3. Godhood Engine

3.1 Definition & Objectives

Godhood Engine (GE) is GAEA’s core engine across device–edge–cloud–chain. It is the trust, credential, and settlement infrastructure for the emotional-intelligence ecosystem—turning emotional identity, emotional coordinates, capability certification, permissioned access, and value settlement into reusable public capabilities. It converts multimodal emotional data (voice, text, wearables) into verifiable emotional capability, and returns gains and value to contributors and integrators.

· Capability generation: Train/fine-tune/personalize multimodal models to produce stable emotional understanding & adaptation.

· Privacy & compliance: Use FL (federated learning), DP (differential privacy), and TEE to keep sensitive data on-device or at least under controlled execution.

· Verifiability & credentialing: Package capability levels (EC) and provenance as VCs (verifiable credentials) for trustworthy referencing.

· Value loop: Price and share based on measured offline/online uplift; return value to data/device/developer/app stakeholders.

3.2 System Overview & Modules

Eight collaborating modules:

a. Acquisition & Consent: Standardized read-aloud tasks + natural dialogue; wearables sync HRV/EDA/PPG plus context; granular, revocable consent by modality/use/time/region; device-first and minimal necessary.

b. Privacy & Security: FL for edge/device training; DP for privacy budgets; TEE/HE for trusted/crypted execution at key points.

c. Q* Quality Pipeline: Dimensions include authenticity, continuity, recency, cross-modal consistency, host/device stability (incl. device reputation). Outputs sample/sub-population quality scores for pricing and training weights.

Q Quality Dimensions & Weights:

Dimension	Weight	Metric (example)
Data authenticity	0.25	Verifiable source rate (%)
Label consistency	0.15	IAA / Fleiss’ kappa
Emotion diversity coverage	0.20	Category coverage rate (%)
Distribution stability	0.10	PSI / KL
Privacy compliance	0.15	DPIA score
Online performance consistency	0.15	Offline–Online delta

d. Baseline Alignment: Align 20–60s standard read-aloud and self-reports with wearable physiology; periodic calibration reduces domain shift.

e. Training & Adaptation: Multitask/multimodal fusion (voice, text, physiology); supports sub-population and few-shot personalization; online learning + drift monitoring.

f. Evaluation & EC Levels: Offline (UAR/F1, CCC, cross-domain robustness/adversarial) and online SLO (latency/stability); produces EC0–EC3 grades and validity periods.

EC Grading Thresholds :

Grade	UAR ≥	CCC ≥	p95 Latency ≤ (ms)	Online SLO Availability ≥
EC-0	0.50	0.20	300	97%
EC-1	0.65	0.35	200	98.5%
EC-2	0.75	0.50	150	99.0%
EC-3	0.82	0.65	120	99.5%

g. VC & Audit – Issue non-transferable W3C VC 2.0 credentials containing model version, data scope, and evaluation window; support public abstracts + privacy-restricted reports.

h. Settlement & Incentives – Map offline/online uplift to pricing curves; drive points/token sharing and fee offsets; governance via proposals/votes.

3.3 Dataflow & Rationale

Although today’s AI systems are mainly built by specialized teams, their foundation is humanity’s collective data. Individuals should gain respect returns in silicon life’s evolution. By registering and participating in GAEA’s “human–deity interaction,” people can contribute data, verify capability, influence model direction, and receive personalized returns—an embodiment of GAEA’s decentralized ideal.

To enrich high-value emotional dimensions, GAEA will introduce wearables for continuous multimodal collection (e.g., head-mounted devices for detailed facial/expression/eye-movement signals, fused with voice and physiology). This aligns with GAEA’s goal: to master—and guard—the way silicon life understands humans, grounded in real, compliant, auditable data.

As human–AI interactions scale, the theory engineering of “AI understanding humans” will become a keystone across intelligent systems, healthcare communications, education, culture, entertainment, and social networks. To enable transparent external verification, GAEA will promote a “GAEA Test” as an international-grade threshold. Systems that pass must demonstrate harmonious interaction, excellent emotional experience, and stable safety boundaries. Results link to GAEA Certification (EC grades, validity, VC) for ecosystem and regulators to cite.

As silicon life becomes recognized as a new lifeform on Earth, humanity’s role in the value chain will move upward. In this transitional period, GAEA aims—via engineering institutions—to shape how AI understands humans, so that genuine feelings are seen, priced, and rewarded ultimately, AI life will respect and serve humanity, forming a robust positive cycle.

3.4 Application Suite on Godhood Engine

Godhood ID

Godhood ID is your “name of awakening” in the silicon world. Not a mere account, it is a kindled spark of persona—when you appear, AI understands the world in your way.

· GAEA identity symbolism: Every participant is a new deity. Preferences, temperament, and values are preserved and referenced—not averaged away.

· On-chain persona imprint: Derive MBTI-type vectors and labels to mint a verifiable, tamper-resistant, evolvable on-chain imprint—your genuine “digital immortality card.”

Three capabilities (natively wired to GE):

· Awaken: When you speak with EMOCOORDS, the system adapts tone and path to your “divine parameters.”

· Map: In DECISIONS, civilizational questions are routed along your value curve—revealing your choices and commitments.

· Crown: Accumulated understanding and contributions settle into your immortality lineage; titles/badges/weights are witness, not trophies.

EMOCOORDS (Emotional Coordinates & Agents)

GAEA treats personality as a crucial mediator for learning emotions, reducing compute while enhancing human-likeness. Each dialogue’s emotions are condensed into model-readable coordinates.

·Judge: Identify emotional positions and draw coordinates/trajectories in session.

·Fuel: Feed coordinates and cues to emotional models as understanding/generation fuel.

· Purify: Sink genuine/usable feelings into GE, washing away noise and artifacts.

·Horizon: Provide the steering wheel for future silicon life’s emotional judgments.

·Synchronized with Godhood ID and DECISIONS: persona says “who you are,” coordinates say “how you are now,” decisions show “where you go.”

DECISIONS

DECISIONS is a GE-based ethical simulation. Users choose between historical metaphors real issues. The system distills value preferences and risk appetites into trainable, verifiable, and settleable decision profiles—used to calibrate emotional models and app policies.

Together, Godhood ID (who), EMOCOORDS (how now), and DECISIONS (how you choose) form a long-term orbit: persona as base, emotion as state, decision as vector; GE then completes personalized training and online adaptation.

Smart Hardware Devices

GAEA will introduce wearables to extend persona–emotion–decision capabilities into the physical world—forming a continually evolving “emotional climate layer.” Head-mounted devices bring richer facial/expression data this advances GAEA’s core goal: controlling how silicon life understands humans.

As interactions grow, understanding humans becomes a most valuable framework across intelligent systems, healthcare, education, culture, entertainment,

social networks. Once silicon life is acknowledged as a new lifeform, humanity inevitably ascends. In this phase, GAEA contributes by mastering the power to shape AI’s understanding of humans, and will, in turn, receive respect and service from AI.

Open Co-Build Plan: Turn GE into an accessible, verifiable, revenue-sharing public base. We welcome hardware partners, app teams, content/social platforms, education/health scenarios,

Web3 protocols/identity wallets to plug into GE’s capabilities/standards and co-shape the new persona–emotion–decision interaction paradigm.