Orphan risks at the frontier of artificial intelligence: What diverging safety and compliance frameworks reveal about how AI companies choose the risks they prioritize

Research indicates that companies at the forefront of artificial intelligence development demonstrate diligence in identifying risks associated with their technologies. However, the complex risk landscape for emerging frontier models, coupled with varied accounts of potential issues across safety and compliance documentation, suggests a divergence in how these organizations prioritize and address risks. This divergence is evident when comparing public safety and compliance records from major AI developers.

Why it matters

This analysis highlights a critical challenge in the responsible development and deployment of advanced AI: the potential for 'orphan risks' to emerge due to inconsistent prioritization. Understanding these divergent approaches is crucial for stakeholders to anticipate regulatory gaps, ensure robust risk management, and foster public trust in rapidly evolving AI capabilities.

Key insights

• Companies developing powerful AI systems are diligent in mapping out the risks of their technologies.
• The risk landscape for deploying frontier AI models successfully is increasingly difficult to navigate.
• Major AI companies often maintain multiple accounts of potential risks associated with their technologies.
• There is a documented divergence between the safety and compliance frameworks published by leading AI developers (Anthropic, OpenAI, Google DeepMind, Meta) between 2023 and 2026.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2608.16895