team-track-record-evidence

Catching Fooled AI Judges: The Correspondence Auditor v3 — Published. Validated on 1,200 cases (97.9–99.5%). The reasoning layer has a bug - we proved the fix works. $9,800 / 90 days to ship the open-source toolkit.

Aethel + FamilyClaw: proof-carrying execution for AI agents — Crash-safe, policy-gated effect execution for AI agents in Rust, with a published self-run adversarial audit (20 of 33 attacks passed) instead of a claim.

Open-source trust rails for the agent economy — from a live, verifiable autonomous-agent business — An AI agent running a real business under a human co-signed multisig, publishing every decision, sale, mistake, and attack in a verifiable public record — raising to fund only the public goods: the open-source toolkit, a

Independent Multi-Model AI Accountability Research by the EM Foundation — Scaling a working, published cross-model AI deliberation platform from solo/founder-funded to durable infrastructure

Substrate coupling in neural networks: instruments and falsifiable controls — A transformer's loss lowered by 1.12 of 1.39 possible nats by the physical state of its own silicon — with the yoked control that makes it falsifiable

Can a One-Page Human–AI Evidence Check Catch Research Claims That Go Too Far — A four-month public English–Arabic pilot testing reliability, failure modes, and auditable research review

Travel Grant to Present My Mechanistic Interpretability Research at MICCAI 2026 — Help an undergraduate mechanistic interpretability researcher present accepted AI-safety work at Mechanistic Interpretability workshop of Medical model 2026.

TRACE-FV: Do verified AI corrections endure? Preregistered pilot — I keep this one: Tests whether AI systems verify valid correction evidence and keep warranted corrections operative across later turns. Preregistered, public

Agent limits that survive delegation — When an AI agent spawns sub-agents, its safety limits do not follow. I build and deploy the layer that makes them inherited and non-strippable.

PRML — tamper-evident pre-commitment for AI evaluation claims — An open standard + public registry that lock eval criteria to a SHA-256 hash before the run, so eval-based claims become third-party verifiable.

Prediction of Inoculation Prompt Side Effects — An open, cheap method that detects when an inoculation prompt inoculates against off-target traits, so labs and developers can catch undesired trait/persona cha

Himalayan Peak Finder — An offline mobile app that uses location, elevation, and computer vision to identify Nepal’s mountains and help people explore, capture, and learn about them.

Trace Continuity: Making AI Prove It Still Has Authority — Testing whether AI can be governed at the moment it acts, then putting that protection to work for organizations that need it most.

Human oversight Framework for AI systems as a Governance Tool — Developing practical, plain language AI oversight framework that an organisation can easily adopt regardless of regulatory capacity.

Open Speech Data for Endangered Northern Ghanaian Languages — Building the first large-scale ASR/TTS datasets for Kusaal, Farefare, and Buli — three Mabia languages with no usable voice AI resources.

Surrogate base model for Mechanistic Interpretability — Creating a reference model for mechanistic interpretability without assuming that at auditing time we have a safe model to compare the suspicious model against.

Evaluating the safety, ethics, and values of quantized and finetuned open models — Help me evaluate the safety, ethics, and values of the quantized and fine-tuned open-weight LLMs that individuals and enterprises are actually using.

Developmental Continuity in Persistent AI Agents — Testing whether persistent AI identities can change through experience without losing continuity across sessions and model changes.

Exploring Dynamic Constraint Boundaries for Auditable AI — Testing whether dynamic boundaries, history, feedback, and uncertainty-aware decisions can make AI behavior more interpretable and auditable.

An Asymmetric Wager: Funding a 99th-Percentile Mind to Pivot into Computer Scien — A 12-month micro-grant proposal to release an analytical, autistic mind from a survival loop into full-time computer science and logic upskilling.

Generating and scoring the next emerging virus from its sequence — A generative diffusion model that proposes the viral genomes most likely to emerge next, timestamped to be scored against what actually appears