If faith is involved it's not science.
But I’m not the scientist in this scenario. I have faith in the process they use to reach conclusions by testing hypotheses. There are certainly limitations to this, but it does appear to be the best practice we have. The alternative is personal expertise in every field which in spite of its impossibility flies in the face of Adam Smith, and that’s blasphemy as far as I’m concerned!
Regarding the predictions, most areas of science don’t really require this. I know in areas like climate change they probably should be able to do this with some degree of accuracy, but I would argue climate science is not a real scientific discipline anyway due to the lack of falsifiable hypotheses in the formulation of their theories. A lot of epidemiology seems to suffer from a similar ailment I’ve noticed over the past year. But modelling, in either climate science or epidemiology, is a statistical rather than strictly scientific discipline. And stats can be open to quite wide interpretation.
No part of science requires faith, not faith in a process, not faith in an institution or faith in an expert. All claims must be backed up by testable evidence.
You don't need personal expertise in every field to assess whether their predictions have been borne out or not. If someone is demanding drastic action (such as shutting down an economy) then they need to present their claims in a straightforward manner without technobabble which can be understood by anyone, not just specialists in their field. If they can't do so, and we are left with no way to distinguish empty jargon from nuanced argument, then we should make the default assumption that it's empty jargon.
But I lack the expertise to even understand the testable evidence. As an example, I have a close family member who is expert in virology. I ask them questions about these matters in an effort to better understand the topic. But as hard as I may try I just don’t get it. There’s lots of more fundamental microbiological matters I would need to fully understand to even begin to grasp the complex matters I’ve had fruitlessly explained to me. So in that scenario should my inability to understand the data or even methodology invalidate the conclusions of the those can understand it? At some point you have to put faith in things.
Your second paragraph appears to be referring to current lockdowns to stop the spread of the virus. As I said before this is based on statistical modelling which is not really a hard scientific discipline. I do agree modellers should be able to make reasonable predictions and be held to them. I also think we are have a lot of comparatives with other countries now, and I don’t think the lockdowns are a good idea. But I can understand stats and obviously I can compare relatively similar populations who have adopted different methods. I think this is quite different from the necessity to put your faith in those more knowledgable than yourself in matters in which you have to admit your own ignorance or limitations.
But I lack the expertise to even understand the testable evidence. As an example, I have a close family member who is expert in virology. I ask them questions about these matters in an effort to better understand the topic. But as hard as I may try I just don’t get it. There’s lots of more fundamental microbiological matters I would need to fully understand to even begin to grasp the complex matters I’ve had fruitlessly explained to me. So in that scenario should my inability to understand the data or even methodology invalidate the conclusions of the those can understand it? At some point you have to put faith in things.
You don't need to understand every technical nuance of every paper they write to understand a broad claim and a broad implication. Like I said, it depends on the scale of what they're claiming/demanding.
If an expert says "we need to shut down everyone's lives and put them under house arrest for months/years/forever because of a deadly virus," then they need to have very specific and testable predictions to back up that demand. For example, the expert from imperial college advising the UK government claimed that even with the lockdowns there would be a quarter of a million dead, and without there'd be at least half a million. Back in the real world, he turned out to be wrong, just as he was wrong when he made similar predictions about SARS and swine flu. I do not need to know the nuances of his data processing techniques and his model (which incidentally he refused to release) to know that the substantive of his claim was wrong.
If, on the other hand, he makes some very limited claim about the protein capsule surrounding the virus and recommends food factories install a particular type of filter most of them are using anyhow, then there's a lot less need for scrutiny and I'm not too worried about leaving the assessments of his claims to other experts.
Your second paragraph appears to be referring to current lockdowns to stop the spread of the virus. As I said before this is based on statistical modelling which is not really a hard scientific discipline. I do agree modellers should be able to make reasonable predictions and be held to them. I also think we are have a lot of comparatives with other countries now, and I don’t think the lockdowns are a good idea. But I can understand stats and obviously I can compare relatively similar populations who have adopted different methods. I think this is quite different from the necessity to put your faith in those more knowledgable than yourself in matters in which you have to admit your own ignorance or limitations.
If you admit ignorance of a particular topic you should not be granting a carte blanche to someone who claims expertise. This is the reason why professionals like doctors, lawyers and accountants only ever frame their professional services as "advice." They are explaining things to you and making a reasoned recommendation. You are never supposed to just admit defeat and do whatever they say without understanding it.
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