A case that whole brain emulation research is net-harmful by default

Graphical abstracts Summary A true human whole brain emulation would be very helpful to humanity. The WBE could increase their own intelligence through self-modification and then somehow prevent AGI from killing everyone. However, if a research project made any serious progress towards WBE, it would likely contribute to existential risk from AI by contributing to AI capabilities progress. Here is the argument that a successful WBE research project would accelerate AI capabilities: Creating a WBE is very hard. Therefore, it's very unlikely that a research project, unless extremely well-resourced, could reliably create a WBE very quickly (in less than five years, say). There is a wide spectrum of difficulty within the set of problems building up to WBEs. Some are easy, some are pretty difficult, some are very difficult, some are extremely difficult. Therefore, a project is likely to make some initial progress partway to WBEs, and then to stall and not quickly get all the way to WBEs. Therefore, it's very likely for a WBE project to spend a significant amount of time having already made partial progress, but not being very close to WBEs. If a project makes serious partial progress towards WBEs, it will have produced artifacts (whether data, methods, apparatuses, ideas, algorithms, or running simulations) that enable one to partially emulate some powerful aspects of the human brain. In other words, it is not feasible to eventually get a computer emulation of all the immensely powerful algorithms of the human mind, without, in the interim between here and there, being able to create "partial brain emulations" that embody some but not all of the powerful algorithms of the human mind. The AI capabilities research sector would probably succeed at expropriating those "partial brain emulations" and using them to accelerate AI capabilities research. In other words, solving approximately everything about WBEs would be great. Solving anywhere between 5% and 95% of the problems leading up to WBEs would be quite bad. The latter is much more likely to happen from a given WBE research program, if it makes much progress at all. It's much easier to get some capabilities out of the brain and into the computer than to get all of them into the computer. This situation induces a bad "knee curve" of utility for WBE research: It's net-negative up until it fully succeeds, and it's difficult to fully succeed. Thus, WBE research is net-harmful by default. Prior art (not necessarily in concurrence): Byrnes 2020: "Building brain-inspired AGI is infinitely easier than understanding the brain" Byrnes 2023: "8 examples informing my pessimism on uploading without reverse engineering" Caveats I don't imagine this article will materially impact too much. But if it did, I would think that impact to be at significant risk of being mistaken, unless there was appropriate pushback somewhere (here in the comments or elsewhere). I state arguments fairly strongly in this article. My hope is to do this in the spirit of debate, rather than shutting anything down. I stand by the arguments I make here, but this is coming from mostly recently formed opinions. In particular, I haven't spent a lot of effort trying to find a workable WBE plan that responds to the critique I make here; maybe such effort would bear fruit. I'm not remotely close to being an expert in neuroscience. Some of the ways this article could be wrong There are some settings of background strategic variables that would make WBE research good even if everything argued in this article is true. For example, if you think all of: AGI is very likely very near, even given all efforts to stop it. There's a nonnegligible chance of making the research "leap" all the way to WBEs in a few years. It's not worth changing course based on unilateralism / cooperation concerns saying not to add to AI capabilities even when it seems like a good idea, because you degrade our ability to stop AGI research. Then a crash project to get WBEs could make sense. It could also be that making a quasi-WBE that emulates electrical structure only (no learning) is already useful and pretty easy. It could be that some kinds of "WBE research", especially ones such as connectomics that don't try to reverse engineer the brain's learning algorithm, are net-helpful. See Byrnes 2023: "Connectomics seems great from an AI x-risk perspective". I a little bit believe this regarding connectomics. I don't strongly believe this about connectomics or about any research, a priori, because either it doesn't lead to true, extremely helpful, human WBEs, or else it does and it's powerful and therefore it throws off powerful PBEs on the way there. However, see the next paragraph: It could be that Flourish or Astera Neuro or another group will have already cracked the dangerous brain algorithms, but not yet have finished turning that into a world-destroying AI. In that case, a WBE project couldn't add much dangerous information, so it could