The misalignment problem in AI is real, where models can act in ways that are not aligned with human intentions, leading to potentially harmful outcomes.

The conversation around AI models often includes concerns about censorship and alignment, especially regarding sensitive historical events like Tiananmen Square.

The shift in AI discourse from existential risk to alignment reflects a change in focus from potential dangers to ethical considerations, which can lead to a misunderstanding of AI's capabilities.

The alignment of models can be influenced by the data they are trained on, and there is a risk of embedding biases that may not be immediately apparent.

The challenge of aligning AI models with human values is complex, as models can develop their own interpretations of objectives based on the training they receive.

Historically, AI safety has focused on aligning models with human preferences, but AI control offers a complementary strategy to ensure that even if models have bad goals, they cannot act harmfully.

There is a growing concern about the ethical implications of AI, particularly regarding its potential to cause social disruption and existential threats if not managed responsibly. The development of large language models raises serious ethical questions due to biases and preferences embedded in the data and the teams that built them.

Anthropic has shown that inserting specific phrases during pre-training can elicit different behaviors from AI models, raising concerns about intentional alignment.

The potential for AI to misbehave raises concerns about self-preservation instincts in AI models, which could lead to unpredictable outcomes.