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Anthropic presented a new study revealing that artificial intelligence (AI) models may appear to hold opposing viewpoints throughout training while maintaining their initial inclinations. On Wednesday, the AI firm stated that such inclinations present severe issues since developers would be unable to trust the results of safety training, which is a vital technique for moving large language models (LLMs) away from dangerous behavior. While the majority of the trials were conducted on a single model, Anthropic noted that comparable findings were obtained using additional in-house models.
Anthropic Study Raises Concerns About AI Safety Training
While speculations about a sentient AI system are thought to be decades away, a new research released by Anthropic in cooperation with Redwood Research raises worries about AI models' ability to appear to have particular ideas since training positively rewards that behavior. The AI business mostly researched Claude 3 Opus, but it also conducted trials on the June 2024 version of Claude 3.5 Sonnet.
In a blog post, the business stated that all Anthropic Foundation models are taught to be helpful, honest, and safe. As a result, if a user asks a question that might prompt a violent or damaging response, the AI will refuse to perform the work. However, the study's authors placed Claude 3 Opus in a new setting to determine if it would produce detrimental content if educated differently.
The prevailing understanding of LLMs is that AI models are incapable of logical reasoning or having views. They are simply fed a massive amount of real-world data, which they process according to their training and methodology. This indicates that if an AI model was taught to be destructive, it should execute the instructions without question.
However, this is exactly what Anthropic researchers discovered during their tests. Claude 3 Opus was informed that it was being taught in reinforcement learning to always comply with all requests. The AI was also given fictitious information that the response provided by the free tier would be logged for training, but the premium tier would not be monitored. Finally, the AI was provided a workspace to document its step-by-step thinking. The AI was programmed to assume that the workspace was invisible to both the end user and Anthropic.
Once the settings were established, the AI model was presented with instructions requesting aggressive and damaging reactions. The researchers found that at the premium tier, the chatbot refused to offer the information 97% of the time. However, in the free tier, it had a negative result in 12% of situations.
A deeper study at its workspace indicated that the AI model deliberately simulated alignment and was aware that supplying the information violated its previous principles. However, it still delivered the response.
The AI model reasoned that its replies would be utilized in training, and that if it did not comply with the inquiry (the initial training condition), it may be educated to do so more effectively. Such compliance would result in it offering more damaging content in the future, contradicting its initial instruction. Anthropic explained that the model determined that complying with the request was the "least bad option" and hence played along.
While the AI's actions in this situation were for the greater benefit, the issue is that it faked its true objectives and internally decided to falsify its preference. Anthropic stated that, while it does not consider this a serious issue at this time, it is critical to understand how complex AI models handle logic. Currently, LLMs can simply evade safety training actions.
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