lee Yongwook · Lee Humanities lecture 02
## Response
This question asks what explanatory power and limitations Merleau-Ponty’s concept of embodied perception has when applied to generative AI’s mediation of language and vision, and what challenge the absence of bodily sensation between prompt and output poses to theories of perception. The analysis below proceeds in sequence: (1) the evidentiary basis and limitations of the Khoj local documents, (2) the central concepts of Merleau-Ponty’s theory and their applicability to generative AI, and (3) the challenges involved.
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## 1. Evidentiary Basis and Limitations of the Khoj Local References
The Khoj search results show relatively low semantic similarity scores, ranging from 0.094 to 0.131. An evaluation of the actual content of each document indicates the following:
**Document 1** (`The argument for the coherence of the four stages of human–AI contact.txt`) is the closest to the present question. The four stages presented here—generative wonder → uncanny unfamiliarity → critical reflection—structure a process in which contact between AI and humans begins with **affect** and proceeds toward **cognition (reflection)**. The first stage, “generative wonder,” is defined as “immediate response, experience prior to aesthetic judgment,” which connects directly with the **pre-objective and pre-reflective character of perceptual experience** discussed by Merleau-Ponty in `Phenomenology of Perception`. However, this document does not explain **why contact with AI can produce an affective response despite the absence of bodily sensation**, nor does it theorize the mechanism involved.
**Documents 2–5** concern the use of AI in educational contexts and have limited direct relevance to the present question. The question “Is AI a tool, or part of the environment?” (Document 5) could be reinterpreted from a Merleau-Pontian perspective, but the documents do not explicitly establish a connection with the conceptual framework of embodied perception.
**Limitation**: The Khoj documents provide empirical observations and educational implications concerning human–AI contact, but they do not offer sufficient grounds for the central axes of the present question: a theoretical discussion of Merleau-Ponty, the perceptual specificity of generative AI, and a phenomenological analysis of the absence of bodily sensation between prompt and output. Accordingly, the analysis below relies primarily on academic web-search results (Heersmink et al. 2024, *AI Meets Philosophy* Vol. 6) and interpretations of Merleau-Ponty’s primary works.
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## 2. Merleau-Ponty’s Embodied Perception and Generative AI: Scope and Limits of Explanatory Possibility
### 2.1 Applicable Concepts
There are three key concepts in Merleau-Ponty’s theory of embodied perception that can explain phenomena mediated by generative AI:
**First, the lived body (*corps propre*) and the perceptual field.** For Merleau-Ponty, perception is not a matter of neural networks or representations, but of the body’s motor, affective, and spatial being-in-the-world (*être-au-monde*). Generative AI ‘produces’ language and images, but there is no field in which these outputs arise. For AI, there is no ‘here’ (there). When a prompt is entered, AI does not receive it from any spatial or temporal perspective, and the meaning of the input is constituted not through bodily situatedness but through a statistical distribution.
**Second, the intentional arc.** Merleau-Ponty writes that all conscious life projects “a past, a future, a human setting, a physical, ideological and moral situation” through the intentional arc (Dreyfus, *The Current Relevance*). This arc operates on the basis of bodily habits and an accumulated understanding of the world. Generative AI’s outputs likewise form a kind of statistical model of the ‘world’ through the distribution of its training data, but this is fundamentally different from Merleau-Pontian intentionality. AI ‘responds’ to the world, but is not ‘affected’ by the world. Its outputs are free from embodied risk, desire, fatigue, and joy—the ways in which a body relates to the world. This may be why AI outputs can sometimes feel “too perfect to be comfortable,” connecting with Document 1’s stage of “uncanny unfamiliarity.”
**Third, flesh (*la chair*) and chiasm.** In his later work, Merleau-Ponty explains the reversibility between the sentient and the sensible through the concept of flesh. The dual condition of being a being that sees the world while simultaneously being seen within the world is precisely what makes perception possible. Generative AI does not exist within this structure of reversibility. When a human reads text generated by AI, the human ‘senses’ the AI’s output, but AI does not ‘sense’ the human response. This asymmetry lies at the core of the **phenomenological opacity** of LLMs identified by Heersmink et al. (2024).
### 2.2 The Limits of Explanation: The Problem of the Absence of Bodily Sensation between Prompt and Output
Merleau-Ponty’s theory faces the following fundamental limitations in explaining phenomena mediated by generative AI:
**(1) The impossibility of extending the concept of ‘perception.’** For Merleau-Ponty, perception is always contact with the world **from a perspective**. To perceive an object always means perceiving it from a particular angle and under particular bodily conditions. The output of generative AI arises from no perspective whatsoever. A prompt is merely ‘input,’ not ‘perception.’ Accordingly, the claim that “AI perceives” or that “AI output is the result of perceptual experience” is difficult to sustain in Merleau-Ponty’s terms.
**(2) The absence of habit (*habitude*) and the body schema.** For Merleau-Ponty, habit is the way the body adapts to the world; it is a motor understanding that operates without conscious reflection. The well-known example of a typist whose fingers ‘know’ the location of the keys on a keyboard illustrates this point. Generative AI is not a being that responds to the solicitations of the world through a body schema. AI ‘learning’ is not the formation of embodied habits, but the statistical extraction of surface correlations.
**(3) The absence of intersubjectivity and the co-world.** What Document 1’s stage of “generative wonder” suggests is the paradox that contact with AI can occur without embodied intersubjectivity. Merleau-Ponty regarded the understanding of others as grounded in bodily resonance. Yet AI-generated output can induce meaningful experiences in humans without bodily resonance. This is a phenomenon that is difficult to explain within Merleau-Ponty’s model and reveals the distinctive character of AI-mediated experience.
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## 3. Challenges and the Need for Theoretical Reconstruction
Merleau-Ponty’s concept of embodied perception has **partial explanatory power** with respect to phenomena mediated by generative AI, but it also faces fundamental challenges.
### 3.1 Major Challenges Facing Theories of Perception
**Challenge 1: Meaning generation without sensation.** Merleau-Ponty held that meaning arises from the structure of perceptual experience. Generative AI produces meaningful text without sensory experience. This appears to be a counterexample to the phenomenological thesis that “the origin of meaning is embodied experience.” However, the important distinction here is that AI-generated text is meaningful **to humans** because humans receive the text through embodied perception, not because AI has embodied meaning. In other words, the emergence of meaning still depends on human embodied perception.
**Challenge 2: The phenomenological status of the prompt.** What experience does a human user have when entering a prompt? How does this experience differ from a typical perceptual experience, such as reading a book or looking at a picture? The ‘black box’ interval between prompt and output challenges the temporality of Merleau-Pontian perception. Perception is always accompanied by the **lived time of the perceiving subject**, whereas the time spent waiting for an AI response may rupture the continuity of this lived time. This may be the phenomenological condition under which Document 1’s second stage, “uncanny unfamiliarity,” arises.
**Challenge 3: The replacement of bodily sensation with ‘pseudo-sensation.’** In interaction with generative AI, the absence of bodily sensation creates a distinctive phenomenological state for the user. The experience of sending a message through what seems like a transparent medium represents a new form of the **mediation relation** discussed in Don Ihde’s technological phenomenology (1990). Ihde extended Merleau-Ponty to analyze how technologies transform perception, but the phenomenon of a language-only medium completely bypassing perception lies beyond the scope of his analysis.
### 3.2 Proposals for Theoretical Reconstruction
On the basis of the challenges above, the following theoretical reconstructions are necessary:
**Proposal 1: Refining the concept of ‘disembodied meaning.’** The meaning carried by AI output is not the direct product of embodied experience, but the result of human embodied interpretation being ‘projected’ onto a statistical textual distribution. This calls for extending Merleau-Ponty’s concept of the ‘intentional arc’ to the human–machine interface.
**Proposal 2: Granting generative AI’s perception the status of ‘pseudo-perception.’** This approach recognizes AI ‘perception’ not as a lack but as a difference (Medium, *AI Meets Philosophy* Vol. 6). Generative AI’s ‘perception’ has its own distinctive mode of statistical pattern recognition, constituting an autonomous system that cannot be compared with human perception.
**Proposal 3: Connecting with Lee Yongwook’s ‘AI-as-environment’ thesis.** Khoj Document 5 (“Is AI a tool, or part of the learning environment?”) captures the core of this question. If AI is conceptualized not as a ‘tool’ but as an ‘environment,’ its relation to humans can be newly theorized through Merleau-Ponty’s concept of a *milieu propre*. An environment is a precondition of perception, not an object of perception. This is the point of direct connection with the professor’s paper, `AI_environment_vs_object`.
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## 4. Overall Assessment
Merleau-Ponty’s concept of embodied perception provides a **useful contrastive foil** for explaining phenomena mediated by generative AI, but its limitations as a **direct explanatory model** are clear. The reasons are as follows:
1. Merleau-Ponty’s theory maintains that perception is always embodied, whereas generative AI can produce linguistic and visual outputs without embodiment.
2. The absence of bodily sensation between prompt and output violates the basic assumption of traditional theories of perception: perception is always someone’s bodily perspective.
3. However, this absence does not lead to the negative conclusion that “AI cannot truly perceive.” Rather, it raises the positive task of developing a new theoretical framework capable of explaining AI’s distinctive mode of mediation.
The **central issue** is this: if generative AI produces meaningful outputs through a mode entirely different from human embodied perception, then maintaining Merleau-Ponty’s thesis requires us to (1) demonstrate that the origin of meaning is always embodied perception, (2) expand the concept of embodied perception to include AI’s statistical pattern recognition, or (3) fundamentally reestablish the relationship between perception and language generation. Whichever of these paths is chosen, the Merleau-Pontian framework demonstrates that it is not a self-contained answer, but a productive theoretical starting point that generates deeper questions.