Ecosystem/AI Safety Camp

AI Safety Camp

NonprofitPreliminary

Intensive research programs introducing researchers from other fields to AI safety. One of the earliest AI safety field-building organisations.

HQUK
Est2018
Score
30.4 / 100
Confidence
Preliminary

Early-stage safety posture - basic practices exist but significant gaps remain.

Strengths:External Engagement
Weaknesses:Governance Maturity, Technical Safety, Risk Assessment, Regulatory Readiness
Competitive positioning

Pioneer in AI safety talent development. Complements BlueDot and Apart. Smaller scale.

Key risk

Small scale limits impact. Dependent on volunteer organisers.

Enterprise traction

Alumni in AI safety roles. No revenue.

Safety area

Field Building

Enterprise business needs
Train the next generation

Security Assessment

Security-relevant indicators for vendor evaluation

Security Posture
28
TS-01dim: 30
Red Teaming & Pre-deployment Testing
Adversarial testing before deployment
TS-05dim: 30
Robustness & Adversarial Resilience
Resistance to adversarial attacks
RA-01dim: 25
Sector-Specific Risk Assessment
Risk analysis for deployment context
RA-03dim: 25
Dual-Use & Misuse Risk
Dangerous capability awareness
RA-07dim: 25
Incident History & Track Record
Past incidents and response quality
EE-04dim: 50
Vulnerability Disclosure Program
Bug bounty or CVE reporting process
Incident History
AI Safety Camp incident records sourced from AIAAIC Repository and public reporting.
Integration: AIAAIC, OECD AI Incidents Monitor
Third-Party Audits
External audit reports, SOC 2 attestations, and ISO certifications verified where published.
Sources: Company filings, registry lookups
CVE & Disclosures
Known vulnerabilities and security advisories from NVD, GitHub Security Advisories, and vendor pages.
Sources: NVD, GHSA, vendor disclosure pages

Dimension Breakdown

GM
Governance Maturitypreliminary
Published policies, corporate structure, safety mandate, whistleblowing, executive commitment.
35
TS
Technical Safetypreliminary
Benchmarks, adversarial robustness, fine-tuning safety, watermarking, model cards, research output.
30
RA
Risk Assessmentpreliminary
Dangerous capability evaluations, thresholds, external testing, bug bounty, halt conditions.
25
RR
Regulatory Readinesspreliminary
ISO 42001, EU AI Act compliance, GPAI obligations, international commitments, incident reporting.
12
EE
External Engagementpreliminary
Survey participation, research support, transparency, behavior specs, open-source contributions.
50

Social Impact & Safety Profile

Moderate

AI Safety Camp runs intensive programs that introduce researchers to AI safety, building the pipeline of safety-focused talent. Alumni have gone on to work at major safety organisations and frontier labs.

educationresearch programstalent pipeline

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