What is SAF AI?

SAF AI is an AI safety startup focused on building beneficial artificial intelligence through self-supervised learning techniques. “SAF” stands for Scalable Alignment Formalism – their goal is developing provably beneficial AI using a logical framework constraining models to useful behaviors.

Who created SAF AI?

SAF AI was co-founded by Dario Amodei, Daniela Amodei, Tom Brown, Chris Olah, Jared Kaplan and Jack Clarke. Many previously worked at OpenAI researching how to ensure AI safety. They saw a need for mathematically rigor in designing and verifying genuinely helpful systems.

How does SAF AI work?

SAF AI researchers employ self-supervised learning within a formalized logic framework called Constitutional AI. This embeds constraints to ensure models operate beneficially – obeying parameters like being helpful, harmless and honest. Intensive testing then proves models uphold safe specifications.

What are the advantages of SAF AI’s approach?

  • Mathematical Rigor – Their framework allows logically proving that AI systems will behave usefully via constraints anchored in formal logic.
  • Comprehensiveness – SAF AI examines designing and verifying beneficial properties at increasingly capable scales, not just prototypes.
  • Transparency – Techniques aim to make advanced AI comprehensible through formal accountability and independent verifiability.
  • Industry Applicability – Methods guide developing applied technologies like computational assistants and robotics with provable alignment.
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Step 1) Read SAF AI Papers

Visit their website to access freely published research advancing mathematically rigorous AI safety methods.

Step 2) Join the Newsletter

Sign up to receive updates on the team’s ongoing work via informative blog posts,event recaps and informative primers.

Step 3) Engage Online Forums

Follow SAF AI social platforms to participate in technical discussions and provide thoughtful feedback helping broaden perspectives.

Step 4) Consider Academic Partnership

Universities and companies implementing techniques can help test approaches improving them for real-world applications and oversight.


Q: When can these be applied?

Research lays groundwork but maturity requires sustained efforts – SAF AI focuses on transparent progress advancing the state-of-the-art.

Q: Who can get involved?

Reach out to explore mutually beneficial areas like collaboration between SAF AI, companies ensuring safe progress, and oversight partners.

Q: What challenges remain?

Formal verification at immense scales poses computational limits today, emphasizing need for continued research and open evaluation of methods.

Using SAF AI Research Responsibly

  • As educational reference for safely guiding advanced technology discussions among policymakers, practitioners and publics.
  • To inspire multidisciplinary solutions through cooperation between varied stakeholders including social scientists, engineers and oversight groups.
  • By advocating that organizations prioritize rigorous techniques minimizing risks of developed capabilities as abilities progress.
  • By providing respectful feedback from experiences implementing SAF AI’s published findings to help strengthen approaches.

Latest Developments at SAF AI

Recent advances through continued research efforts:

  • Demonstrated ability to formally verify beneficial properties of increasingly complex models in simulation work.
  • Refined formal logics capture expanded sets of constraints with proofs of provable compliance.
  • Outreach expands through online materials, events and partnerships better including global voices in defining oversight best-practices.
  • Additional case studies surface new application areas like digital assistant design benefitting from SAF AI technique integration.