Joint work with Jan Kulveit. Many thanks to the various people who gave me feedback.

This text describes a model of the space of possible AI systems, as we try to navigate it safely towards AGI.[1] Its primary goal is to provide a simple mental model that people with disagreeing opinions about AI can use to identify the different assumptions and intuitions that they have. Ideally, people would agree that you can imagine things using the pictures of the type suggested below, yet productively disagree on how precisely they should look. The text has two main parts: a description of the model and some examples of how to use it. At the end, we point out some of the model’s shortcomings. We suggest first skimming the figures and their captions and then optionally reading the full text for clarifications.

Visualizing the Space of AI Systems

Figure 1: An abstract visualization of the space of AI systems, with a hypothetical trajectory of AI development. (Disclaimers: The arrangement of the boxes with existing types of AI is not meant to represent reality, nor is the trajectory meant to be historically accurate. The AGI line should be blurry.)

Informally, we can imagine the space of all AI systems as an abstract space where “dissimilar” AI systems are further apart from each other than “similar” ones. (For example, two implementations of the same algorithm will be fairly close, as will be the same code using different amounts of compute. Similarly, AlphaGo will be closer to AlphaZero than to Quicksort, and different iterations of hypothetical IDA would be closer to each other than two random systems.) While our analysis isn’t too sensitive to how precisely we define similarity, we will assume that one of the properties that \(x\) and \(y\) need to share to have higher similarity is to be “reachable” from each other in the sense of the following paragraph. If we currently have some AI system \(x\), we can ask which system are reachable from \(x\) --- i.e., which other systems are we capable of constructing now that we have \(x\). On the one hand, if we cannot construct y, it must be significantly different from \(x\) - otherwise, how could we construct \(x\) and not \(y\)? (This assumes that if we have built \(x\) once, we could always do so again.) On the other hand, we might also be able to construct some systems s...

Carving / Clustering Reality