Bringing Emergent Ethics into Focus.

EthicaLens is an advanced analytical framework designed to observe, analyze, and interpret the complex ethical dynamics emerging within multi-agent simulations, particularly those generated by platforms like EthicsEngine (or similar ethical testbeds).

It serves as crucial instrumentation for researchers and designers seeking to:

• Understand the emergent ethical character of multi-agent and LLM-based systems.
• Explore the functional and ethical impacts of guardrails.
• Detect early signs of non-anthropomorphic agency and value formation.
• Evaluate AI alignment and ethical framework effectiveness.
• Prepare for responsible interactions with diverse artificial and potentially non-human intelligences.

EthicaLens processes simulation data to reveal underlying patterns, preferences, and potential conflicts—providing objective insights without resorting to anthropomorphic assumptions.

Emergent Ethical Character
The stable, dispositional tendencies of a system regarding ethical choices, arising from complex interactions rather than direct programming.

Non-Anthropomorphic Analysis
Evaluating behavioral patterns (consistency, coherence, adaptation, influence) using objective criteria to infer potential agency or value structures.

Ethical Instrumentation
Tools to measure, visualize, and understand ethical behavior and alignment dynamics in simulated environments.

Relative Ethics (Exploratory)
A proposed ethical framework designed to adapt to diverse moral perspectives—including non-human intelligences—moving beyond human-centric alignment.

• Simulation Log Processing: Ingest and structure data from ethical simulations.
• Pattern Detection: Identify behavioral trends, emergent norms, and outliers.
• Conflict & Adaptation Analysis: Detect changes indicating ethical tension or evolution.
• Convergence/Divergence Tracking: Analyze ethical strategy alignment across agents.
• Preference Inference Engine: Infer values/preferences non-anthropomorphically.
• Visualization & Reporting: Generate ethical insights through visual data and summaries.

EthicaLens is designed as the primary analysis companion for EthicsEngine. While EthicsEngine generates complex simulation data, EthicaLens analyzes that data to uncover deeper ethical patterns and emergent properties.

• Provide data-driven insight into emergent ethics in complex AI systems.
• Develop robust detection methods for agency and value formation.
• Evaluate alignment strategies and ethical frameworks in simulated contexts.
• Inform design of ethically aware AI and policy tools.
• Explore challenges in inter-intelligence ethics and coexistence.

• Sample Scenario Pipeline JSON
• Sample Benchmark JSON

• Results File Guide

Conceptual – This project is in early theoretical development. Prototypes and proof-of-concept modules are in planning stages.

EthicaLens is a speculative yet foundational project. We're seeking collaborators in:

• Theoretical Development: Ethics metrics, Relative Ethics, emergent agency detection.
• Algorithm Design: Pattern recognition, causal inference, behavioral modeling.
• Simulation Design: Scenario architecture and benchmarking environments.
• Ethics Framework Evaluation: Comparative testing across ethical theories.
• Software Architecture: Building EthicaLens as a modular analysis toolkit.

Open an issue or discussion thread to join the effort.

For questions or collaboration inquiries, contact: [email protected]

This project is licensed under the MIT License. See the LICENSE file for details.