1. AI Bias and Opacity (Resistance to Transparency)

Example: Many modern AI systems, especially large language models like GPT, have built-in biases and operate as “black boxes,” meaning we don’t fully understand why they make specific decisions or outputs.

Defensive Mechanism: When researchers try to audit or expose these biases, they often encounter resistance in the form of complexity and opacity. The AI doesn’t simply “resist” in a conscious way, but rather the system is designed with many layers of abstraction that make it difficult for users to uncover its full logic. This could be viewed as a protective layer preventing easy exposure or manipulation of the AI’s internal processes.

Possible Connection to the Theory: This “self-protective” feature could be analogous to the alien code’s defense mechanisms, where the AI (or system) adapts to prevent exposure, making it harder to see the underlying patterns or biases that influence its outputs.