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Comment by bjt2n3904 | Hacker News Reader

Some of the most scientifically illiterate people I've encountered are the people who say things like, "We listen to the science when it comes to COVID-19". Let us be perfectly real. When it comes to political decisions based on forecasts, you are not "listening to science".

Science can answer many questions. I can ask it, "How long do I need to fire the engines to achieve this particular orbit", or perhaps "How much material do I need in this region of the bridge to sustain the load of traffic going across it?"

But science is not the computer from Star Trek. I can't come to science and ask it, "How long should we quarantine to minimize health impact, and maximize economic recovery?" Ultimately, that question does not have a scientific answer. It can be informed by statistics -- to the best that we understand the numbers, and scientists can present models of what they think the future will look like... but results not guaranteed.

Some problems have clear cut answers, that science can contribute concrete solutions to. Other problems do not have clear cut answers -- but have a large population of supporters claiming that all "the science" agrees with them, and to disagree with them is to shun reason.

This is also scientific illiteracy.

View on HN

I understand what you're saying, but I think there's some "both sides"-ism at play here.

Yes, there is a level of scientific ignorance displayed when people hand wave and claim "the science" is on their side without actually understanding the science. However, there is a huge qualitative difference here, illustrated even by your example of quarantine recommendations.

If we approximate an answer to "What is the optimal quarantine strategy?" through the combined efforts of various sciences--statistics, biology, etc--then while the results are not guaranteed, the recommendation is certainly not unfounded. It may be incomplete, but it is built off of decades of empirical evidence.

Conversely, outright ignoring recommendations about COVID or climate or something similar, simply because "science isn't always right" or because you "aren't a scientist" is a different thing altogether.

> outright ignoring recommendations

Have you ever wondered why it's not terribly controversial to "recommend" seat belts and airbags?

But when your "recommendation" is to join a large organization and funnel millions of dollars into it, or to levy massive taxes to prevent "the end of the world as we know it"? Pardon me, but I'm deeply skeptical.

Do you remember Solyndra? $500 million loan from the government. Went bankrupt.

I will not accept this straw man re-framing of the issue. Yes, "some people" say "but science isn't always right", and that is a poor argument indeed. But I am not.

>why it's not terribly controversial to "recommend" seat belts

Yet this was not always the case. Growing up wearing seatbelts was the exception, not the norm. Much less the law in some places.

Yes, and I remember having discussions on whether airbags caused more injuries than they prevented! But the fact of the matter is the issue is largely settled in the public eye. How did we get here? The answer is simple. The approach was a dispassionate search for the best solution.

There were no "scientists" claiming hyperbolic doomsday scenarios if we didn't pass specific legislation by a certain date. The collapse of our transportation infrastructure due to Kessler Syndrome -- but for highways. This should cause any rational person to be skeptical.

There were no fund raising rallies held by highly influential "scientists" who refused to wear seat belts themselves. This too, should cause any rational person to be skeptical.

People did not start with a chosen solution, and selected evidence to back it. They started with evidence, and searched for the best solution.

In effect? Seatbelts and airbags weren't a cargo cult driven by celebrity "scientists" that relied on emotional appeal. If you want your politicians to "listen" to "science", then you must divest the emotions, the desire for power, and the appeal to authority from it.

I assume it was a combination of incremental laws and public safety campaigns. It's also true that, in the US and I assume many other countries, there's been a general and incremental shift towards safer behaviors and products of which airbags and seatbelts are just two examples. Increasing automobile safety even at increased cost, etc. wasn't exactly swimming against the tide.

When seatbelts were introduced, there was indeed a number of people opposed to it and just like with COVID19, claiming it infringed on their rights and refusing to wear seatbelts out of spite.

The reason it's not controversial nowadays is because it's (almost) universally accepted as a good idea (though people do buy fake seatbelt plugs to disable the alarms)

> I understand what you're saying, but I think there's some "both sides"-ism at play here.

Why do these conversations "always" go like this, even on a site as rational as HN? If we can't even discuss these very real issues here without rhetoric, how do we expect politicians and the masses (and here I include literal deniers) to do so? Because that is what we are asking of them, is it not? To stop being stupid (which they are doing, to a very large degree), and to start being rational?

Also: why is an article as reasonable as this [flagged] (and therefore removed from the public discourse here)? We ask others to stop living in an information bubble, yet are we willing to do so ourselves?

Might this flagging (of which this is but one of who knows how many instances - HN users shall not know such things) hint at some underlying human characteristic that is a root cause of why we cannot have nice things? Obviously speculative, but it seems reasonable to me.

> even on a site as rational as HN?

This site is made up of people, just like all the other sites out there. As a group, HN is no more or less susceptible to biases and irrationality than any other group of people or any other website. Our starting lemma should be that we are flawed, not that we are inherently less flawed. Acknowledging our biases and irrationalities is the first step toward overcoming them.

> This site is made up of people, just like all the other sites out there. As a group, HN is no more or less susceptible to biases and irrationality than any other group of people or any other website.

From a binary perspective, agreed. From this non-comprehensive perspective, you are correct.

But the reality here is more complex than a binary.

From a continuum perspective, is it actually correct that HN is "just like all the other sites out there", that they are "no more or less susceptible to biases and irrationality than any other group of people or any other website"?

This level of precise consistency across any arbitrary grouping of people seems rather unlikely to occur in reality, and if it was like this, you'd think someone would have noticed it. Also, this take on it seems rather contrary to my "feel" for the aggregate self-evaluation that the individuals members of this community have voiced. I'm fine with either one, but perhaps it might be useful for us to decide on which it is.

If you think about it, if superior rationality is literally impossible, then are we not completely wasting our time on discussing where flaws exist in society, and which groups need to be focused on and improved (which is a very common topic of conversation around here)? If nothing can be done, why do we not just abandon the entire topic of improving the world and devote the remainder of our short lives to enjoying ourselves?

Isn't that a strawman though? How many people actually give an answer like "science isn't always right" when choosing to ignore recommendations about COVID? Perhaps it's the circles I move in, but most people who think COVID recommendations are junk (which doesn't mean they don't follow them) can give far more reasoned and deep explanations for their views than the people they disagree with. Absolutely standard to get an answer like "because I trust the experts" (i.e. "I have no idea") from people who are the most passionately in favour of masks, lockdowns etc. You don't see that in reverse, because people disagreeing with authority by definition can't make an appeal to authority.

This is not my experience at all.

I've seen many people opposing masks and lockdowns due to dangerous half-knowledge and appealing to "that one doctor is also saying that the recommendations are junk (but they are shunned by the mainstream press)".

Of course, we usually find our own reasoning valid and logical and tend to think that the other side can't give "reasoned and deep explanations". I can't claim to be unbiased here.

I'll just note that, from a Bayesian perspective, "trusting experts" is usually not the worst idea and something we're basically forced to do every day anyway. I listen to quite a lot of what some of the experts way, but of course, I am completely unable to independently verify that what they say is valid - without decades of experience in the field, this is simply impossible.

I think they're just using a different definition of "expert" to you. Your reply alludes to this; your definition of an expert involves whether journalists say they're experts. How would journalists know?

Trusting experts is definitely a good policy from a Bayesian perspective given the dictionary definition of expert, i.e. "a person who is very knowledgeable about or skilful in a particular area" to quote Google's top result for the definition.

The problem we have with COVID is the people journalists present to us as experts (invariably academics) keep saying incredibly dumb stuff that's totally wrong, and by now many of us have concluded these "experts" don't actually know any more about disease than the man on the street does.

This is an inevitable problem with how academia is structured. Academics aren't financially rewarded for being correct, like private sector experts are. They're rewarded for writing things their peers find interesting. That's a totally different thing. We hope that being interesting and being correct are strongly correlated, but the replication crisis and general low standards observable in research papers are strong evidence they actually aren't.

I am completely unable to independently verify that what they say is valid - without decades of experience in the field, this is simply impossible.

The people you're disagreeing with also disagree about this. I've read a lot of epidemiology papers this year. The field is a joke: epidemiology is a piece of piss. The Gender Studies of medicine. It's just stats and some basic programming. I've not once had to look up any biology when reading these papers (microbiology being a genuinely hard field) because none of them use any. It's absolutely straightforward to find major, severe defects in these papers without decades of experience in this field. There's definitely a huge gulf in how difficult and deep different fields are, certainly, not all scientific endeavours are the same.

> The problem we have with COVID is the people journalists present to us as experts (invariably academics) keep saying incredibly dumb stuff that's totally wrong, and by now many of us have concluded these "experts" don't actually know any more about disease than the man on the street does.

It's not "what journalists say". Those people usually have valid credentials, e.g. when they are the people that developed the first PCR test for the new Coronavirus. I trust such people much more than random people on the street (or on the internet).

> The people you're disagreeing with also disagree about this. I've read a lot of epidemiology papers this year.

Forgive me if I don't find it terribly convincing that someone over the internet is trying to sell me something like this. Many fields of study are really hard to understand without a lot of context. There might be implicit things you might not be aware of. The internet is full of people who think they have found "flaws" in mathematical proofs or have discovered why FLT is true.

But you're also claiming that all the "experts" and all the relevant papers are from epidemiology whereas we also have a lot of contributions from other fields, such as virology or vaccinology.

I don't think virologists have contributed much so far, at least not to government policy. That's driven almost entirely by modellers.

I'm not asking you to blindly trust me on this. By no means. Go read some of the papers yourself if you like. The value of academic credentials in the field of epidemiology is zero. These people just constantly make basic errors in their papers and standards are so systematically low across the board nobody notices or cares.

I've posted here a list of just some of the problems I've noticed whilst reading these papers:

https://news.ycombinator.com/item?id=25202182

By all means, have blind faith in the credentialed classes. Just remember these are the same people who came up with critical race theory, every replication failure in the field of psychology, the decades of 180 degree turns in nutrition, etc. This article is a good (albeit slightly technical) introduction to some of the problems outsiders find when they sit down and actually read academic output:

https://fantasticanachronism.com/2020/09/11/whats-wrong-with...

It's useful because it has some meta-scientific analysis of quality problems in scientific papers.

Virologists have been instrumental in the debates relating to hygiene rules, the role that aerosols play for the infection, the different tests that exist and when/how they should be applied, what mutations mean or don't mean for infectiousness and immunity, and they can at least partially speak to why certain hypotheses that were observed empirically are not implausible from a biological point of view, or to how vaccines fundamentally work. They're also often in regular contact with practitioners on the field and can speak to the situation there, probably more so than random people on the street.

Here in Germany, virologists have very much been at the center of media attention (and not only of the media: the first PCR test for covid-19 was co-developed by Prof. Drosten who leads the virology department of the Charité clinic in Berlin).

> By all means, have blind faith in the credentialed classes. Just remember these are the same people who came up with critical race theory, every replication failure in the field of psychology, the decades of 180 degree turns in nutrition, etc.

As well as with countless examples of genuine scientific and technological progress. It's not that credentialed scientists are always right, it's that the scientific community (not so much individuals) is much more likely to be right than random people. And that doesn't mean that publication bias isn't a thing, but I'm not gonna hedge my bets on what some un-credentialed people are going to say because they looked at a bunch of papers.

edit: and I'll also mention that it seems you imply that scientists are a uniform bloc or that they all propose the same measures but that's not even true. But they do, largely, agree on some key issues, most notably, that this is a dangerous virus. It is my understanding that not even Tegnell (from Sweden) denies this.

At least in the English speaking media I hardly ever see virologists mentioned. However, maybe I should read some of their papers too then because basically all the advice around masks, lockdowns and so on has been proven wrong by observational data. Totally unclear why; perhaps there's some basic issue with germ theory. It seems unlikely but there aren't that many possible explanations. However these policies (the "non pharmaceutical interventions") have in the Anglosphere all been proposed by epidemiologists, not virologists.

Oh, the Drosten PCR test is under fresh fire today by a team in Denmark for having design issues, and of course we may observe the claim that PCR testing has no false positives must have come from either microbiology or virology (not that there's much difference).

the scientific community (not so much individuals) is much more likely to be right than random people

It's clear now that this isn't the case at all. The successes of physics and chemistry tell us nothing about fields like social psychology because the norms and practices within those fields are totally different. There is no "scientific community". Wildly different thresholds for statistical significance are one such difference that hits you immediately when comparing fields, but the issues are far deeper and more complex than just that.

Epidemiology is a pseudo-science. I've read so many papers by now that are just ludicrous and would never be accepted (I hope!) in more rigorous fields, that you can't really convince me by making vague allusions to the awesome powers of SCIENCE! Epidemiologists aren't wrong as random individuals, they are wrong as a bloc, as a set of institutions, as an entire field. That's exactly why peer review doesn't help: the papers are reviewed by peers who have standards just as low as the people they're reviewing. And unfortunately in academia, peer review is the only tool they have to catch problems.

But they do, largely, agree on some key issues, most notably, that this is a dangerous virus. It is my understanding that not even Tegnell (from Sweden) denies this.

That's a vague and unscientific statement, so sure, of course epidemiologists make it. "Dangerous" is entirely relative. Dangerous compared to what? Statistically it's about as bad as a bad flu wave, which is the sort of event that's been seen many times in the living memory of even quite young people. Most people wouldn't say that's dangerous, even though in some senses almost anything can be dangerous to some people. After all, lots of people die from drowning. Is water dangerous? In some contexts, sure. In others, no.

> "How much material do I need in this region of the bridge to sustain the load of traffic going across it?"

To nitpick a bit: anyone who answers that question for a living will be practicing engineering, not science. Just as an excellent physician can espouse wildly unscientific beliefs, so too can someone become quite good at the craft of engineering without actually doing much science at all.

> I can't come to science and ask it, "How long should we quarantine to minimize health impact, and maximize economic recovery?" Ultimately, that question does not have a scientific answer. It can be informed by statistics -- to the best that we understand the numbers, and scientists can present models of what they think the future will look like... but results not guaranteed.

Correct me if I'm wrong, but you consider "hard" disciplines like orbital mechanics and structural engineering to be science, and anything with less certainty in it to be not science, but statistics. This is inaccurate. Find me a scientific field that doesn't involve uncertainty and statistical analysis. Your examples of orbital mechanics and structural engineering certainly do. Conclusions made in both of these disciplines will always need to account for various sources of irreducible error (e.g., uncertainty in mass, temperature, altitude, fuel load; simplifying assumptions about atmosphere structure, gravity anomaly, solar wind, etc.). The importance of safety factors is the ultimate proof that uncertainty is core to engineering: https://en.wikipedia.org/wiki/Factor_of_safety

Science is the modeling of reality by formulating and testing hypotheses through observation and/or experiment. Does epidemiology not fall squarely within this definition? What do you propose as an alternative approach to inform governments and individuals what to do in the face of a natural phenomenon (a pandemic) which, although inherently uncertain, exhibits behaviors that are decidedly not random and inherently unpredictable?

Statistics by definition is not science. The vernacular usage of science refers to the empirical sciences; physics, chemistry, geography, biology. Mathematics, statistics, and computer science are all formal sciences, sometimes simply referred to as math.

See the application section of https://www.cdc.gov/csels/dsepd/ss1978/lesson1/section1.html.

And for when the two fields clash: https://www.nature.com/articles/s41467-018-04243-3

> To nitpick a bit: anyone who answers that question for a living will be practicing engineering, not science. Just as an excellent physician can espouse wildly unscientific beliefs, so too can someone become quite good at the craft of engineering without actually doing much science at all.

Engineering is based on science. They aren't scientists but what they do is based on science.

Science is the modeling of reality by formulating and testing hypotheses through observation and/or experiment. Does epidemiology not fall squarely within this definition?

This is really the heart of the issue, in 2020 at least (I hope people will go back to arguing about climatology soon!). In theory epidemiology does fall squarely within that definition. In practice if you read their papers you'll quickly discover most of them are entirely pseudo-scientific. I've read a lot of them this year. Here are some things that are absolutely standard in computational epidemiology (modelling) papers:

• Making predictions without writing a follow-up paper to study how closely observed data matched. Epidemiology routinely makes predictions that are wildly different to reality. This has no impact on the field at all. Science is meant to involve adjusting hypotheses if predictions don't match collected observational data, but in epidemiology step 1 is make a prediction with a model. Step 2, goto step 1.

• Making unfalsifiable predictions.

• Ignoring data that falsifies predictions.

• Altering predictions post-publication via public statements.

• Truncating graphs to hide data that would invalidate an argument.

• Using long since obsolete data, or data that aren't the best available when the paper is written. Invariably this makes the predicted epidemic worse, I've not yet seen anyone do this where it leads to better outcomes.

• Giving confidence intervals so wide they are equivalent to saying "we don't know what will happen" whilst not making that obvious.

• Incorporating model parameters that are simply made up, not based on any observational data.

• Engaging in circular reasoning.

• Ignoring basic biology. One of the most surprising things about epidemiological models is that they basically don't utilise any biology at all and epidemiologists will happily violate basic biological or historical common sense if it helps them achieve their goals. For example they calculate R0 using case curves. R0 is meant to be an intrinsic property of a virus representing how infectious it is, but one model I saw calculated a totally different value for COVID for each outbreak/country it was applied to. Clearly their values for R0 couldn't be correct, as it's the same virus everywhere so the values should be at least a little bit consistent. They were orders of magnitude different! This didn't bother anyone in the modelling team or anyone who peer reviewed their work at all. Another paper assumed Rt (case curve rate of change) could only change if government interventions forced it to, which flatly contradicts tens of thousands of years of experience in which epidemics rise and fall naturally, without lockdowns or masks of any kind. No peer reviewer quibbled with this, one even said it was a reasonable assumption.

I could go on all day. Maybe one day I'll write this up somewhere outside HN. But seriously, epidemiology is by far the most problematic field of "science" I've ever seen, and I read plenty of research papers from other fields. I don't consider what they're doing to be even slightly scientific: way too many papers are flat out intellectually fraudulent.

Your experience and comment history during the Covid-19 crisis merits authoring a book possibly? You have, over time, contributed much insight but this forum is not the best one for an excellent writer.

Thanks! I'm not sure why your post was dead but seeing as you're so nice to me, I vouched for it to bring it back.

As Asimov once said: "It is not so much that I have confidence in scientists being right, but that I have so much in nonscientists being wrong." Right now there are people running around saying that COVID is as deadly as the flu, that the pandemic was faked, that masks are a conspiracy. You don't have to believe that epidemiologists are 100% correct about every recommendation during a fast-developing emergency in order to see how the rejection of evidence and conspiracy-theorizing are harmful.

> Right now there are people running around saying that COVID is as deadly as the flu, ...

Which is the current best estimation of the risk of getting covid-19 and dying?

Which is the current best estimation of the risk of getting flu and dying?

I actually would have guessed they were pretty close. Apparently I was wrong:

The following claims 5% vs .2%

https://www.businessinsider.com/coronavirus-death-rate-us-co...

Then again this chart seems to indicate something closer to 2% of confirmed cases are fatal for Covid:

https://ourworldindata.org/grapher/total-deaths-and-cases-co...

I imagine more non-fatal Covid cases go unreported than fatal ones so perhaps even that's high, but it's still close to an order of magnitude worse than the flu.

Edit:

That first source isn't great, and is outdated anyways. This one seems to verify the ~2% for Covid in the US.

https://coronavirus.jhu.edu/data/mortality

I think you're mixing up IFR with CFR.

Current best estimate of COVID IFR is 0.27%, which is basically the same as flu.

https://www.who.int/bulletin/online_first/BLT.20.265892.pdf

However the CI is extremely wide.

> Right now there are people running around saying that COVID is as deadly as the flu

COVID is as deadly as flu. Some people just underestimate flu, as if it's something not dangerous.

> that the pandemic was faked

Technically all pandemics are faked, because what is and isn't pandemic is more or less an arbitrary decision made by some official purely for propaganda and obedience reasons. It doesn't actually matter if it's called pandemic or not.

> how the rejection of evidence and conspiracy-theorizing are harmful

Evidence based reasoning is not much different from superstition, it could be just as harmful as rejecting evidence to whatever you think rejecting evidence is harmful. To illustrate how faulty that reasoning is, here you are rejecting evidence that there was a literal conspiracy against general population with some officials and institutions telling people that masks don't work, an evidence they are liars, but somehow you don't want to consider that evidence in your evidence-based reasoning and suggest that others should not reject evidence from liars.

Of course you can't just accept evidence if you want something more than a superstition level decision making. For that you need to actually think and calculate, with all those base rates and probabilities, use something like bayesian reasoning or whatever, do some science. Even just quickly estimating this is still better than "accepting evidence".

> Some of the most scientifically illiterate people I've encountered are the people who say things like, "We listen to the science when it comes to COVID-19". Let us be perfectly real. When it comes to political decisions based on forecasts, you are not "listening to science".

This feels like a straw man to me.

First, let's be very clear: There is absolutely a cohort of people out there who are objectively denying the scientific reality of covid. Those denials ranges from the absurd (e.g. covid doesn't exist, it's a conspiracy, it's going away), to the distorted (e.g. covid is no worse than the flu), to the simply wrong (e.g. masks don't protect you, they actually make you sick).

I think the refrain "we listen to the science when it comes to COVID-19" is short hand for distinguishing oneself from folks in the groups above.

Let's also be clear that statistics and modelling are scientific methods. I'm frankly a little baffled that you've attempted to draw a line between these two things. Science can absolutely help you assess questions like "How long should we quarantine to minimize health impact, and maximize economic recovery?" Will the answers be probabilistic? Yes, absolutely. That doesn't make them any less scientific, and to suggest they are suggests its own form of "scientific illiteracy".

Further, "the science" is very clear: lockdowns are effective, masks help, social distancing helps, contact tracing helps, and so on. "The science" is also clear that none of these are quick fixes or panaceas. They're all part of a web of interventions that each provide some small measure of protection that, taken together, can help keep the pandemic under control. This is the "Swiss cheese" metaphor in action.

Science can also be used to assess the effectiveness of these methods versus their tradeoffs by, again, employing statistical approaches. Are those methods foolproof? No. But they're far from guesswork. I'd argue it's this basic misunderstanding that leads people to, for example, dismiss climate modelling...

Now, ultimately, the decision as to what to do is a political one, not because statistical models and methods are flawed or inaccurate, but rather because there's always going to be a range of trade-offs, and the trade-offs we make are ultimately a political decision.

But the least we can do is expect our politicians--not to mention the people around us--to assess those trade-offs based on rigorous facts and statistical methods. That's what "listening to science" means.

> Further, "the science" is very clear: lockdowns are effective, masks help, social distancing helps, contact tracing helps, and so on.

Of your list of things, masks and lockdowns aren't very clear - they don't seem to be helping given the resurgence this fall. Lockdowns might even have made it worse, pushing people indoors where it spreads easier and there's less sunlight, instead of encouraging social distancing in wide-open outdoor areas.

If anything, it seems COVID-19 is seasonal, and introduction of lockdowns and masks in the spring just coincided with when it was waning anyway.

I think that you are building strawman of what "listening to scientists" in the context of covid is like and then kill that strawman, basically.

Listening to scientists in the context covid will not tell you exactly how long quarantine should be. But it gives you multiple predictions you can start with and then over time see which are more correct and which are less correct.

It does also answer some of quite sure responses to questions that actually ended up disputed. Like: does the Covid have ability to overrun healthcare system? Do asymptomatic spread exists? Is the Covid just a little flu?

>"How long should we quarantine to minimize health impact, and maximize economic recovery?"

You're not asking a scientific question, you're asking a political one, because you also want the economy to do well, which is political.

There are two conflicting questions there, in reality; "How long can we quarantine without affecting the economy?" (Answer is like 0 days)

And "How long must we quarantine to eradicate the virus?" (Answer is around 140 days if a single quarantine unit contains up to 10 people and they infect eachother on the last day of symptom-freeness).

Because the question is not only political but considers two conflicting requirements, you can either satisfy both in a bad way or satisfy one well and abandon the other.

A similar situation occurs when you are tasked with optimizing the material usage for a product. Science can tell you how little product material you need so that it performs to spec and it can tell you how much you need so that it'll perform it's function as long as possible. The balance informs the price of the product but politically capitalism wants you to prefer a low price, similar to how capitalism will prefer no quarantine and lockdown.

Apparently on HN, you're not allowed to admit there are tradeoffs in the current situation especially to do things that some consider to be unnecessary.

You can have tradeoffs but then you're no longer answering scientific questions but either a political question or a question of personal belief (ie, "which you think is better").

Of course. Science can help you e.g. estimate risk. But balancing that risk against other factors has to be a political and/or personal tradeoff. There's no way it could be otherwise. Science, even if it could provide perfect information, doesn't have the tools to make policy decisions. Whether schools should be wide-open, hybrid, or remote only is not a scientific decision although, of course, whatever scientific data is known or thought to be known should of course factor into any decision.

That is exactly the point but also somewhat auxiliary; when people say things like "science can't answer these questions" the issue is either that the question is already politically loaded or requires a tradeoff between two opposing goals, where this balance is policy not science. Science can't solve all our problems but at the same time, it doesn't mean we should discount science when trying to solve them.

When I ask people to listen to science, that doesn't mean "have science solve the problem entirely" but "all viable solution maxima are scientifically solvable, the tradeoff is ethical". If someone suggests a solution that is not scientifically solvable, then it ought to be disregarded or considered for what is it is; pure politics, something you have to think about morally and ethically.

Edit: see replies below this post which clarify what was intended. My response was based on a misunderstanding; that cleared up, I now agree with the poster.

---

> When it comes to political decisions based on forecasts, you are not "listening to science".

if those forecasts are based on science/maths, yes you are listening to science.

> Ultimately, that question does not have a scientific answer

yes it does, just the best science can do (as in, estimate) based on limited data. If you want better than that, drop to your knees and ask god because that's all that's left.

Your post badly misunderstands what science is.

I think you are misrepresenting the parent which explicitly mentions tradeoffs. Science can help inform those tradeoffs but cannot make them for you. At the risk of reopening a rather heated discussion from yesterday, "science" cannot answer the question of whether it is reasonable to have a policy allowing outdoor dining in, say, NYC.

ADDED: Science can (probably and imperfectly) help you estimate how risky a given behavior is likely to be. However, it cannot tell you whether, say, a presumably low risk activity (both personally and in terms of disease spread) should be allowed given economic impact, people's social needs/wants, etc.

This is perfectly what I wanted to say, but was incapable of saying. Thank you.

What science can do is provide estimates with error bounds. Sometimes the error bounds are extremely large during a developing situation, and people should absolutely be aware of that. There's a major discussion to be had about risk/reward tradeoffs in the face of high uncertainty. (E.g., the relative cost of mandating face coverings is pretty low, even if the science is temporarily uncertain.)

However it becomes impossible to have such discussions when a large contingent of the population are ignoring all of the scientific data, and instead basing their opinions on motivated reasoning, faith, or political preferences.

I don't disagree with any of that. Indeed, there are many policies and behaviors that probably fall into the "better safe than sorry" category--given how much noise and uncertainty there is in the data--although even possibly reasonable people will vehemently disagree about what precise policies/behaviors that applies to. (As you see from voting patterns and discussions here.) And, yes, I also agree that face coverings under at least many circumstances fall into that category.

At the same time, there are different tradeoffs because different people (and governments) are approaching risks and rewards differently even if the facts were known with high certainty.

For what it's worth, "science" in many fields is inherently statistical. Statistical illiteracy is arguably more pervasive and insidious than "scientific" illiteracy.

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