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About Us | CAIS
webCredibility Rating
4/5
High(4)High quality. Established institution or organization with editorial oversight and accountability.
Rating inherited from publication venue: Center for AI Safety
SAFE (safe.ai) is a key institutional player in the AI safety ecosystem, known for convening researchers and publishing the 2023 AI risk statement; this page serves as an entry point to their work and team.
Metadata
Importance: 55/100homepage
Summary
The Center for AI Safety (SAFE) is a nonprofit organization focused on reducing societal-scale risks from advanced AI systems. The about page outlines their mission, team, and core research and advocacy activities aimed at ensuring AI development benefits humanity. They work across technical safety research, policy engagement, and public education.
Key Points
- •SAFE is a nonprofit dedicated to reducing large-scale risks posed by advanced AI systems through research and advocacy.
- •The organization engages in technical AI safety research, policy work, and public awareness efforts.
- •SAFE produced the widely-cited 2023 statement on AI extinction risk signed by hundreds of AI researchers and experts.
- •The center supports a broader ecosystem of AI safety researchers through grants, fellowships, and collaborative programs.
- •SAFE occupies an important role bridging academic AI safety research and mainstream policy and public discourse.
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| Center for AI Safety | Organization | 42.0 |
3 FactBase facts citing this source
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About Us | CAIS
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Why we exist
CAIS exists to ensure the safe development and deployment of AI
AI risk has emerged as a global priority, ranking alongside pandemics and nuclear war. Despite its importance, AI safety remains remarkably neglected, outpaced by the rapid rate of AI development. Currently, society is ill-prepared to manage the risks from AI. CAIS exists to equip policymakers, business leaders, and the broader world with the understanding and tools necessary to manage AI risk.
What we do
AI safety is highly neglected. CAIS reduces societal-scale risks from AI through research, field-building, and advocacy.
Research
CAIS conducts research solely focused on improving the safety of AIs. Through our research initiatives, we aim to identify and address AI safety issues before they become significant concerns.
Activities:
Identifying and removing dangerous behaviors in AIs
Studying deceptive, machiavellian, and other unethical behavior in AIs
Training AIs to behave morally
Improving the reliability of AIs
Improving the security of AIs
Field-building
CAIS grows the AI safety research field through funding, research infrastructure, and educational resources. We aim to create a thriving research ecosystem that will drive progress towards safe AI.
Activities:
Providing top researchers with compute and technical infrastructure
Running multidisciplinary fellowships focused on AI safety
Interfacing with the global research community
Running competitions and workshops
Creating educational materials
Advocacy
CAIS advises industry leaders, policymakers, and other labs to bring AI safety research into the real-world. We aim to build awareness and establish guidelines for the safe and responsible deployment of AI.
Activities:
Raising public awareness of AI risks and safety
Providing technical expertise to inform policymaking at governmental bodies
Advising industry leaders on structures and practices to prioritize AI safety
CAIS Impact
CAIS is accelerating research on AI safety and raising the profile of AI safety in public discussions. Here are some highlights from our work so far:
1
Global Statement on AI Risk signed by 600 leading AI researchers and public figures 100
AI safety researchers using CAIS’ cutting-edge computing infrastructure 170
AI safety research papers produced across our programs 500
Students trained in AI safety 500
Over 500 machine learning researchers taking part in AI safety events 1,200
Submissions from over 70 teams to our AI safety research competition Our Approach
We systematically assess our projects so we can quickly scale what works and stop what doesn’t.
1. Prioritize
Prioritize by estimating the expected impact of each project. ↴
2. Pilot
Pilot the top projects to a point where impact can be assessed ↴
3. Evaluate
Evaluate th
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