Algon 33
Rahul Sharma
David Akpan
We want to help at least 100 top talents across the world to transition into full-time careers in AI safety/governance and help make AI safe for all
Sidharth K
Testing a geometric model of consciousness through mechanistic interpretability
Giuseppe Dal Pra
Combining, iterating and refining best-practice epistemic democratic AI Governance with a documentary and international strategy to scale a UK citizen assembly
Lucille Grant
A reproducible multi-model study of proxy exploits, evaluator defects, distribution shifts, and withheld tests
Evgeniy Galuschak
Testing whether powerful AI systems can remain useful while their ability to affect the external world is structurally constrained.
Abeer Sharma
AISHK will run an in‑person weekend sprint hub for elite finance talent and host the winning team during the Apart Fellowship.
Allen Lu
Ethan Roland
We want to measure & prevent drift in model alignment characteristics during RLVR and continual learning.
Kate Lowry
Keep AI Whistleblowers Alive
SS
IBBIS
Defining which sequences are dangerous enough to screen for, so providers and regulators screen consistently
Constance Li
Animal Welfare Midtraining Data Creation
Sharo Saadi Hassan
Scaling open-source AI safety content, localized research breakdowns, and web tools for the Kurdish community specially and world generally
Ruslan Bayandin
A negative result on behavioural testing, a narrow positive one on cryptographic execution proof, and 8 independent attestations anyone can check
Nathaniel Opoku
A three-week virtual fellowship where young Africans learn about AI safety and turn big ideas and catastrophe scenarios into videos the public can understand.