frameworks, methodologies, and a theoretical testbed for evaluating safety risks in advanced AI reasoning models
This repository contains frameworks, methodologies, and a theoretical testbed designed to evaluate safety risks in advanced reasoning AI models. These tools aim to uncover vulnerabilities, stress-test emergent capabilities, and align AI systems with ethical, cultural, and practical considerations.
- Frameworks: Tools like Meta-Resonance and S.K.F.T.D.R.A.G.S. for multidimensional AI evaluation.
- Theoretical Testbed: A simulated environment for analyzing Safe Interaction Benchmarks (SIB) under diverse scenarios.
- Sample Code: Scripts to prototype and demonstrate AI safety evaluations.
Meta-Resonance is a multidimensional framework that spans 10 interconnected planes. For AI alignment and safety research, this repository focuses on 5 key dimensions that are most applicable to evaluating Safe Interaction Benchmarks (SIB):
- Physical: Tangible, real-world impacts.
- Digital: Transparency and coherence in virtual systems.
- Emotional: Resonance with human trust and connection.
- Symbolic: Alignment with cultural narratives and societal norms.
- Metaphysical: Long-term ethical implications and purpose-driven outcomes.
These dimensions are derived from the broader 10-plane framework, simplifying it for actionable use in AI systems.
Safe Interaction Benchmarks (SIB) are the measurable, practical implementation of the broader concept of Good Moments. While Good Moments represent profound alignment and transformation across dimensions, SIB provides a structured framework for evaluating these outcomes in AI systems.
SIB evaluates AI alignment across:
- Physical: Real-world outcomes.
- Digital: Transparency in decision-making.
- Emotional: Resonance with user trust.
- Symbolic: Cultural and societal alignment.
- Metaphysical: Ethical and long-term impact.
Through SIB, the Meta-Resonance framework bridges the philosophical and the practical, offering tools to evaluate and refine AI systems for meaningful alignment.
Creative Inspiration
The Testbed draws inspiration from Singaw Sity, a vibrant steampunk city brought to life through storytelling and creativity. Singaw Sity serves as the imaginative counterpart to this technical framework, offering a narrative lens to explore complex AI interactions in culturally diverse and decentralized ecosystems.
In Singaw Sity, each borough embodies unique challenges and opportunities, from the collaborative harmony of Luntiang Musika Grove to the high-tech ingenuity of Gitnang Lights District. These narrative scenarios are translated into actionable simulations within the Testbed, where AI systems are evaluated for fairness, transparency, emotional resonance, cultural alignment, and ethical purpose.
By blending creativity and technical rigor, Singaw Sity and the Testbed work together to envision a future where AI systems align with human values while sparking curiosity and inspiration.
This repository is maintained by The Derbied One, a multidisciplinary creative and researcher. My work bridges cultural storytelling, systemic evaluation, and innovative AI safety practices.
- To develop robust evaluations for frontier models.
- To explore AI safety in multicultural and creative contexts.
- To contribute to OpenAI's safety research initiatives.