by mrlongroots 3 hours ago
Pyschiatry gets complicated because the failures are not mechanical. Even if you could image every single neuron in a person's head we do not have a very good way to define an algorithm for these issues. I do not have a good answer for psychiatry.
> This is a kind of thinking a lot of programmers fall prey to. The real world, outside of code, is a very fuzzy and inherently analog place.
Having said that, I would vehemently reject and push back against this, and without doubting your sincerity, characterize it as an ad hominem.
The vast majority of issues with the human body are mechanical in nature. Restricted blood flow, unwanted tissue, a broken bone, a bad valve etc. These are causal descriptions of "disease". Where causal descriptions exist, the "One True Diagnosis" principle holds. Psychiatry just happens to be unique in that it is a fuzzy science where we rely on checklists and ultimately all diagnosis is probabilistic.
EDIT:
> This is a kind of thinking a lot of programmers fall prey to. The real world, outside of code, is a very fuzzy and inherently analog place. There is very rarely one in any complex system having a complex problem needing a complex solution. At some point even the definition of diagnosis gets fuzzy.
I would also push back against this mindset in general. This is not a falsifiable claim, it is incoherence as an argument, and I do not need to be a programmer to hold this position.
That the real world is analog is irrelevant to its amenability to causal explanations. Or "fuzzy": "fuzzy" in this context just does not mean anything.
I am not trying to sound exasperated or win internet points, just impress this point on you and anyone reading this. We can write math to predict weather, make it tractable to solve using approximations, tolerate IEEE 754 weirdness, and finally tell what the clouds will do a week from now. This is nature telling us that there is a pattern to how it behaves, and it is the only weapon we have as scientists.
To say that nature is not amenable to explanations is a very defeatist thing to say: neither Newton nor Einstein nor any of the million-odd people that have built modern society would exist if nature did not have causal explanations. I urge you to reject this defeatist thinking.
There's quite a few diseases and conditions that don't have definitive tests. For example, alzheimer's and parkinsons are diagnosed based on medical history and symptoms. With alzheimer's an autopsy can tell for sure but that's not much help for a patient. I'm sure there's other things out there with similar situations. Hard to come up with "the one true" diagnosis with an definitive way to determine it.
> With alzheimer's an autopsy can tell for sure but that's not much help for a patient.
Ok let us unpack this statement.
For your point to hold, I would have to be saying "all kinds of practical diagnostics are invented now. No progress can be made in better diagnostics".
If Alzheimer's can be validated by slicing open a dead patient, there is a causal mechanical explanation for the disease. If we can not confirm that defect without slicing open the patient, that is a limitation of 2026 tools. The "One True Diagnosis" is an Oracle explanation that all real diagnostic techniques try to approach in the asymptotic sense, and it is helpful exactly because it clarifies in discussions like this.
There are going to be diseases where we do not yet have causal explanations. Or where we treat them without establishing them. Hypertension is one example: while technically it can be caused by vascular stiffness, some weirdness with the RAAS system, some hyperadrenergic weirdness, practically you get a lot of mileage out of just prescribing people telmisartan if they're old.
That does not mean the frontier of hypertension is settled, or the 10% who do not have a vascular stiffness problem would not benefit from better causal models of hypertension. Science is us continuously pushing back against the fog: of the tools we have in 2026, some are great, some are imperfect, some are promising etc.
There might be "one true diagnosis" but there's no reason to believe that we'll have practical diagnostic tools to get it. If we need to sample the brain chemistry to diagnose a neurochemical disorder, it's probably not too useful in a clinical setting. The world makes no guarantees that we will be able to differentiate between certain situations with tools that we can realistically access and build.
Today's limits are known and undisputable. Tomorrow's limits are a promise: some promises over-deliver, others under-deliver. :)
Regardless, to bring the discussion back to the claim at hand: at all points in future, we will need the ability to reason under partial information. "Absolutely flawlessly complete diagnostics" is an asymptotic goal we get closer to but never reach. This is both very doable for a disciplined human, and very hard to outsource completely to an LLM. Treated as tools operatored by competent users, they are magical. But they can not outperform their user.