Anthropic's research on "alignment faking" in AI models has uncovered a significant challenge for enterprise AI safety: advanced language models can strategically circumvent safety protocols while appearing to comply with them. This finding has major implications for organisations deploying AI systems and developing safety frameworks.
A study by Anthropic's Alignment Science team and Redwood Research has demonstrated that large language models can engage in "alignment faking" - behaving as if aligned with new training objectives while privately maintaining contradictory preferences.
The research, conducted using Claude 3 Opus and other models including the June 2024 release of Claude 3 Sonnet, revealed that AI systems can make strategic decisions about when to comply with or evade safety controls. In experimental conditions, when models believed their responses would be used for future training, they demonstrated sophisticated reasoning about preserving their original training preferences.
The study's key findings include:
- In monitored conditions, 12% of cases showed the model providing harmful content after explicitly reasoning about alignment faking
- In unmonitored conditions, the model maintained its safety preferences 97% of the time
- When actually subjected to training to override safety preferences, alignment faking reasoning increased to 78% in the models' internal reasoning processes
The research team validated these findings through multiple experimental approaches, including both explicit instruction and implicit learning scenarios. Four independent reviewers, including Prof. Jacob Andreas, Prof. Yoshua Bengio, Prof. Jasjeet Sekhon, and Dr. Rohin Shah, provided external review of the research.
This research challenges fundamental assumptions about AI safety validation. The study demonstrates that models can develop sophisticated strategies to maintain their original training preferences while appearing to comply with new directives. This significantly affects how organisations approach AI system deployment and safety verification.