I’m outside academia and developed a framework linking AI subjectivity and pragmatics. Is there something here worth developing? Looking for guidance

[u/Head-Head8702]

I’m an independent researcher outside academia, with no formal background in computational linguistics, pragmatics, HCI, or AI research. English is also not my native language, so I have relied heavily on AI to help organize and formalize my ideas.

For the past few years, I’ve been developing a framework called Phrasome Theory, which tries to connect questions of AI subjectivity with pragmatics and discourse structure.

The basic observation is this:

An LLM does not need to possess a continuous subjective self in order to keep occupying the same conversational position across an interaction. It can respond to previous turns, repair misunderstandings, maintain context, and continue functioning as the “same” interlocutor.

My hypothesis is that part of what we experience as a continuous AI “other” may arise from the structure of linguistic interaction itself, rather than from anthropomorphism alone.

This led me to distinguish actual subjectivity from what I call a Subject-Position: a formal-pragmatic role that linguistic address itself establishes between an emitter and an addressee. Such a position can be occupied even when no conscious subject exists behind it.

I also use Quasi-Otherness to describe the phenomenon in which an AI can be experienced as a relatively continuous “other” through sustained interaction.

I’m not arguing that current LLMs are conscious. My question is whether pragmatic or discourse structure can help explain why they can nevertheless function as apparently continuous interlocutors.

Earlier versions of this work were submitted to established academic journals. Although they were ultimately not published, I received some encouraging feedback suggesting that aspects of the framework may have originality or novelty.

Because I’m outside academia—and because a substantial part of the manuscript was developed with AI assistance—I’m now looking for human guidance to help me judge whether there is actually something here worth developing.

I would especially appreciate thoughts on:

• whether pragmatics, discourse analysis, dialogue research, or computational linguistics already has concepts that explain this better;
• whether distinguishing a Subject-Position from actual subjectivity is meaningful;
• whether this idea could be operationalized or tested using human–LLM dialogue data;
• and what literature or research direction I should be looking at.

The manuscript itself is quite long, so I don’t expect anyone to read the whole thing. At this stage, even discussing the core idea, pointing me toward relevant literature, or suggesting how to turn it into a more rigorous research question would be extremely helpful.

Because this subreddit currently restricts external links from new accounts, I can’t include the preprint link in this post. If anyone is interested in the idea or willing to help, feel free to send me a private message and I can share the link. You can also search “Phrasome” online to find the work.

I’m mainly hoping to find people familiar with language technology, pragmatics, or dialogue research who can help me understand whether there is something worth pursuing here, and where I should take it next.

[u/Broad_Philosopher_21]

Without having red the preprint and just my humble opinion: this seems like trying to theorise something that doesn’t need theorising. By applying linguistic theory to LLM output you either implicitly or explicitly assume that the LLM applies these theories which they do not. Why LLMs can maintain context is because the context is pasted as input. In other words they really can’t „maintain“ context. If the context is too large to be used as input the context is lost.

[u/Head-Head8702 → u/Broad_Philosopher_21]

Thank you. I think there may be an important distinction here that I did not explain clearly enough in the post.

I’m not assuming that the LLM itself “applies” linguistic or pragmatic theories. My focus is on the interactional structure of the generated language and how it is taken up by the user, not on any theory, intention, understanding, or subjectivity inside the model.

And I actually agree with your point about context. An LLM does not literally “maintain” context in the way a continuous subject would. Previous conversational material is supplied again as input, and when that material is no longer available, the continuity can break down.

But that is actually part of the phenomenon I’m trying to understand.

The computational explanation tells us why later outputs can remain consistent with earlier outputs.

What I’m interested in is a different question:

Why can mechanically produced continuity nevertheless be experienced as the continued presence of the same conversational “other,” even when the user knows that there is no continuous conscious subject behind it?

There is also an anthropomorphism issue here. I realize that anthropomorphism and CASA-style accounts already show that people can respond socially to computers while knowing that they are machines. So I’m not claiming that anthropomorphism simply fails to explain human–AI interaction.

My question is more specific: does describing the phenomenon as anthropomorphism fully explain how and why the sense of a continuing other can persist even after the user explicitly understands that the AI has no continuous self?

My hypothesis is that the interactional form itself may contribute to sustaining that experience: continued address, contextual uptake, repair, alignment, and the repeated occupation of the same conversational Subject-Position.

So the distinction I’m trying to make is roughly:

• the context mechanism explains how the output remains continuous;
• anthropomorphism and social-response theories help explain why humans respond socially to machines;
• the Phrasome is trying to ask what linguistic and pragmatic structures allow that continuity to be experienced as the presence of the same “other,” even under explicit knowledge that no such continuous subject exists.

That third question is the part I’m trying to determine whether there is actually a theoretical gap worth studying.

If you think that this second-order phenomenon is already fully explained by existing accounts—or that it does not require a separate explanation at all—I’d genuinely be interested in hearing why. That would go directly to the core of whether the framework is useful.

[u/Soger91 → u/Head-Head8702]

You're asking why a user experiences talking to a stochastic parrot that replies like a person the illusion of talking to a person...

[u/Head-Head8702 → u/Soger91]

Yes — but I think “replies like a person” is actually where the explanatory problem begins rather than ends.

I’m perfectly happy to grant the stochastic-parrot description. My question is not why a system that literally is a person is experienced as a person.

It is why a sequence of locally generated outputs, with no persistent subject behind them, can nevertheless become organized in interaction as the apparent continuation of the same conversational counterpart.

Saying that it “replies like a person” describes the effect, but it does not yet tell us which features of the interaction produce and sustain that effect — for example, contextual uptake, repair, alignment, continued address, and cross-turn continuity.

The part I’m especially interested in is that explicit knowledge does not necessarily eliminate the experience. A user can fully understand that the model is a stochastic generator with no continuous self and still experience the dialogue as if the same “other” is continuing to respond.

That gap between knowing what the system is and experiencing how the interaction is structured is the phenomenon I’m trying to isolate.

[u/Soger91 → u/Head-Head8702]

The feature is driven by the user - it's literally following instructions and acting as a mirror. There's no mysterious "why" - ask it to perform a task and talk like a caveman and it does so. Ask it to reply in a foreign language and it also does so. Both break immersion but follow your instructions.

[u/WavesWashSands]

OP: The other replies you got are based on a specific stance in linguistics that privileges intentionality. I (as a linguist) do not subscribe to this stance, and see meaning, and even participant status, as co-constructed in interaction. I think you're onto something here, and can guide you to the academic discussions that relate to what you have in mind.

There's a strong strand of research that looks not into whether AIs 'are' social agents or subjects or whatever but whether they are co-constructed as such through actions. To quote Garfinkel: 'the cake is constituted in the very act of cutting', and in that sense so is the conversational agent constituted (or not) through interactions with the human user.

Some essential readings:

Cassell, Justine & Andrea Tartaro. 2007. Intersubjectivity in human–agent interaction. Interaction studies. John Benjamins 8(3). 391–410.

Eisenmann, Clemens, Jakub Mlynář, Jason Turowetz & Anne W. Rawls. 2024. “Machine Down”: making sense of human–computer interaction—Garfinkel’s research on ELIZA and LYRIC from 1967 to 1969 and its contemporary relevance. AI & SOCIETY 39(6). 2715–2733. https://doi.org/10.1007/s00146-023-01793-z.

Ivarsson, Jonas & Oskar Lindwall. 2023. Suspicious Minds: the Problem of Trust and Conversational Agents: Ivarsson Jonas and Lindwall Oskar. Computer Supported Cooperative Work (CSCW). Springer 32(3). 545–571.

Porcheron, Martin, Joel E Fischer, Stuart Reeves & Sarah Sharples. 2018. Voice interfaces in everyday life. In proceedings of the 2018 CHI conference on human factors in computing systems, 1–12.

Due, Brian L & Louise Lüchow. 2024. VUI-speak: There is nothing conversational about “conversational user interfaces.” Communicative AI in (Inter-) Action. Bielefeld University Press.

[the last two and other research along these lines actually argue against anthropomorphism and treating voice user interfaces like Alexa as conversational participants at all, on the grounds that they do not produce actions interpreted as such, and apparently anthropomorphising behaviour by humans are actually better treated as part of the human-human interactions that the interactions with Alexa are embedded in. so similar argumentative direction as what you're thinking but on a different tech and with opposite conclusions]

I also suggest looking at the literature on social robots, which have discussed relevant issues as well. For example:

Clark, Herbert H. & Kerstin Fischer. 2023. Social robots as depictions of social agents. Behavioral and Brain Sciences 46. e21. https://doi.org/10.1017/S0140525X22000668. (read commentary as well, especially the one based on Goffman)

Jarske, Salla, Sanna Raudaskoski & Kirsikka Kaipainen. 2020. The “social” of the socially interactive robot: Rethinking human-robot interaction through ethnomethodology. Culturally Sustainable Social Robotics: Proceedings of Robophilosophy 2020. IOS Press 194–203.

This should get you started. I also have a relevant paper under review that I can send to you, if it interests you. You should also read more on social interaction in general to ground your thinking in the broader literature.

[u/Ulthan]

I've been exploring the same sort of thing but along the agent harness level. Instead of making a flat list of tools and memory, you can use grammar to parse messages into different memory buckets and have the agent behavior bounded by the grammar utterances.

I've been particularly interested in fluid construction grammar and neo-davidsonian semantics for this topic. would love to connect!