Personal website: https://andrewtmckenzie.com/
Andy_McKenzie
Karma: 1,580
identity is irretrievably lost when the brain activity stops
My point here is that this is a very strong claim about neuroscience—that molecular structure doesn’t encode identity/memories.
The examples you provided don’t actually support the “one funeral at a time” narrative in your title. Take Barbara McClintock’s jumping genes or Barry Marshall’s H. pylori discovery—in both cases, many scientists changed their views based on compelling evidence while very much alive. There are plenty of other examples of this. For example, the acceptance of prions as disease agents, the role of microbiomes in health, dark energy, and mitochondria’s bacterial origins all show how consensus can shift rapidly once a sufficient amount of evidence has accumulated. Scientists change their minds all. the. time.
This is not to say that there are not fads or incorrect beliefs in science—of course there are. And sometimes it can takes years or decades for them to be overwhelmed. But the “funeral” framing in particular is not only historically inaccurate but also promotes a harmful view that death is necessary for progress. What we actually see in these examples is that scientific views change when sufficient evidence accumulates and a sufficient number of people are convinced, regardless of generational turnover. Suggesting we need scientists to die rather than be convinced by evidence is both incorrect and ethically fraught. I am saddened to see it here and therefore strong downvoted this post.
Thanks for the clarification and your thoughts. In my view, the question is to what extent the polymer gel embedding is helpful from the perspective of maintaining morphomolecular structure, so that it is worth the trade-off of removing the lipids, which could potentially also have information content. https://brainpreservation.github.io/Biomolecules#how-lipid-biomolecules-in-cell-membranes-could-affect-ion-flow
You are in good company in thinking that clearing and embedding the tissue in a hydrogel is the best approach. Others with expertise in the area have suggested the same thing to me. I’m just not convinced, so I think that more research is required to tell whether that is the best approach.
ETA: Sorry, just saw your edit. Interesting thoughts on the interaction between preservation and reconstruction. Your perspective and goals make sense to me, although it is not exactly what we are pursuing at Oregon Brain Preservation. We are agnostic as to the potential method of revival and expect this to be relatively further away in the future, if it ever becomes possible.
Thanks for your interest!
Does OBP plan to eventually expand their services outside the USA?
In terms of our staff traveling to other locations to do the preservation procedure, unfortunately not in the immediate future. We don’t have the funding for this right now.
And how much would it cost if you didn’t subsidize it?
There are so many factors. It depends a lot on where in the world we are talking about. If we are talking about someone who legally dies locally in Salem, perhaps a minimal estimated budget would be (off the top of my head, unofficial, subject to change):
Labor cost of brain preservation = ~$500-1000
Cost of chemicals, disposable equipment = ~$100-300
Cost of death certificate, cremation, funeral services fees for the rest of the body = ~$1000-1500
Long-term preservation cost = very difficult to estimate, depends on economies of scale, and other factors, perhaps ~$1000-2000
These are rough estimates. But generally speaking, there is a reason that many brain banks around the world are also able to allow people to donate their brains for free. There are many many thousands of brains preserved in this way throughout the world. It is not nearly as expensive as traditional cryonics. Here is some more information about costs for similar type of procedure from the Brain Support Network: https://www.brainsupportnetwork.org/brain-donation/brain-donation-faq/
Cost is a common complaint about cryonics so I could see you becoming much bigger than the cryonics orgs, but judging by the website you look quite small. Do you know why that is?
I don’t know. A couple of guesses are that we are just getting started and not really doing any marketing because our focus is on researching the preservation methods. Also, it is likely that many people are skeptical of the preservation methods that we use, since they are new and different than others, as well as being experimental. Here is some more information about our research program, which you might find interesting: https://osf.io/preprints/osf/c28hm
We discuss the possibility of fluid preservation after tissue clearing in our article:
An alternative option is to perform tissue clearing prior to long-term preservation (118). This would remove the lipids in the brain, but offer several advantages, including repeated non-invasive imaging, and potentially reduced oxidative damage over time (119).
And also in our fluid preservation article we have a whole section on it. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11058410/#S7
I’m not sure why this option is much more robust that formaldehyde fixation alone. I haven’t seen any strong evidence for that. I do agree that it is potentially very useful for 3D reconstruction, but reconstruction is a much different problem than preservation.
I can’t speak for Adele, but here is one somewhat recent article by neuroscientists discussing memory storage mechanisms: https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-016-0261-6
DNA is discussed as one possible storage mechanism in the context of epigenetic alterations to neurons. See the section by Andrii Rudenko and Li-Huei Tsai.
This is an important question. While I don’t have a full answer, my impression is that yes, it seems to preserve the important information present in DNA. More information here: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11058410/#S4.4
Thanks for the comment. I’m definitely not assuming that p(success) would be a monocausal explanation. I’m mostly presenting this data to give evidence against that assumption, because people frequently make statements such as “of course almost nobody wants cryonics, they don’t expect it will work”.
I also agree that “is being revived good in expectation / good with what probability” is another common concern. Personally, I think niplav has some good analysis of net-negative revival scenarios: https://niplav.site/considerations_on_cryonics.html
Btw, according to the author, ‘Lena’ is largely a critique of exploitive capitalism: https://qntm.org/uploading
Very high-effort, comprehensive post. Any interest in making some of your predictions into markets on Manifold or some other prediction market website? Might help get some quantifications.
A simple solution is to just make doctors/hospitals liable for harm which occurs under their watch, period. Do not give them an out involving performative tests which don’t actually reduce harm, or the like. If doctors/hospitals are just generally liable for harm, then they’re incentivized to actually reduce it.
Can you explain more what you actually mean by this? Do you mean if someone comes into the hospital and dies, the doctors are responsible, regardless of why they died? If you mean that we figure out whether the doctors are responsible for whether the patient died, then we get back to whether they have done everything to prevent it, and one of these things might be ordering lab tests to better figure out the diagnosis, and then it seems we’re back to the original problem i.e. the status quo. Just not understanding what you mean.
Out of curiosity, what makes you think that the initial freezing process causes too much information loss?
I agree with most of this post, but it doesn’t seem to address the possibility of whole brain emulation. However, many/(?most) would argue this is unlikely to play a major role because AGI will come first.
Thanks so much for putting this together Mati! If people are interested in cryonics/brain preservation and would like to learn about (my perspective on) the field from a research perspective, please feel free to reach out to me: https://andrewtmckenzie.com/
I also have some external links/essays available here: https://brainpreservation.github.io/
It seems to me like your model is not necessarily taking into account technical debt sufficiently enough. https://neurobiology.substack.com/p/technical-debt-probably-the-main-roadblack-in-applying-machine-learning-to-medicine
It seems to me like this is the main thing that will slow down the extent to which foundation models can consistently beat newly trained specialized models.
Anecdotally, I know several people who don’t like to use chatgpt because its training cuts off in 2021. This seems like a form of technical debt.
I guess it depends on how easily adaptable foundation models are.
Sounds good, can’t find your email address, DM’d you.
Those sound good to me! I donated to your charity (the Animal Welfare Fund) to finalize it. Lmk if you want me to email you the receipt. Here’s the manifold market:
Bet
Andy will donate $50 to a charity of Daniel’s choice now.
If, by January 2027, there is not a report from a reputable source confirming that at least three companies, that would previously have relied upon programmers, and meet a defined level of success, are being run without the need for human programmers, due to the independent capabilities of an AI developed by OpenAI or another AI organization, then Daniel will donate $100, adjusted for inflation as of June 2023, to a charity of Andy’s choice.
Terms
Reputable Source: For the purpose of this bet, reputable sources include MIT Technology Review, Nature News, The Wall Street Journal, The New York Times, Wired, The Guardian, or TechCrunch, or similar publications of recognized journalistic professionalism. Personal blogs, social media sites, or tweets are excluded.
AI’s Capabilities: The AI must be capable of independently performing the full range of tasks typically carried out by a programmer, including but not limited to writing, debugging, maintaining code, and designing system architecture.
Equivalent Roles: Roles that involve tasks requiring comparable technical skills and knowledge to a programmer, such as maintaining codebases, approving code produced by AI, or prompting the AI with specific instructions about what code to write.
Level of Success: The companies must be generating a minimum annual revenue of $10 million (or likely generating this amount of revenue if it is not public knowledge).
Report: A single, substantive article or claim in one of the defined reputable sources that verifies the defined conditions.
AI Organization: An institution or entity recognized for conducting research in AI or developing AI technologies. This could include academic institutions, commercial entities, or government agencies.
Inflation Adjustment: The donation will be an equivalent amount of money as $100 as of June 2023, adjusted for inflation based on https://www.bls.gov/data/inflation_calculator.htm.
Regulatory Impact: In January 2027, Andy will use his best judgment to decide whether the conditions of the bet would have been met in the absence of any government regulation restricting or banning the types of AI that would have otherwise replaced programmers.
Sounds good, I’m happy with that arrangement once we get these details figured out.
Regarding the human programmer formality, it seems like business owners would have to be really incompetent for this to be a factor. Plenty of managers have coding experience. If the programmers aren’t doing anything useful then they will be let go or new companies will start that don’t have them. They are a huge expense. I’m inclined to not include this since it’s an ambiguity that seems implausible to me.
Regarding the potential ban by the government, I wasn’t really thinking of that as a possible option. What kind of ban do you have in mind? I imagine that regulation of AI is very likely by then, so if the automation of all programmers hasn’t happened by Jan 2027, it seems very easy to argue that it would have happened in the absence of the regulation.
Regarding these and a few of the other ambiguous things, one way we could do this is that you and I could just agree on it in Jan 2027. Otherwise, the bet resolves N/A and you don’t donate anything. This could make it an interesting Manifold question because it’s a bit adversarial. This way, we could also get rid of the requirement for it to be reported by a reputable source, which is going to be tricky to determine.
Understandable. How about this?
Bet
Andy will donate $50 to a charity of Daniel’s choice now.
If, by January 2027, there is not a report from a reputable source confirming that at least three companies, that would previously have relied upon programmers, and meet a defined level of success, are being run without the need for human programmers, due to the independent capabilities of an AI developed by OpenAI or another AI organization, then Daniel will donate $100, adjusted for inflation as of June 2023, to a charity of Andy’s choice.
Terms
Reputable Source: For the purpose of this bet, reputable sources include MIT Technology Review, Nature News, The Wall Street Journal, The New York Times, Wired, The Guardian, or TechCrunch, or similar publications of recognized journalistic professionalism. Personal blogs, social media sites, or tweets are excluded.
AI’s Capabilities: The AI must be capable of independently performing the full range of tasks typically carried out by a programmer, including but not limited to writing, debugging, maintaining code, and designing system architecture.
Equivalent Roles: Roles that involve tasks requiring comparable technical skills and knowledge to a programmer, such as maintaining codebases, approving code produced by AI, or prompting the AI with specific instructions about what code to write.
Level of Success: The companies must be generating a minimum annual revenue of $10 million (or likely generating this amount of revenue if it is not public knowledge).
Report: A single, substantive article or claim in one of the defined reputable sources that verifies the defined conditions.
AI Organization: An institution or entity recognized for conducting research in AI or developing AI technologies. This could include academic institutions, commercial entities, or government agencies.
Inflation Adjustment: The donation will be an equivalent amount of money as $100 as of June 2023, adjusted for inflation based on https://www.bls.gov/data/inflation_calculator.htm.
I guess that there might be some disagreements in these terms, so I’d be curious to hear your suggested improvements.
Caveat: I don’t have much disposable money right now, so it’s not much money, but perhaps this is still interesting as a marker of our beliefs. Totally ok if it’s not enough money to be worth it to you.
I’m wondering if we could make this into a bet. If by remote workers we include programmers, then I’d be willing to bet that GPT-5/6, depending upon what that means (might be easier to say the top LLMs or other models trained by anyone by 2026?) will not be able to replace them.
Thanks for writing this post. I completely agree that trying to fight involuntary death is a great idea.
A few thoughts:
In my view, recording an external mindfile (what I see/hear/say) is not nearly sufficient. Most of the information I value isn’t what I see, but how I react to it, such as the unique patterns of neural activation, the associations my brain makes, and the subtle emotional colorings. A video of me watching a game of bridge tells you nothing about why that particular card game reminded me of my grandparents, or how it shifted my mood in ways I couldn’t even articulate.
There’s a huge difference between recording outputs and preserving the computational substrate that generates those outputs. It’s like trying to recreate an AI model by saving only a relatively small amount of its chat logs. You’d be missing the actual architecture that makes it that particular system. (Now, if we could get enough behavioral data, maybe we could theoretically reverse-engineer the underlying computation. But we’re talking about orders of magnitude more data than what AR glasses and EEG caps will give us. You’d need the internal states, not just the outputs. In my view, your “portable advanced EEG” in the 2030s clearly won’t capture individual synaptic connection strengths or the molecular-level information that likely matters for long-term memories and personality.)
I would recommend reading or at least skimming the whole brain emulation roadmap, which you said you’re planning to do. It’s more about building an emulation on the basis of scanning a preserved brain.
For myself, I am focused on structural brain preservation, which I believe can address this problem well. I think we need to preserve the connectome and the physical instantiation of memory and personality, which could potentially allow for revival with the benefit of future technology. For a recent intro to this topic, see: https://www.frontiersin.org/journals/medical-technology/articles/10.3389/fmedt.2024.1400615/full
Please email me if you’re interested in discussing this more. Maybe I’m wrong about something—if so, I would love it if you could prove me wrong. I’m very glad you’re interested in this space!