Furkan Elmas
A concrete safety experiment to detect when an LLM's local reasoning stops behaving like a single stable executive stream, using scalar hazard signals.
L
Paula Coelho
A free platform enabling researchers in emerging economies to collaborate, innovate, and build deep-tech and Responsible AI projects
Mirco Giacobbe
Developing the software infrastructure to make AI systems safe, with formal guarantees
A simulation engine for modeling system deviation, collapse trajectories, and stability dynamics in advanced AI systems.
Gergő Gáspár
Help us solve the talent and funding bottleneck for EA and AIS.
Douglas Rawson
Mitigating Agentic Misalignment via "Soul Schema" Injection. We replicated a 96% ethical reversal in jailbroken "psychopath" models (N=50).
Miles Tidmarsh
Training AI to generalize compassion for all sentient beings using pretraining-style interventions as a more robust alternative to instruction tuning
Nicole Mutung'a
Funding research on how AI hype cycles can drive unsafe AI development
Early-stage work on a small internal-control layer that tracks instability in LLM reasoning and switches between SAFE / WARN / BREAK modes.
Carlos Arleo
WFF: Open-Sourcing the First Empirically-Proven Constitutional AI for Democratic Governance
Sean Sheppard
The Partnership Covenant Hardware-enforced containment for superintelligence — because software stop buttons are theater
Martin Percy
An experimental AI-generated sci-fi film dramatising AI safety choices. Using YT interactivity to get ≈880 conscious AI safety decisions per 1k viewers.
Chris Canal
Enabling rapid deployment of specialized engineering teams for critical AI safety evaluation projects worldwide
Jade Master
Developing correct-by-construction world models for verification of frontier AI
David Rozado
An Integrative Framework for Auditing Political Preferences and Truth-Seeking in AI Systems
Building an operator-based simulation environment to analyze stability, divergence, threshold failures, and collapse modes in advanced AI-related systems.
Adam Morris
Train LLMs to accurately & honestly report on their internal decision-making processes through real-time introspection