Show HN: Is AI hijacking your intent? A formal control algorithm to measure it | Hacker News Reader

Show HN: Is AI hijacking your intent? A formal control algorithm to measure it

10 pointsdaikikadowaki49 comments

I’m an independent researcher proposing State Discrepancy, a public-domain metric to quantify how much an AI system changes a user’s intent (“the Ghost”).

The goal: replace vague legal and philosophical notions of “manipulation” with a concrete engineering variable. Without clear boundaries, AI faces regulatory fog, social distrust, and the risk of being rejected entirely.

Algorithm 1 (on pp.16–17 of the linked white paper) formally defines the metric:

1. D = CalculateDistance(VisualState, LogicalState)

2. IF D < α : optimization (Reduce Update Rate)

3. ELSE IF α ≤ D < β : warning (Apply Visual/Haptic Modifier proportional to D)

4. ELSE IF β ≤ D < γ : intervention (Modulate Input / Synchronization)

5. ELSE : security (Execute Defensive Protocol)

The full paper is available on Zenodo: https://doi.org/10.5281/zenodo.18206943

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Is this paper written with heavy aid by ai? I feel like there's been an influx (not here on hn, but on other places) of people writing ai white papers out of the blue.

/r/llmphysics has a lot of these

It certainly looks AI generated. Huge amount of academic "boilerplate" and not much content besides. It's broken up into chapters like a thesis but the actual novel content of each is about a page of material at most.

The Ghost UI is a nice idea and the control feedback mechanism is probably worth exploring.

But those are more "good ideas" rather than complete finished pieces of research. Do we even have an agreed-upon standard technique to quantify discrepancy between a prompt and an output? That might be a much more meaningful contribution than just saying that you could hypothetically use one, if it existed. Also how do you actually propose that the "modulation" be applied to the model output? It's so full of conceptual gaps.

This looks like an AI-assisted attempt to dress up some interesting ideas as novel discoveries and to present them as a complete solution, rather than as a starting point for a serious research program.

I appreciate the rigorous critique. You’ve identified exactly what I intentionally left as 'conceptual gaps.'

Regarding the 'boilerplate' vs. 'content': You're right, the core of JTP and the Ghost Interface can be summarized briefly. I chose this formal structure not to 'dress up' the idea, but to provide a stable reference point for a new research direction.

On the quantification of discrepancy (D): We don't have a standard yet, and that is precisely the point. Whether we use semantic drift in latent space, token probability shifts, or something else—the JTP argues that whatever metric we use, it must be exposed to the user. My paper is a normative framework, not a benchmark study.

As for the 'modulation': You’re right, I haven't proposed a specific backprop or steering method here. This is a provocation, not a guide. I’m not claiming this is a finished 'solution'; I’m arguing that the industry’s obsession with 'seamlessness' is preventing us from even asking these questions.

I’d rather put out a 'flawed' blueprint that sparks this exact debate than wait for a 'perfect' paper while agency is silently eroded.

https://www.lesswrong.com/posts/rarcxjGp47dcHftCP/your-llm-a...

Hi author, this isn't personal, but I think your AI may be deceiving you into thinking you've made a breakthrough.

Fascinating. Searching https://hn.algolia.com for "zenodo" and "academia.edu" (past year) reveals hundreds of similar "breakthroughs".

The commons (open access repositories, HN, Reddit, ...) is being swamped.

Since OpenAI patched the LLM spiritual awakening attractor state, physics and computer science is what sycophantic AI is pushing people towards now. My theory is that those things tend to be especially optimised for deceit because they involve modelling and many people can become confused between the difference between a model as the expression of a concept and a model as in the colloquial idea of "the way the universe works".

I'd love to see a new cult form around UML. Unified Modeling Language already sounds LLMy.

it's all ai allucination, in a subreddit i once found a tailor asking for how to contact some professors because they found a breakthrough discovery on how knowledge is arranged inside neural networks (whatever that means)

“perceptibility of judgement” is not rigorously defined in these papers, as far as I can tell.

The proposed JTP principle is suspended in midair, too. I can’t identify its ethical basis. Whatever perceptible judgement is supposed to mean, why should it always be transparent? Mechanical systems, such as a physical slot that mounts a sliding door, automatically cause alignment of the force that you use to open that sliding door. Is that “judgement” of the slot perceptible as it corrects my slightly misaligned push? Do I care? No.

I would say that any tool we use responsibly requires that we have a reliable and rich model of the tool in our minds. If we do not have that then we cannot plan and predict what the tool will do. It has nothing to do with “judgements” that the tool makes. Tools don’t make judgements. Tools exhibit behavior.

The issue this paper is grappling with (to what extent humans have a place in the middlespace between them asking an ai to do something, and the ai doing it) is interesting (although I disagree with how the paper tries to solve it).

I’m empathetic to a non-native English speaker using ai to help communicate. I mean, seriously, I would do the same thing if the lingua franca was Japanese.

The author is here saying, well yeah, there’s this weird thing that happens when I use ai by which the ideas that come out the other end are a bit different from what the author intended.

I think the sentiment “well you shouldn’t have used ai” is incomplete.

The paper is not great, but it’s an interesting question.

This is exciting, I hope you manage to get traction for the idea!

I currently have rely on a sort of supervisor LLM to check and detect if we're drifting, or overcomplicating or similar (https://github.com/open-horizon-labs/superego).

While I still to figure out who watches the watchers, they're are pretty reliable given the constrained mandate they have, and the base model actually (usually) pays attention to the feedback.

> the risk of being rejected entirely

I would have phrased it the hope of being rejected entirely, but to each his own I guess.

'Hope' might be a more honest word in an era of infinite noise.

If my logic is just another hallucination, then I agree—it deserves to be rejected entirely. I have no interest in contributing to the 'AI-generated debris' either.

But that’s exactly why I’m here. I’m betting that the 'State Discrepancy' metric and the JTP hold up under actual scrutiny. If you find they don't, then by all means, fulfill your 'hope' and tear the paper down. I'd rather be rejected for a flawed idea than ignored for a fake one."

Hi, I think I saw you on slate star codex the other day!

Wow, good catch! I was just lurking in the shadows of that open thread. I didn't think anyone was actually reading my comments there.

If you've been following my train of thought since then, this white paper is basically my attempt to formalize those chaotic ideas into a concrete metric. I’d love to know if you think this 'State Discrepancy' approach actually holds water compared to the usual high-level AI ethics talk.

Hi HN, I recently submitted a white paper on State Discrepancy (D) to the EU AI Office (CNECT-AIOFFICE). This paper, "The Judgment Transparency Principle (JTP)," is my attempt to provide a mathematical foundation for the right to human autonomy in the age of black-box AI.

Philosophy: Protecting the Future While Enabling Speed

• Neutral Stance: I side with neither corporations nor regulators. I advocate for the healthy coexistence of technology and humanity.

• Preventing Rupture: History shows that perceiving new tech as a “controllable threat” often triggers violent Luddite movements. If AI continues to erode human agency in a black box, society may eventually reject it entirely. This framework is meant to prevent that rupture.

Logic of Speed: Brakes Are for Racing

• A Formula 1 car reaches top speed because it has world-class brakes. Similarly, AI progress requires precise boundaries between “assistance” and “manipulation.”

• State Discrepancy (D) provides a math-based Safe Harbor, letting developers push UX innovation confidently while building system integrity by design.

The Call for Collective Intelligence: Why I Need Your Strength I have defined the formal logic of Algorithm V1. However, providing this theoretical foundation is where my current role concludes. The true battle lies in its realization. Translating this framework into high-dimensional, real-world systems is a monumental challenge—one that necessitates the specialized brilliance of the global engineering community.

I am not stepping back out of uncertainty, but to open the floor. I have proposed V1 as a catalyst, but I am well aware that a single mind cannot anticipate every edge case of such a critical infrastructure. Now, I am calling for your expertise to stress-test it, tear it apart, and refine it right here.

I want this thread to be the starting point for a living standard. If you see a flaw, point it out. If you see a better path, propose it. The practical brilliance that can translate this "what" into a robust, scalable "how" is essential to this mission. Whether it be refining the logic or engineering the reality, your strength is necessary to build a better future for AI. Let’s use this space to iterate on V1 until we build something that truly safeguards our collective future.

Anticipating Pushback:

• “Too complex?” If AI is safe, why hide its correction delta?

• “Bad for UX?” A non-manipulative UX only benefits from exposing user intent. Calling it “too complex” admits a lack of control; calling it “bad for UX” admits reliance on hiding human-machine boundaries.

If this framework serves as a mere stepping stone for you to create something superior—an algorithm that surpasses my own—it would be my greatest fulfillment. Beyond this point, the path necessitates the contribution of all of you.

Let us define the path together.

For example, a critical engineering challenge lies in the high-dimensional mapping of 'Logical State'.

While Algorithm 1 defines the logic, implementing CalculateDistance() for a modern LLM involves normalizing vectors from a massive latent space in real-time. Doing this without adding significant latency to the inference loop is a non-trivial optimization problem.

I invite ideas on how to architect this 'Observer' layer efficiently.

> If AI continues to erode human agency in a black box

What do you mean by this?

Is there evidence this has happened?

> I advocate for the healthy coexistence of technology and humanity.

This means whatever you want it to mean at any given time, I don't understand this point without further elaboration.

Thanks for the direct push. Let me ground those statements in the framework of the paper:

1. On "eroding human agency in a black box":

I am referring to "Agency Misattribution". When Generative AI transitions from a passive tool to an active agent, it silently corrects and optimizes human input without explicit consent. The evidence is observable in the psychological shift where users internalize system-mediated successes as personal mastery. For example, when an LLM silently polishes a draft, the writer claims authorship over nuances they did not actually conceive.

2. On "healthy coexistence":

In this paper, this is defined as "Seamful Agency". It is a state where the human can quantify the "D" (Discrepancy) between their raw intent and the system's output. Coexistence is "healthy" only when the locus of judgment remains visible at the moment of intervention.

For a more rigorous definition of JTP and the underlying problem of "silent delegation," I highly recommend reading Chapter 1 of the white paper.

Does this technical framing of "agency as a measurable gap" make more sense to you?

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