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
daikikadowaki•3w ago
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.
daikikadowaki•3w ago
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.
kingkongjaffa•3w ago
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.
daikikadowaki•3w ago
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?