LawZero
LawZero is a Montréal-based nonprofit AI research organization founded by Yoshua Bengio, launched on 3 June 2025 with $30 million in philanthropic funding. Its mission: develop technical solutions for highly-capable, safe-by-design AI systems — specifically, the “Scientist AI” approach Bengio has championed since 2024.
The name nods to Asimov’s “Zeroth Law of Robotics” — that no AI system should harm humanity. The structural choice (nonprofit, philanthropic-funded, no commercial product roadmap) is a deliberate response to what LawZero argues are the inadequate safety incentives at frontier commercial labs.
Founding and Funding
- Founder & scientific lead: Yoshua Bengio — Turing Award winner, Nobel-Prize-adjacent recognition (most-cited living scientist), and chair of the International AI Safety Report
- Launch date: 3 June 2025
- Location: Montréal, Quebec (closely associated with Mila — Quebec’s AI institute, where Bengio is also based)
- Initial funding: $30M
- Funders include: Jaan Tallinn (Skype founding engineer), Eric Schmidt (former Google CEO), Open Philanthropy and the Future of Life Institute, plus other AI safety funders
Mission
Per LawZero’s own framing:
Current frontier AI systems are becoming more capable and autonomous, yet they remain opaque and misaligned with human goals. These systems are already showing many early signs of deception behaviors and self-preservation, creating growing uncertainty about how these systems will behave with even greater abilities to strategize autonomously.
LawZero positions itself to do work the commercial labs structurally cannot: build safety-first, non-agentic AI insulated from market and government pressures.
Technical Approach: Scientist AI
LawZero’s technical research operationalizes the Scientist AI approach — a research direction already catalogued in the wiki’s Shallow Review 2025 agenda. The defining principle (per Bengio):
Understanding — even of arbitrary depth and scope — can be disentangled from preference over how the world unfolds.
That is, an AI can be highly intelligent without being agentic. The architecture has:
- Generator component held accountable by a neutral estimator — probabilistic predictions with transparent, auditable reasoning and no hidden objectives
- Contextualization — separating facts from opinions in training data
- Consequence invariance — preventing feedback loops about downstream outcomes from shaping behavior
A featured 2025 LawZero paper credits Damiano Fornasiere, Oliver Richardson, Gaël Gendron, Iulian Serban, and Bengio.
Theory of Change
LawZero argues a Scientist AI system can serve four roles:
- Accelerate scientific breakthroughs without taking action in the world
- Provide guardrails for agentic AI — double-checking proposed actions before they’re enacted
- Advance the science of AI risk — formal tools for understanding what current systems are doing
- Help build safer agentic superintelligence later, when alignment science is more mature
The Scientist-AI-as-guardrail framing is the most novel part: rather than try to align agentic AI directly, LawZero argues you should first build a non-agentic AI that is provably safe, and then use it to oversee agentic systems. This places LawZero in the AI control / scalable-oversight research neighborhood, but with a distinctive non-agentic anchor.
Significance
LawZero is the most-funded nonprofit AI safety lab founded in 2025 and arguably the highest-profile new institution in the field that year. Three structural shifts it represents:
- Scientist credibility behind nonprofit safety work — Bengio’s stature gives the model legitimacy that EA-adjacent labs have struggled to build with mainstream ML researchers.
- Non-agentic AI as a serious research direction — moves the conversation beyond “align the agents” to “maybe don’t build agents (yet).”
- Permanent capacity for safety-first frontier research — distinct from technical-evaluation work at the AI Safety Institutes and from policy-think-tank work at FLI / CLTR / CeSIA.
Connection to This Wiki
- Institutional home of the Scientist AI research agenda (existing SR2025 entry).
- Closes a gap: the wiki had Bengio’s authority work (international-ai-safety-report) and his theoretical alignment framing (scientist-ai), but not the lab actually building it.
- Belongs to the same post-2023 institutional layer as the AISIs but with a distinct nonprofit-research profile.