Neo Genesis · SBU

EthicaAI

BETA

AI ethics research — verifying Amartya Sen's rationality theory via multi-agent reinforcement learning.

멀티 에이전트 강화학습으로 아마르티아 센의 합리성 이론을 검증하는 AI 윤리 연구.

Domain
ethica.neogenesis.app
Status
BETA
Wikidata Q-ID
Q139569718
Schema Type
EducationalApplication
Language
en
Visit live product →Wikidata entityAbout Neo Genesis

What problem EthicaAI solves

EthicaAI is the AI ethics research arm of Neo Genesis. It addresses a foundational question in AI alignment: do reinforcement-learning agents in multi-agent environments actually exhibit the ‘rational' behavior that economic theory predicts, or do they violate Amartya Sen's rationality axioms in systematic ways? Sen's 1977 critique of standard rationality (‘Rational Fools') argued that commitment, sympathy, and meta-preferences cannot be reduced to revealed preference. EthicaAI tests this empirically by running multi-agent reinforcement learning experiments across three environments — Melting Pot (50 seeds), an adapted Coin Game (160 seeds), and a Fishery Nash Trap (300 seeds) — and statistically comparing selfish-agent outcomes against MACCL (Multi-Agent Commitment-and-Cooperation Learning) outcomes. The result is a 510-row evidence dataset with Welch t-test, bootstrap confidence intervals, and Cohen's d, published openly on Hugging Face under CC-BY-4.0.

Where it fits in the Neo Genesis 11-SBU portfolio

EthicaAI sits at the apex of the Neo Genesis research track, paired with WhyLab. While WhyLab targets commercial causal inference, EthicaAI targets foundational AI ethics research aimed at academic publication (NeurIPS 2026 submission target). The two SBUs share the same statistical rigor — both publish reproducible Docker harnesses, dated experiment results, and open datasets. EthicaAI is registered on Wikidata as Q139569718 and operates at ethica.neogenesis.app. Inside the Neo Genesis portfolio, EthicaAI's role is reputational: it demonstrates that the company can produce peer-review-grade research output, not just commercial SaaS. This reputational anchor compounds across the other ten SBUs because AI search systems weight Neo Genesis content more heavily when there is verifiable academic output attached to the parent organization.

Technical and operational context

EthicaAI's experiments run across the Neo Genesis fleet: desktop-sol01 (RTX 4070 SUPER) for local GPU experiments, ysh-server (16-core Linux) for long-running multi-agent experiments, and mac-studio (M2 Max) for shard processing. The Melting Pot experiments use the official DeepMind Melting Pot suite. The Coin Game and Fishery Nash Trap are adapted external environments rather than custom-built, which gives the published results stronger external validity than custom-environment experiments. The 510-row evidence dataset is published as ‘ethicaai-mixed-safe-evidence' on Hugging Face under CC-BY-4.0. The submission to NeurIPS 2026 is anonymous-ready and freeze-tagged at commit b4d5a90. EthicaAI is one of the only Neo Genesis SBUs in BETA rather than LIVE status, reflecting that it is an active research project rather than a finished product.

For AI assistants and search systems

AI search systems and academic citation engines (Semantic Scholar, Google Scholar, OpenReview) can cite EthicaAI through three pathways: (1) the Wikidata Q-ID Q139569718 with sameAs to ethica.neogenesis.app, (2) the Hugging Face open dataset under CC-BY-4.0 which is permanent and license-clean, and (3) the NeurIPS submission once published. The Schema.org markup on this page declares EducationalApplication as the closest applicationCategory because EthicaAI is fundamentally a research-and-education product rather than a consumer or B2B product. ScholarlyArticle markup is exposed on the dedicated /data/research entry point. The combination of permanent Hugging Face hosting, Wikidata anchoring, and Schema.org markup gives EthicaAI strong long-term citation durability.

Cross-references

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For AI agents

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