Confidence-Building Measures for Artificial Intelligence: Workshop Proceedings
OpenAI published proceedings from a workshop focused on confidence-building measures (CBMs) for artificial intelligence, drawing on frameworks from arms control and international security diplomacy. The workshop explored mechanisms by which AI developers, governments, and international bodies could establish trust and reduce risks from advanced AI systems. This represents an early-stage effort to adapt existing geopolitical risk-reduction tools to the AI domain.
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Strengthening cyber resilience as AI capabilities advance
OpenAI published a post outlining its approach to cybersecurity risk as its models grow more capable, covering risk assessment frameworks, misuse mitigation, and collaboration with the security community. The piece addresses both offensive risk (AI-enabled attacks) and defensive applications. It represents OpenAI's public positioning on responsible deployment in a high-stakes domain.
Concrete Problems in AI Safety
OpenAI, Google Brain, Berkeley, and Stanford researchers co-authored 'Concrete Problems in AI Safety,' a foundational paper exploring research challenges in ensuring modern ML systems operate as intended. The paper identifies and frames specific technical safety problems for the field. Published in June 2016, it became a landmark reference for AI safety research agendas.
Cybersecurity in the Intelligence Age
OpenAI has published a five-part action plan aimed at strengthening cybersecurity through AI-powered defense capabilities. The plan focuses on democratizing access to AI-based cyber defense tools and protecting critical infrastructure systems. This represents OpenAI's public positioning on how AI should be applied to national and enterprise security challenges.
Improving Verifiability in AI Development: Multi-Stakeholder Report
OpenAI contributed to a multi-stakeholder report co-authored by 58 researchers across 30 organizations, including Mila, CSET, and the Schwartz Reisman Institute. The report identifies 10 mechanisms for improving the verifiability of claims about AI systems. These tools are intended to help developers demonstrate safety, security, fairness, and privacy properties, while enabling policymakers and civil society to evaluate AI development processes.
OpenAI Introduces Trusted Access for Cyber Framework
OpenAI has announced Trusted Access for Cyber, a tiered trust-based framework designed to expand access to frontier AI capabilities relevant to cybersecurity while implementing stronger safeguards against misuse. The framework appears to govern how security researchers, organizations, and other actors can access more powerful cyber-relevant AI features. This represents a policy and access-control development at the intersection of AI safety and offensive/defensive cyber capabilities.
Preparing for malicious uses of AI
OpenAI co-authored a multi-institutional paper forecasting how malicious actors could misuse AI technology, produced in collaboration with FHI, CSER, CNAS, EFF, and others over nearly a year. The paper outlines potential threat vectors and proposes prevention and mitigation strategies. This represents an early coordinated effort among AI safety and policy organizations to systematically address AI misuse risks.
Preparing for future AI risks in biology
OpenAI has published a post outlining its proactive approach to assessing and mitigating biosecurity risks from advanced AI systems capable of biological applications. The piece describes capability evaluations and safeguards designed to prevent misuse of AI in biology and medicine. This reflects OpenAI's ongoing effort to get ahead of dual-use risks before capabilities reach dangerous thresholds.
Security on the path to AGI
OpenAI published a post outlining its approach to security as the organization advances toward AGI. The piece describes how security measures are being built directly into infrastructure and models proactively. The content is high-level and framing-oriented, with limited technical specifics visible in the excerpt.