Many engineering projects get dismissed as impossible or pseudoscientific because it's easier to imagine how something would fail than how it would succeed. When someone imagines multiple ways a project could fail, they assume that they've explored all the feasible ways of accomplishing it and conclude, "Because I've found five ways it couldn't work, there's probably no other way it could work."

I was debating the possibility of self-driving cars with a friend in the early 2000s and he said, "It's not gonna happen because AI needs to get as smart as a human. We're nowhere near that and it might not even be possible." He'd taken the first solution that came to mind—human-level AI—realized that there wasn't any evidence of it lying around, and concluded that self-driving cars are impossible.

Yet here we are with prototypes of self-driving cars navigating through busy streets using multiple proxies for human capabilities instead of one generally intelligent entity at the helm.

Cryonics is another engineering effort that's labeled pseudoscientific because of a lack of easy-to-imagine pathways to reviving a person. One common objection is that the freezing process would damage brain tissue as the water crystallizes. However, cryonics companies long ago moved from a straight freezing process to a process called vitrification, which preserves brain tissue with almost no damage. The question is whether the slight damage that occurs can be repaired—or whether enough of it can be repaired—to revive a patient.

We don't have the technology to do that today [1], but that shouldn't cause someone to say "cryonics is pseudoscientific", just like one couldn’t say "computers beating Go champions is pseudoscientific" before 2016 or "heavier-than-air flight is pseudoscientific" before 1903. Sure, we failed thousands of times, but as Edison would say: "we haven't failed once, we just found thousands of ways that don't work."

Engineers can tolerate ambiguity because you only need one way that works, never mind that all other attempts have failed. Scientists, in contrast, feel unease with incomplete theories and models of the world. It's their job to plug in those gaps, so they seek those holes and consider a theory unsolved until they're filled.

When you have trouble integrating your client management SaaS product with Salesforce, do you declare it pseudoscientific and abandon it? No, you put Salesforce aside and focus on customers using products you can integrate with. Your product works. It just has that unsolved problem you can figure out later if it becomes super important.

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[1] R. Michael Perry, Ph.D. suggests atomically precise manufacturing (APM), also known as molecular nanotechnology (MNT), as an enabling technology for both cryopreservation and revival. He writes:

[We need] "More theoretical work showing how MNT might be implemented, with emphasis on application to cryonics revival. This would especially put focus on systems that would operate at low temperature and would be able to do “readouts” of objects, to determine the internal structure down to molecular levels."

(Dec 2019 issue of Cryonics magazine, p. 35)

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Unsurprisingly, APM itself has its share of faulty criticism. K. Eric Drexler, who developed APM theory, writes of many encounters with scientists familiar with nanotechnology who dismissed APM's feasibility with arguments like:

“Some surfaces would bond together on contact, therefore . . .”

“Some systems are sensitive to small inaccuracies, therefore . . .”

“Some kinds of machines would fail when exposed to gunk . . .”

True statements like these do not speak against well-chosen surfaces serving as bearings, or well-designed systems being robust, or machines working because they don’t let gunk get inside. At best, they draw attention to constraints.

(Drexler, K. Eric. Radical Abundance, p. 127.)

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For a recent discussion of the applications of APM to cryonics, see "Cryostasis Revival: The Recovery of Cryonics Patients through Nanomedicine" 2022 Book by Robert A. Freitas Jr.

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