AI assisted tools for scaling human review
See our projects
Atlas Computing is an R&D nonprofit prototyping AI-powered tools to generate formal specifications. We're empowering engineers to verify code easily and develop software that’s built for trust.
We aim to bridge the gap between human intent and machine output.
Risk
AI entrenches biases from an unequal world, while hiding them under a veneer of objectivity
Solution
We need to empower human deliberation to set rules for AI outputs.
Risk
Future AI could pursue our directives in dangerous and unpredictably inhuman ways
Solution
We need to be able to set objective constraints on AI systems
Risk
Stopping progress toward artificial general intelligence (AGI) prolongs all problems that AGI can solve
Solution
We need to build verifiable tools to solve today’s and tomorrow’s problems
How specification-driven AI works
As the outputs of AI systems become increasingly complex, human review systems (ranging from code review to regulatory approval) will become overwhelmed.
Instead, we envision a world where it is easy to set objective criteria that AI outputs should satisfy, and generative AI systems make it clear to humans that those criteria are met.
We're starting with making tools to generate formal specifications, as computer science already has a language for expressing and automatically verifying these objective criteria of software programs. This could reduce cybersecurity vulnerabilities and regulatory burdens that cost economies billions annually.
Specification-driven AI enables automated verification and compliance, letting humans focus on what an AI system should do, not worrying about if it's doing it.
We aim to bridge the gap between human intent and machine output
Human review exists on a spectrum, and as demands grow, traditional manual review alone won’t suffice - it's the most expensive and time consuming.
Read our 2-pager on scaling safety proofs of software or check out the projects page to see our other efforts as well.
