Feedback Requested: Stress-Testing the Core Logic of Agape-Centered Ethics & Ethical Chess

The following are examples. Please edit the below so that your disclosure is accurate:

• I used an LLM to help structure, phrase, and draft this post, and it likely contains >50% AI-generated text, but the underlying logic, specific framework references (Weatherill 2025), and conceptual architecture are entirely my own work which I fully endorse.

I am seeking philosophical and formal logic critiques on the axiomatic foundation underpinning Agape-Centered Ethics (ACE) and the Ethical Chess (EC) framework (Weatherill 2025/2026). [1, 2]

While the downstream derivatives of this architecture have been compiled into highly functional alignment prompts to stress-test human value conflicts using LLMs, I want to isolate and evaluate the antecedent logic block. If the root logic contains flaws, the derivative applications will compound those errors. [1, 2]

The Foundational Logic Block

My architecture reduces the human moral condition to the following minimal logic:

1. Self-Defense = Immutable: A non-negotiable, biologically embedded baseline. [1]
2. Pain = "Is" and "Ought": I address Hume’s is-ought gap by positing that neurobiological pain simultaneously functions as a descriptive fact (is) and an intrinsic prescriptive instruction for its own cessation (ought). [1]
3. Proxy-Pain = Vicarious Aversion = Pain: Empathy is conceptualized as "proxy-pain". The agent’s drive for psychological self-defense against this internal aversion creates a direct instruction to act, making another's well-being contingent on their own ("You hurt / I hurt"). [1, 2]
4. Less Pain = Better: A negative utilitarian baseline of minimizing total aversive states. [1, 2]
5. Morality = Minimizing Proxy-Pain: The core objective. [1, 2]
6. Ethics = The Rational Means: The strategic calculations required to achieve minimization. [1]

Application in AI Alignment (Ethical Chess)

In application (the Ethical Chess v iterations), this logic block is used to configure AI as a Diagnostic Mirror (DM) rather than an autonomous moral agent. [1]

By establishing a non-zero floor for moral signal decay based on relational distance $\text{Stake-Weight}\propto \frac{1}{r^2}$, the system forces a strict Human-in-the-Loop (HITL) architecture. It prioritizes high-fidelity, user-sovereign data points over the polite, homogenized "statistical mean" of standard corporate LLM alignment. [1, 2]

Questions for the Community

1. The Is-Ought Bypass: Does using involuntary, neurobiological proxy-pain as a functional imperative validly constrain the prescriptive "ought," or is it a logical bypass that crumbles under analytic scrutiny? [1]
2. Systemic Health vs. Soft Talk: The EC architecture relies on a "Required Load" protocol—forcing the user to accept the cognitive friction of uncomfortable truths to maintain coherence. How do safety and alignment researchers view this trade-off against standard "homeostatic shielding" (AI politeness)? []

I would deeply appreciate any pushes in the right direction regarding the foundational logic. If the core holds, I am happy to open up the broader data on how the version iterations manage scope-interference and value conflicts in active sessions.