GPT-4 explains shard theory after minimal prompting; it does a surprisingly good job (and I’m faintly surprised it knows so much about it):
Shard theory is a conceptual framework proposed by Alex Turner [Edit by me: And Quintin Pope!] to describe how an AI’s values or “shards” can emerge from its interactions with the environment during the learning process. The theory is an attempt to explain how complex value systems might arise in advanced AI systems without being explicitly programmed.
Key Aspects of Shard Theory
1. Value Learning: Shard theory suggests that an AI learns values by interacting with its environment and receiving feedback, such as rewards and punishments. These interactions lead to the formation of “shards,” which are small pieces of value or preference that the AI acquires over time.
2. Shard Composition: The AI’s overall value system is composed of multiple shards that it has picked up from different contexts within its environment. These shards can be thought of as heuristics or rules of thumb that guide the AI’s behavior.
3. Behavioral Influence: Shards influence the AI’s behavior by affecting its decision-making process. When faced with a choice, the AI weighs the relevance and strength of each shard to come to a decision.
4. Emergent Complexity: The theory posits that the AI’s value system can become quite complex as it accumulates more shards, leading to sophisticated and nuanced behavior that may not have been directly programmed by the AI’s designers.
5. Alignment Implications: Shard theory has implications for AI alignment, as it provides a framework for understanding how an AI’s values develop and change over time. This understanding could be crucial for designing AI systems that align with human values and for predicting how AI values might diverge from human expectations.
6. Research Applications: Turner’s work on shard theory contributes to the broader field of AI alignment by offering a model for how value systems can emerge in AI. It also provides a potential avenue for developing AI systems that learn to value the right things by carefully curating the environment and feedback they receive.
Shard theory is part of ongoing research efforts to understand and guide the development of AI value systems. It aims to ensure that as AI systems become more autonomous and capable, they do so in a way that is beneficial and not harmful to humanity.
and I’m faintly surprised it knows so much about it
GPT-4 via the API, or via ChatGPT Plus? Didn’t they recently introduce browsing to the latter so that it can fetch Web sources about otherwise unknown topics?
GPT-4 explains shard theory after minimal prompting; it does a surprisingly good job (and I’m faintly surprised it knows so much about it):
It’s better than the first explanation I tried to give you last year.
GPT-4 via the API, or via ChatGPT Plus? Didn’t they recently introduce browsing to the latter so that it can fetch Web sources about otherwise unknown topics?
ChatGPT but it wasn’t displaying the “web browsing” indicator, so I think that means it wasn’t doing so?
You’re right; I’d forgotten about the indicator. That makes sense and that is interesting then, huh.