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It's completely logical that engineers have professional deformation. Society is in crisis and there are metrics. How can you realistically expect engineers no

by ralfn 6y ago

It's completely logical that engineers have professional deformation. Society is in crisis and there are metrics. How can you realistically expect engineers not to start debugging and interpreting the metrics? Yes. Engineers aren't medical domain experts, but the experts and/or political leadership failed. The models are not being shared. The process isn't transparent, nor optimized for quick interventions based on incomplete information. And claims and policies differ around the world. There is no consensus among the experts. The truth is, engineers might have more experience in how to operate during a crisis like this. How to quickly asses risks in a world of incomplete and sometimes contradictory information. I wish the real experts were more convincing in their abilities. But in the west this is the first time they deal with this kind of situation while it not being a hypothetical. They is their first real experience with it as well.

notacoward 6y ago
> engineers might have more experience in how to operate during a crisis like this. That's probably more true for real engineers - the kind requiring certification and insurance - than software engineers. Yet they hesitate to speak over the epidemiologists. Why? Because they know how to be diligent and not say things they can't back up. > But in the west this is the first time they deal with this kind of situation while it not being a hypothetical. I've personally had to work with epidemiologists in the context of a (minor) measles outbreak. TB is an ongoing issue in many western countries. Norovirus. Legionnaire's. Western epidemiologists have also been involved in outbreaks elsewhere - e.g. SARS or Ebola. Their experience isn't any less because those outbreaks weren't on their home turf. Sure, they don't have direct experience with a pandemic, but neither do the amateurs. How can you think that people who have spent years studying the theory and getting real in-the-field experience are less qualified than some random software developer or VC when neither have faced this before? The fact that mistakes have been made doesn't mean there's nothing to their field and anyone can do it. Are there no software bugs? Can just anyone come in and fix those?
- thu2111 6y ago
  But you're overlooking the most likely outcome - that nobody is qualified in this field. However software developers can admit this and epidemiologists can't. Bearing in mind for a moment that epidemiologists are amateur programmers, their work output is literally papers+code, they have a major handicap that they can't stop and say "maybe this doesn't work". What else would they do? I've found the comments by Caswell Bligh very insightful on this topic. Bligh is one of the awful "men in tech" programmers the article laments, who has been writing his own models based on epidemiological papers. Perhaps even from an armchair. Everything he's concluded is worth reading but I'll quote some extracts: https://lockdownsceptics.org/2020/04/26/latest-news-12/#comment-935 https://lockdownsceptics.org/2020/04/26/latest-news-12/#comm... Do ‘R0’ or the other ‘R’ values even mean anything when ‘infection’ versus ‘exposure’ can’t even be defined? If social distancing reduces the level of exposures but not the number, does this mean the ‘R’ number is the same, or reducing? Maybe the lockdown means that the population is being quietly, in the background, inoculated to a certain level of resistance (which is what I think is probably happening) but that it doesn’t show up in antibody tests. Many of these things will never be known. They are probably not even predictable with viruses that are not ‘novel’. Virologists and immunologists may know some of it, and they also know what they don’t know. The modellers don’t know any of it. As such, models will never be able to give you absolute values for the number of infections, deaths and so on. We may as well not bother with the units on the axes and simply use the model to illustrate the different shapes that are possible In this interview there's a useful quote: https://fivethirtyeight.com/videos/how-one-modeler-is-trying-to-forecast-the-toll-of-covid-19/ https://fivethirtyeight.com/videos/how-one-modeler-is-trying... At about 8.00: “The nature of SEIR models is they do tend to always show this huge increase up to the point of saturation where most people get infected and very often that has not historically happened”. https://lockdownsceptics.org/how-reliable-is-imperial-colleges-modelling/#comment-1070 https://lockdownsceptics.org/how-reliable-is-imperial-colleg... @Hugh Osmond. What you’ve articulated – and it’s something that’s been bothering me – is that ‘R0’ and the other ‘R’ variants are not a real characteristic of the virus. Snapshots during the epidemic may give you observed values for them, but that doesn’t mean that they represent something fundamental. Attempting to both derive, and then use values for ‘R’ in models, has led to this disaster. It needs to be shouted from the rooftops. ‘R0’ is not a characteristic of the virus. And saying “‘R0’ depends on the virus but also age/population density/pollution etc. etc.” is just another way of saying the same thing. If you know ‘R0’ in advance, you’ve already anticipated what the simple model is going to tell you – there’s almost no point running the model. In the more sophisticated, more realistic model we shouldn’t even try to accommodate an ‘R0’ input at all, and nor should we try to modify an ‘R’ as time goes on. That’s the wrong way round. Really, I think you’ve articulated something extremely important here. It’s been driving me mad for weeks: the illness is being defined in terms of a standard, simplistic, mathematical model that was easy to compute before the invention of computers. But even now, if you want to make a more sophisticated model, you are still forced to talk about its results in terms of the simple model. When I told a biologist friend of mine I was creating a model, the first thing she asked me was “What value of R0 are you using?”. This is how we have arrived at this disaster.
- ralfn 6y ago
  >when neither have faced this before >The fact that mistakes have been made doesn't mean there's nothing to their field and anyone can do it I was not making that claim. The premise is: should every non epidemiologist keep their mouth shout and trust the domain experts blindly? Don't they have the right in a democracy to question the science and therefor the legitimicy of the suggested policies? That's a hard sell, when the field of experts themselves have little consensus. I might be seeing this from a different bubble, over here in the Netherlands. We have had our equivalent of the CDC show and explain their models and policy choices in detail. We got powerpoints and everything. Now before you make assumptions: https://www.weforum.org/agenda/2019/11/countries-preparedness-pandemics/ https://www.weforum.org/agenda/2019/11/countries-preparednes... .. the Netherlands ranked 3rd in preparedness. Yet, it turned into a shitshow. It was already going wrong in Italy, when they claimed their models suggested we have it fully under control if only we wash our hands, and they then let one of the biggest social events happen (think mardi gras). Even though we already had our first cases. Italy's expert initially said they had it under control. They suggested cultural differences in health and healthcare made it such a bigger problem for China than for them. Then it went to shit in Italy. Then the dutch experts said, after a few cases, they had it completely under control and the reason it went wrong in Italy was cultural differences in health and healthcare. Yeah, racist ignorance. And all their preparations didn't include supply chain management or the human factor. For example: the relationship (worldwide) between the lockdowns and the available of PPE -vs- the availability of PPE and the spread of the virus. Because none of those things are part of the known models. So they just exclude it entirely. So, given all of that, yeah, I would like to see their homework in more detail, and we should all put in the intellectual effort, to sort this stuff out. >Are there no software bugs? More than any other engineering discipline. So software engineers do actually have more experience debugging collapsing systems build on the wrong assumptions. >Can just anyone come in and fix those? Yes, mostly. Its called a pull request.

by ralfn 6y ago

notacoward 6y ago

> engineers might have more experience in how to operate during a crisis like this. That's probably more true for real engineers - the kind requiring certification and insurance - than software engineers. Yet they hesitate to speak over the epidemiologists. Why? Because they know how to be diligent and not say things they can't back up. > But in the west this is the first time they deal with this kind of situation while it not being a hypothetical. I've personally had to work with epidemiologists in the context of a (minor) measles outbreak. TB is an ongoing issue in many western countries. Norovirus. Legionnaire's. Western epidemiologists have also been involved in outbreaks elsewhere - e.g. SARS or Ebola. Their experience isn't any less because those outbreaks weren't on their home turf. Sure, they don't have direct experience with a pandemic, but neither do the amateurs. How can you think that people who have spent years studying the theory and getting real in-the-field experience are less qualified than some random software developer or VC when neither have faced this before? The fact that mistakes have been made doesn't mean there's nothing to their field and anyone can do it. Are there no software bugs? Can just anyone come in and fix those?

thu2111 6y ago
But you're overlooking the most likely outcome - that nobody is qualified in this field. However software developers can admit this and epidemiologists can't. Bearing in mind for a moment that epidemiologists are amateur programmers, their work output is literally papers+code, they have a major handicap that they can't stop and say "maybe this doesn't work". What else would they do? I've found the comments by Caswell Bligh very insightful on this topic. Bligh is one of the awful "men in tech" programmers the article laments, who has been writing his own models based on epidemiological papers. Perhaps even from an armchair. Everything he's concluded is worth reading but I'll quote some extracts: https://lockdownsceptics.org/2020/04/26/latest-news-12/#comment-935 https://lockdownsceptics.org/2020/04/26/latest-news-12/#comm... Do ‘R0’ or the other ‘R’ values even mean anything when ‘infection’ versus ‘exposure’ can’t even be defined? If social distancing reduces the level of exposures but not the number, does this mean the ‘R’ number is the same, or reducing? Maybe the lockdown means that the population is being quietly, in the background, inoculated to a certain level of resistance (which is what I think is probably happening) but that it doesn’t show up in antibody tests. Many of these things will never be known. They are probably not even predictable with viruses that are not ‘novel’. Virologists and immunologists may know some of it, and they also know what they don’t know. The modellers don’t know any of it. As such, models will never be able to give you absolute values for the number of infections, deaths and so on. We may as well not bother with the units on the axes and simply use the model to illustrate the different shapes that are possible In this interview there's a useful quote: https://fivethirtyeight.com/videos/how-one-modeler-is-trying-to-forecast-the-toll-of-covid-19/ https://fivethirtyeight.com/videos/how-one-modeler-is-trying... At about 8.00: “The nature of SEIR models is they do tend to always show this huge increase up to the point of saturation where most people get infected and very often that has not historically happened”. https://lockdownsceptics.org/how-reliable-is-imperial-colleges-modelling/#comment-1070 https://lockdownsceptics.org/how-reliable-is-imperial-colleg... @Hugh Osmond. What you’ve articulated – and it’s something that’s been bothering me – is that ‘R0’ and the other ‘R’ variants are not a real characteristic of the virus. Snapshots during the epidemic may give you observed values for them, but that doesn’t mean that they represent something fundamental. Attempting to both derive, and then use values for ‘R’ in models, has led to this disaster. It needs to be shouted from the rooftops. ‘R0’ is not a characteristic of the virus. And saying “‘R0’ depends on the virus but also age/population density/pollution etc. etc.” is just another way of saying the same thing. If you know ‘R0’ in advance, you’ve already anticipated what the simple model is going to tell you – there’s almost no point running the model. In the more sophisticated, more realistic model we shouldn’t even try to accommodate an ‘R0’ input at all, and nor should we try to modify an ‘R’ as time goes on. That’s the wrong way round. Really, I think you’ve articulated something extremely important here. It’s been driving me mad for weeks: the illness is being defined in terms of a standard, simplistic, mathematical model that was easy to compute before the invention of computers. But even now, if you want to make a more sophisticated model, you are still forced to talk about its results in terms of the simple model. When I told a biologist friend of mine I was creating a model, the first thing she asked me was “What value of R0 are you using?”. This is how we have arrived at this disaster.
ralfn 6y ago
>when neither have faced this before >The fact that mistakes have been made doesn't mean there's nothing to their field and anyone can do it I was not making that claim. The premise is: should every non epidemiologist keep their mouth shout and trust the domain experts blindly? Don't they have the right in a democracy to question the science and therefor the legitimicy of the suggested policies? That's a hard sell, when the field of experts themselves have little consensus. I might be seeing this from a different bubble, over here in the Netherlands. We have had our equivalent of the CDC show and explain their models and policy choices in detail. We got powerpoints and everything. Now before you make assumptions: https://www.weforum.org/agenda/2019/11/countries-preparedness-pandemics/ https://www.weforum.org/agenda/2019/11/countries-preparednes... .. the Netherlands ranked 3rd in preparedness. Yet, it turned into a shitshow. It was already going wrong in Italy, when they claimed their models suggested we have it fully under control if only we wash our hands, and they then let one of the biggest social events happen (think mardi gras). Even though we already had our first cases. Italy's expert initially said they had it under control. They suggested cultural differences in health and healthcare made it such a bigger problem for China than for them. Then it went to shit in Italy. Then the dutch experts said, after a few cases, they had it completely under control and the reason it went wrong in Italy was cultural differences in health and healthcare. Yeah, racist ignorance. And all their preparations didn't include supply chain management or the human factor. For example: the relationship (worldwide) between the lockdowns and the available of PPE -vs- the availability of PPE and the spread of the virus. Because none of those things are part of the known models. So they just exclude it entirely. So, given all of that, yeah, I would like to see their homework in more detail, and we should all put in the intellectual effort, to sort this stuff out. >Are there no software bugs? More than any other engineering discipline. So software engineers do actually have more experience debugging collapsing systems build on the wrong assumptions. >Can just anyone come in and fix those? Yes, mostly. Its called a pull request.