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What? We have to model human health. Find good proxies for it (non invasive scans, bloodwork, PCR, rapid antigen test, whole genome sequencing, anamnesis [medic

by pas 5y ago

What? We have to model human health. Find good proxies for it (non invasive scans, bloodwork, PCR, rapid antigen test, whole genome sequencing, anamnesis [medical history]) and there's ample to predict. Of course there are better and worse signals to use.

Barrin92 5y ago
>We have to model human health no, the correct behavior under uncertainty isn't modelling, it's something akin to Taleb's notion of antifragility or robustness. The correct response to a pandemic isn't some sort of Hari Seldon psycho-history which, as the article points out, is futile. The right response is building systems so responsive they can crush a pandemic before it gets to that stage.
- pas 5y ago
  Antifragility depends on knowing how to respond so that next time you'll be less fragile for the "same" stimuli. For that we need better public health measures, those depend on modeling, vaccine development, etc. There's no escaping understanding human health. It underpins and informs our responses. (Which kind of viruses are likely to pose a real threat, monitoring those threats, evaluating them, models, predictions, data, etc.) I'm not talking about one big Seldon-esque equation, but about the public/global health system we already have, the whole of medical research, and so on. These toy classifiers trained on COVID scans are in the same class as Tesla's dangerous "autopilot", because the system is too limited, it doesn't understand context, it lacks a world model. (Tesla's lack epistemic convergence and stability for object detection, ie. it lacks the understanding that cars, roads, obstacles don't flicker in and out of existence, nor do they change from frame to frame. Similarly a "medical AI" needs to understand that medical imaging artifacts are unlikely to be good proxies for real diagnosis, so it needs to be able to abstract away from the image, process away the artifacts and recording environment differences, etc.)

by pas 5y ago

Barrin92 5y ago

>We have to model human health no, the correct behavior under uncertainty isn't modelling, it's something akin to Taleb's notion of antifragility or robustness. The correct response to a pandemic isn't some sort of Hari Seldon psycho-history which, as the article points out, is futile. The right response is building systems so responsive they can crush a pandemic before it gets to that stage.

pas 5y ago
Antifragility depends on knowing how to respond so that next time you'll be less fragile for the "same" stimuli. For that we need better public health measures, those depend on modeling, vaccine development, etc. There's no escaping understanding human health. It underpins and informs our responses. (Which kind of viruses are likely to pose a real threat, monitoring those threats, evaluating them, models, predictions, data, etc.) I'm not talking about one big Seldon-esque equation, but about the public/global health system we already have, the whole of medical research, and so on. These toy classifiers trained on COVID scans are in the same class as Tesla's dangerous "autopilot", because the system is too limited, it doesn't understand context, it lacks a world model. (Tesla's lack epistemic convergence and stability for object detection, ie. it lacks the understanding that cars, roads, obstacles don't flicker in and out of existence, nor do they change from frame to frame. Similarly a "medical AI" needs to understand that medical imaging artifacts are unlikely to be good proxies for real diagnosis, so it needs to be able to abstract away from the image, process away the artifacts and recording environment differences, etc.)