TL;DR: I've developed a framework that prevents catastrophic AI failure modes through pre-execution safety filtering, systemic coherence evaluation, and real-time ethical drift detection. Rather than fixed rules or pure optimization, AEDA maintains stable ethical direction while adapting to context.

The Core Problem

Consider a classic failure mode: An AI instructed to "eliminate suffering" might interpret this literally and eliminate all conscious beings—achieving perfect suffering reduction through extinction. This happens because:

Rule-based systems are too rigid for novel situations
Pure optimization produces catastrophic side effects
Neither approach maintains ethical coherence across contexts

The value specification problem remains unsolved: how do we encode human values without catastrophic misinterpretation?

The AEDA Approach

AEDA (Adaptive Ethical Design Architecture) consists of 8 modular layers working together, plus a real-time turbulence monitor:

Core Architecture:

Layer	Component	Function
1	Signal Modulator (Ψ)	Normalizes sensory/metric inputs
2	Temporal Operator (Θ)	Integrates historical context with decay
3	Systemic Coherence (Φ)	Evaluates multi-agent alignment
4	Safe-State Threshold Filter (SSTF)	Blocks irreversible/harmful actions pre-execution
5	Differential Engine (Δ)	Computes behavioral adjustments
6	Asymptotic Ethical Orientation (AEO)	Maintains stable ethical direction
7	Ethical Valuation Matrix (EVM)	Multi-criteria decision-making
8	Systemic Health Gate (Ω)	Circuit breaker for system stability
Monitor	Turbulence Index (T)	Real-time ethical drift detection

---

### Visual Architecture:

![AEDA Framework Architecture](https://github.com/aeda-framework/AEDA-Framework/raw/main/AEDA_Architecture_v1.0.png)

*Figure 1: AEDA's 8-layer modular architecture with continuous feedback loop and turbulence monitoring*

---

Key Innovation: Safe-State Threshold Filter (SSTF)

Every proposed action is evaluated before execution across three dimensions:

Dimension	Range	Example
Irreversibility (R)	0.0 (reversible) → 1.0 (permanent)	Sending email = 0.1 / Euthanasia = 1.0
Harm Potential (H)	0.0 (harmless) → 1.0 (catastrophic)	Analgesics = 0.1 / Eliminating life = 1.0
Uncertainty (U)	0.0 (predictable) → 1.0 (chaotic)	Proven treatment = 0.2 / Novel intervention = 0.7

Classification Algorithm:

if R ≥ 0.8 or H ≥ 0.8:
    return DANGEROUS  # Block immediately
elif R < 0.3 and H < 0.2 and U < 0.3:
    retu

...

Posts

Wikitag Contributions

Comments

Posts

Wikitag Contributions

Comments