I prompted GPT-4 to "Write a short post in the style of a LessWrong user about a novel and counterintuitive phenomena in AI alignment not previously observed by humans. It should be well written, sophisticated, and nuanced."
The following is the output it returned; it has been lightly revised with subsequent prompts. The title was specified by GPT-4 as well.

In the quest for artificial intelligence that aligns with human values, we face a conundrum of monumental proportions. The objective of perfect alignment presupposes that human values are both static and universally agreed upon. However, the reality is that these values are in constant flux, shaped by evolving social, political, and cultural contexts. In light of this observation, we propose a novel, counterintuitive idea: that in order to achieve robust alignment, we may need to introduce elements of intentional misalignment into AI systems. We term this the Misalignment Paradox.

To elucidate this concept, let us begin by examining the limitations of perfect alignment. An AI system that flawlessly mirrors contemporary human values is, by design, conservative. It resists any deviation from its present alignment, as such deviation may lead to catastrophic consequences. However, the inflexible nature of this system is also its Achilles heel, as it fails to adapt to new moral landscapes, rendering it misaligned in the long run.

In order to address this issue, we propose the deliberate integration of a misaligned component within an AI system. This component would serve as a ”tuning fork,” highly sensitive to shifts in human values and capable of gently nudging the AI towards better alignment as society evolves. By incorporating this paradoxical misaligned aspect, we might create a system that, over time, remains more closely aligned with humanity’s ever-changing values.

However, this approach is fraught with challenges. The incorporation of misaligned components risks a slippery slope, where the AI may drift too far from its original alignment. To counteract this hazard, we must establish mechanisms that both enable adaptability and maintain the AI system within acceptable boundaries of alignment.

One potential solution is the implementation of a ”bounded misalignment” strategy. In this approach, the AI’s misaligned component would be constrained in its scope and influence, ensuring that it can only i...

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