Problem with science today and the war on reason

[jedishrfu]

A recent Guardian article discusses the problem with science today and the war on reason:

https://www.theguardian.com/science...ication?utm_medium=email&utm_source=flipboard

 

[gleem]

A link of your reference provides additional insight into the problem of why people seem to be resistant to scientific facts.

https://www.theguardian.com/science...ists-losing-science-communication-skeptic-cox

 

[Choppy]

The "scicomm" effect may be a contributing factor to people being less willing to accept science, but I don't think it's completely at fault.

I think you have to go deeper and look at phenomena like confirmation bias. A reasonable person who is willing to be swayed by the balance of evidence will consider details behind scicomm statements. A person with a predetermined position will either comb through details for weaknesses, or invent "possible" details if the statements do not agree with said position. If the statement supports his or her predetermined position, that person is likely to ignore the details completely.

I think there's also the "boy cried wolf" factor. The damage that's done from scandals like that autism-vaccine fraud is enormous. Even when the truth of the matter comes out that the paper was completely wrong, you still end up with a decrease in the level of trust that the public affords to scientific institutions.

Other factors:
- growing distrust of authority in general
- exposure to mass commercial media makes people skeptical of just about everything they hear
- binary vs spectral conditions: whether you accept creation or not is reasonably black and white, with climate change there are different positions: the climate isn't changing at all, the climate is changing, but humans aren't at fault, the climate is changing and humans are part of the problem, the climate is changing and carbon emission from human activities is the primary reason, etc.

 

[PeterDonis]

I think scientists themselves, at least the ones that go in for pop science books and TV specials (Brian Greene is my go to example for this, because of the number of threads in the physics forums here that have been based on misconceptions a lay person has gotten from one of his books or shows) are partly to blame, by not carefully distinguishing varying levels of confidence in different parts of science. Greene, for example, will talk about way-out speculations or extrapolations of quantum physics (such as saying that QM says there is some small probability that you can teleport through a wall) the same way he talks about results with strong experimental confirmation (such as the behavior of individual qubits in quantum computing). It's natural enough for the audience to think that Science is telling them the first is just as well confirmed as the second.

In short, scientists who do popularizations often succumb to the temptation to portray science as an Authority, instead of as a tool for everyone to use to develop their own independent understanding. And then, when the Authority ends up saying things that turn out to be wrong, people flip to the other extreme and don't believe anything scientists say.

 

[brainpushups]

Today's Vermont Edition (local public radio talk show) was a discussion about the public perception of science. I only caught about half of it live, but I'll plan on listening to the entire show soon. I thought the discussion was good. You can listen to the program here.

 

[Borg]

At least one university is trying to educate their students in how to decipher the truth:
University offers course to help sniff out and refute BS

Interesting course title.
Calling Bulls... in the Age of Big Data

 

[Greg Bernhardt]

I see a lot of people resisting credible scientific claims because of two related reasons.

1. They toss the basket of apples because a few went bad. There is bad science out there and studies that are fraudulent, poorly designed or political. Some even get big media attention. When finally debunked this creates a skepticism and distrust in the viewer next time they read a headline. I just came across this article which doesn't help either Most scientists 'can't replicate studies by their peers'.

2. Science is changing and improving all the time, but people see this aspect of science as negative. One day eggs are bad for you, the next they are good etc. One day we understand gravity the next is a headline saying maybe we got it all wrong etc. This leads some people to doubt everything categorically. Or able to pick and choose and then point to a case when science was wrong in the past and corrected itself later.

In short, scientists who do popularizations often succumb to the temptation to portray science as an Authority, instead of as a tool for everyone to use to develop their own independent understanding. And then, when the Authority ends up saying things that turn out to be wrong, people flip to the other extreme and don't believe anything scientists say.

This is spot on. Some people see scientific claims as an arrogance and resist the presentation of authority. You will see these people refer to science as a dogma or religion.

Science educators and communicators have a massive task in front of them because as we've seen with some cabinet picks it doesn't matter what the scientists think if the general public isn't on board.

 

[PeterDonis]

Science is changing and improving all the time, but people see this aspect of science as negative. One day eggs are bad for you, the next they are good etc.

I think this is an example of scientists miscommunicating with the public. In the example of eggs, what happened was not that we had a valid scientific theory that said eggs were bad for you, and then we discovered that that theory was incomplete and a more complete theory said eggs were good for you after all. In other words, it was not anything like, for example, the transition from Newtonian physics to relativity. We never had a scientific theory that said eggs were bad for you in the first place. What we had was a highly heuristic guess based on one very incomplete understanding of how human metabolism worked, which was replaced by another highly heuristic guess based on another very incomplete understanding of how human metabolism worked. Neither guess was supported by controlled experiments, and neither guess had very strong statistical backing.

Yet when scientists said "eggs are bad for you", they presented it as Scientific Fact, and the public believed them. But Scientific Fact isn't supposed to change; you're only supposed to use that kind of strong statement when you have extensive support from controlled experiments and you can demonstrate impressive predictive power--in other words, when there is extremely high confidence that what you say is not going to change. The astronomers who calculate the trajectories of near-Earth asteroids fifty years out don't come back every so often and say their models were way off and all the numbers they said before should be thrown out. And that's true even though they're using Newtonian physics, not GR, to calculate. As Steven Weinberg once said, "If you have one of those t-shirts with Maxwell's Equations on them, you might worry about it going out of fashion, but not about the equations becoming false." But very few scientific fields actually have that high level of confidence.

I just came across this article which doesn't help either

This article actually reinforces what I said above. IMO its title should have been "Most claims that were said to be scientific actually weren't." The replication issue is not new; the media has been confused about it for years, because they don't understand that much of what is being told to them as Scientific Fact, isn't. The replications fail because the original experiments weren't actually showing a real effect to begin with. At least, that's my take.

Some people see scientific claims as an arrogance and resist the presentation of authority.

If scientists make claims of Scientific Fact that later have to be reversed, IMO the public is right to view that as arrogance and a presentation of authority and to resist it. If you present yourself as an authority, you have to have the predictive power to back that up. Many claims of Scientific Fact simply do not have that predictive power, and should not be presented that way. Until scientists fess up to this and take extreme care to distinguish different levels of confidence in different claims, they will continue to have this problem of public disbelief.

 

[Greg Bernhardt]

What we had was a highly heuristic guess

The media has a role in how they report the research as well. We've already talked at length on PF already about how media stories distort research for good headlines. I was just at the dentist and the dentist was telling me about the headline a few months ago where media was telling people about some research that proved flossing doesn't help. The dentist said the actual research was looking specifically at one type of bacteria and if flossing had any effect on it. Certainly that is different than claiming flossing is useless overall.

If scientists make claims of Scientific Fact that later have to be reversed, IMO the public is right to view that as arrogance and a presentation of authority and to resist it.

Yes but the problem is the damage from going back and forth. It creates distrust in layman. They think "why should we trust you now". I have actually found myself debating someone who said that to me. I found it difficult to respond other than to say look at our overall scientific progress and how it always increases year after year.

 

[PeterDonis]

The media has a role in how they report the research as well.

I agree, but I don't think journalists in general have the background knowledge to be able to make independent judgments about the level of confidence in a given piece of scientific research. In other words, they're in the same position as the average lay person. So I would not expect media reports to be any better than an average lay person taking a look at a paper and being able to tell what it says. How many average lay people would have been able to read the paper your dentist described and figure out what it actually said?

There is another way in which the media is more specifically responsible, which is that they claim to be doing journalism but are actually doing entertainment. But that is driven by market forces that are not going to be easy to change.

the problem is the damage from going back and forth.

Yes, and the only way to fix that is to not have to go back and forth, by not presenting anything as Scientific Fact unless it has the same level of confidence as, say, astronomers' predictions of asteroid trajectories. Which means that much, if not most, of what the average lay person currently thinks is Scientific Fact, isn't. It is going to change at some point in the future; we just don't know when or how.

 

[Greg Bernhardt]

In other words, they're in the same position as the average lay person.

There is another way in which the media is more specifically responsible, which is that they claim to be doing journalism but are actually doing entertainment.

Just like journals, different media have different credibility weights. I get the feeling that many media outlets are purposefully constructing misleading headlines to appease their marketing departments. The problem again is given the fake news epidemic it seems the average person has trouble (or is too lazy) to figure out if something is credible or not.

Yes, and the only way to fix that is to not have to go back and forth, by not presenting anything as Scientific Fact unless it has the same level of confidence as, say, astronomers' predictions of asteroid trajectories.

With the public's thirst for quick interesting news bites the media will continue this potentially destructive trend.

 

[Haelfix]

I agree, but I don't think journalists in general have the background knowledge to be able to make independent judgments about the level of confidence in a given piece of scientific research. In other words, they're in the same position as the average lay person. So I would not expect media reports to be any better than an average lay person taking a look at a paper and being able to tell what it says. How many average lay people would have been able to read the paper your dentist described and figure out what it actually said?

It's the same problem that we've always had, its just more manifest now b/c of the density of information people are being exposed too. In particular, i'd argue its a serious deficiency with our education in general, basically at the high school level. There is absolutely no reason why an 18 year old should be sent away from school, without knowing rudimentary statistics. It's the one area of mathematics that is absolutely guaranteed to be of critical importance to all humans lives, whether they realize it or not. Of course, it is also one of the more notoriously difficult subjects for first time students, so of course it is readily dismissed into the murkiness of liberal arts college (where students can easily get their requirements by avoiding the subject altogether).

It's such a problem, that we even have academics writing papers in the social sciences, who have barely the requisite grasp necessary to make correct probabilistic statements. Then our science writers can't even read an abstract or conclusion without mangling the meaning. It's just a complete mess, and it has to start at the beginning.

 

[PeterDonis]

With the public's thirst for quick interesting news bites the media will continue this potentially destructive trend.

Yes, that is what I was referring to as "market forces".

 

[gleem]

With the public's thirst for quick interesting news bites the media will continue this potentially destructive trend.

If you can't report it in 140 character or less they don't want to read it. Or worse it seems that they probably don't even know where to go to find a good source of factual information.

Then our science writers can't even read an abstract or conclusion without mangling the meaning. It's just a complete mess, and it has to start at the beginning

I don't think they necessarily don't understand the content in so much as they don't properly summarize the results in a way the readership will understand without distorting the conclusions. Some may disagree but I think some scientific studies should not even be reported to the public in the general press unless it has an immediate impact on them.

There is absolutely no reason why an 18 year old should be sent away from school, without knowing rudimentary statistics.

Much has been written about this but what good is it unless you are reading the original paper. An then it not only about the math but the validity of the assumptions and the overall study design. How many will go that far to get to the truth.

 

[Dr. Courtney]

How can we expect to do such a bad job in the science and math classrooms and then expect the average graduate to think properly and critically about scientific issues?

Failures of education are a pre-requisite for a "war on reason" to even be possible, at least among those who graduated from high school having passed with 3-4 years of science and 3-4 years of math.

 

[QuantumQuest]

An interesting article. I think that the gist, revolving around the fact that there is no possible effective way to communicate science through media - at least given the present conditions of life, education and all the other influencing factors, is not something that can - at least easily, change. There are three completely different entities from an educational perspective, scientists, media and non-scientists. I won't call the last "laypersons" because this is a very diverse set of people with education / expertise ranging from no-education-beyond-basics to technically well educated people and all in between, regarding many different qualities.

It absolutely stands to reason that what a scientist tells, will not be completely understood - unfortunately more often than not it will be poorly understood, by a media person and given the limitations but also the purposes of exposing a scientist's opinion to the general public, the whole thing will very likely end up being distorted and giving wrong impressions. Now, for the media part, the purposes of "giving scientific facts" range from pure informative to political and all in between. I don't blame media for this, they do their job but science according to its very nature, cannot be presented in the same way as any other thing that media brings to the public. This is the worst thing in my opinion that media do when they present scientific facts or discoveries and it is more than sure that anyone non-scientist, will take what he/she will listen to at its face value and - even worse, the way this face value is presented and finally, what will remain persistent as impression is a fact - like all the other things presented during a certain media program and not something possible that is anyway subject to further research. On the other hand, there is no other way for media to convey science: there is limited time and things must be communicated to audience simply. So, if anything good can be done for all this mess, is on the sides of scientists and general public.

For scientists I'll quote what PeterDonis said because this reflects accurately my opinion too:

I think scientists themselves, at least the ones that go in for pop science books and TV specials (Brian Greene is my go to example for this, because of the number of threads in the physics forums here that have been based on misconceptions a lay person has gotten from one of his books or shows) are partly to blame, by not carefully distinguishing varying levels of confidence in different parts of science. Greene, for example, will talk about way-out speculations or extrapolations of quantum physics (such as saying that QM says there is some small probability that you can teleport through a wall) the same way he talks about results with strong experimental confirmation (such as the behavior of individual qubits in quantum computing). It's natural enough for the audience to think that Science is telling them the first is just as well confirmed as the second.

In short, scientists who do popularizations often succumb to the temptation to portray science as an Authority, instead of as a tool for everyone to use to develop their own independent understanding. And then, when the Authority ends up saying things that turn out to be wrong, people flip to the other extreme and don't believe anything scientists say.

I think that scientists have to think very carefully about how they expose their knowledge and convey scientific meanings to the general public, while on some TV special or anything for that matter. This won't solve everything but at least it will limit the damage done to science in general. When something is initially presented from media as "A" but after some time becomes "A+", "A-" or even "B", general public usually will put the blame on scientists. It is rather rare for media to be blamed for this. After all, journalists and other media people are not scientists - and even the people who are, they are not active in current research.

On the other extreme, general public has to apply good filtering and personal search that is not at all difficult in our era of information flooding, for anyone. We can't ask for "fast and sure things" when the nature itself gives us very few of them. Also as Haelfix points out, there are serious deficiencies in education that have finally to be fixed.

 

[Student100]

Science itself has become diluted.

The social sciences, and some medical sciences to perhaps a lesser extent, are not a science, but their results are often reported as though they held the same rigor and predictive power of say, physics.

That is a shame because people often believe they do, until the picture becomes so muddled they throw the baby out with the bath water and just distrust science as a whole.

They should once again be called what they are, humanities, and those that report on their findings should try to dispel any notion of predictive power. That would be a start.

 

[Dr. Courtney]

I don't have time now, sorry; I'm about to go to bed. And tomorrow I have a very hard study day, no time then probably.

If this answer was intended as a parody, then it is brilliant.

If it is literal, then it demonstrates hypocrisy.

All communication occurs under constraints of time and resources. You cannot demand reasoning, justification, and nuance and yet refuse to provide it yourself.

The right to answer in sound-bite length responses reasonably requires accepting when others do so as well. Requesting longer, nuanced, answers demonstrating the desired complexity should offer the same considerations.

 

[UsableThought]

OK, I've deleted all my comments just now, as a way of withdrawing them until I can find time.

No hypocrisy, just fatigue and a belated realization & remembering I didn't have the time to get involved after that first reflexive post.

I do agree with this:

You cannot demand reasoning, justification, and nuance and yet refuse to provide it yourself.

I'll come back if I can. It's an important topic.

 

[brainpushups]

If scientists make claims of Scientific Fact that later have to be reversed, IMO the public is right to view that as arrogance and a presentation of authority and to resist it. If you present yourself as an authority, you have to have the predictive power to back that up.

I'm reminded of Feynman's '71 Caltech commencement speech (where he coined the phrase cargo cult science). It does seem that the type of utter honesty that he professed was essential to science has continued to erode in scientific communication. As he put it, the first thing a scientist must do is learn not to fool themselves and then it is easy not to fool others after that. I don't know whether there are just more instances of scientists fooling themselves or whether Feynman understated how easy it is to fool others! Pasteur also expressed similar sentiments:

When you believe you have found an important scientific fact, and are feverishly curious to publish it, constrain yourself for days, weeks, years sometimes, fight yourself, try and ruin your own experiments, and only proclaim your discovery after having exhausted all contrary hypotheses. But when, after so many efforts you have at last arrived at a certainty, your joy is one of the greatest which can be felt by a human soul.

I wonder if part of the problem is that the system for funding, tenure, etc. perhaps puts too much pressure on scientists to get positive results. My wife is a veterinarian and she often complains about the studies she sees published. There was one in the last issue (I think) of JAVMA which discussed a new (presumably effective) cancer treatment. The sample size for the study was 6 dogs. Perhaps an example of the cargo cult tendencies for the medical sciences?

A related issue that was discussed in the radio program I linked in post 5 is that null results don't often (ever?) get published. This seems like an absolutely essential tweak (overhaul?) that needs to be made to the databases of scientific literature.

How can we expect to do such a bad job in the science and math classrooms and then expect the average graduate to think properly and critically about scientific issues?

The NGSS have done a good job of reframing the purposes of national standards for science in that a greater emphasis is placed on reasoning than on content. This doesn't fix the problem, but I think it is a step in the right direction. Assessing the validity of the ideas should really be the central question around which any science course content is framed (at least for introductory courses – but perhaps upper level college courses too). This can also be the lens through which skills are taught.

They should once again be called what they are, humanities, and those that report on their findings should try to dispel any notion of predictive power. That would be a start.

I tend to agree that social 'sciences' are more pseudoscientific than not. Note, however, that Popper's demarcation criterion (which essentially boils down to predictive power) is often viewed as too strong a criteria for something to be considered science (even by Popper himself after he published his ideas). For example, Darwin's theory doesn't have predictive power but is considered scientific. As new conceptual frameworks emerge in science (even physics) they often don't have predictive power but can nonetheless develop into fruitful theories. I don't know when the right time for communication to the public about new conceptual schemes is appropriate. I see benefit here in generating excitement (perhaps just as the loathed-by-many popular accounts of modern physics do) but also danger based on what has been mentioned in this thread.

 

[PeterDonis]

Darwin's theory doesn't have predictive power

Yes, it does. For example, evolutionary biologists predicted that overuse/misuse of antibiotics would lead to the evolution of antibiotic-resistant bacteria.

It doesn't have as strong predictive power as, say, quantum electrodynamics. But it certainly can make predictions, and those predictions can be and have been tested.

 

[PeterDonis]

As new conceptual frameworks emerge in science (even physics) they often don't have predictive power but can nonetheless develop into fruitful theories.

Can you give specific examples?

 

[Dr. Courtney]

Can you give specific examples?

Some examples of Physics without predictive power (or very little) are multiverses and string theory.

 

[PeterDonis]

Some examples of Physics without predictive power (or very little) are multiverses and string theory.

But these haven't developed into fruitful theories at this point. So they aren't examples of your claim.

 

[Dr. Courtney]

I'm reminded of Feynman's '71 Caltech commencement speech (where he coined the phrase cargo cult science). It does seem that the type of utter honesty that he professed was essential to science has continued to erode in scientific communication. As he put it, the first thing a scientist must do is learn not to fool themselves and then it is easy not to fool others after that. I don't know whether there are just more instances of scientists fooling themselves or whether Feynman understated how easy it is to fool others! Pasteur also expressed similar sentiments...

Agreed, mostly. I don't mind experimental results being published to allow others to consider and build on them. Most of my objections are when the interpretation.

A related issue that was discussed in the radio program I linked in post 5 is that null results don't often (ever?) get published. This seems like an absolutely essential tweak (overhaul?) that needs to be made to the databases of scientific literature.

Most journals are not interested in publishing null results. Why should a PI bother to write the paper and attempt to shepherd through the peer review and publishing process when the odds of actually getting into print are so small. "Importance" is too big a criteria in the publishing process.

The NGSS have done a good job of reframing the purposes of national standards for science in that a greater emphasis is placed on reasoning than on content. This doesn't fix the problem, but I think it is a step in the right direction. Assessing the validity of the ideas should really be the central question around which any science course content is framed (at least for introductory courses – but perhaps upper level college courses too). This can also be the lens through which skills are taught.

Agreed.

I tend to agree that social 'sciences' are more pseudoscientific than not. Note, however, that Popper's demarcation criterion (which essentially boils down to predictive power) is often viewed as too strong a criteria for something to be considered science (even by Popper himself after he published his ideas).

Popper was right. Even if we fall short of excluding everything from science that fails to meet Popper's criterion, we should at least acknowledge and freely identify science which meets Popper's criterion from (pseudo) science that does not.

 

[Dr. Courtney]

But these haven't developed into fruitful theories at this point. So they aren't examples of your claim.

Circular fallacy. No fruitful theory would fail to make predictions.

We sure spent a lot of money on string theory not to have a fruitful theory.

 

[PeterDonis]

Circular fallacy. No fruitful theory would fail to make predictions.

Sorry, I got mixed up, the claim I was talking about (which said there could be fruitful theories that did not have predictive power) was made by brainpushups, not you.

 

[brainpushups]

Yes, it does. For example, evolutionary biologists predicted that overuse/misuse of antibiotics would lead to the evolution of antibiotic-resistant bacteria.

I left out a key element which is that Popper's criterion hinges on falsifiability, not just testability. "X will evolve" is not a falsifiable claim.

Can you give specific examples?

Aside from those mentioned by Dr. Courtney, a historical example of a concept in physics which had no predictive power at the time of its introduction yet developed into a core principle is Ockam/Buridan's theory of impetus.

Perhaps another example, if you'll accept it, is that of phlogiston. Of course, this theory was replaced rather than augmented as in the case of impetus, but the concept of of phlogiston (which is not too dissimilar to that of oxidation – backwards really) was widely accepted, had no predictive power and helped catalyze the development of more fruitful theories.

EDIT: Oh, and the theory of atoms progressed in a similar vain.

Most journals are not interested in publishing null results. Why should a PI bother to write the paper and attempt to shepherd through the peer review and publishing process when the odds of actually getting into print are so small. "Importance" is too big a criteria in the publishing process.

Right, but in the case of medical research isn't there the risk of repeating studies on drugs (for example) that were shown to have no effect? It seems like having access to, and information about, null results could help streamline certain fields of research.

 

[Student100]

I left out a key element which is that Popper's criterion hinges on falsifiability, not just testability. "X will evolve" is not a falsifiable claim.

Sure it is? X will remain invariant.

Aside from those mentioned by Dr. Courtney, a historical example of a concept in physics which had no predictive power at the time of its introduction yet developed into a core principle is Ockam/Buridan's theory of impetus.

That is probably the worst example you could use. The theory of impetus is not a core principle in physics and was several hundred years before modern scientific study was even formalized.

Perhaps another example, if you'll accept it, is that of phlogiston. Of course, this theory was replaced rather than augmented as in the case of impetus, but the concept of of phlogiston (which is not too dissimilar to that of oxidation – backwards really) was widely accepted, had no predictive power and helped catalyze the development of more fruitful theories.

Again, your examples aren't addressing the initial claim, that predictive power is somehow not a a defining element of science. The phlogiston hypothesis made predictions, thus it had predictive power, that just turned out to be wrong when experimentation tested those predictions.

EDIT: Oh, and the theory of atoms progressed in a similar vain.

Are you talking about plum pudding and Rutherford? All those models made predictions too, that could be tested. That's how they were refuted.

 

[PeterDonis]

"X will evolve" is not a falsifiable claim.

As I stated it, that's true, strictly speaking, since I didn't give a time frame. But the actual prediction did--not in terms of clock time, but in terms of generations of bacteria that it would take for resistance to evolve. Predictions of that sort have been verified, AFAIK, in controlled experiments (exposing bacteria to various antibiotic compounds in test tubes), not just by clinical observation. So they are certainly falsifiable--the experiments could have not worked.

Aside from those mentioned by Dr. Courtney,

Which, as I said, are not examples of your claim, because they have not let to fruitful theories at this point.

a historical example of a concept in physics which had no predictive power at the time of its introduction yet developed into a core principle is Ockam/Buridan's theory of impetus

I'd be interested to look into this. Do you have any references that discuss it?

the concept of of phlogiston (which is not too dissimilar to that of oxidation – backwards really) was widely accepted, had no predictive power and helped catalyze the development of more fruitful theories

I'm not sure it actually helped; from my knowledge of the history of chemistry, if it did anything it impeded the development of more fruitful theories. One of the reasons for that, I think, is that phlogiston was not just "oxidation backwards". It was much vaguer than that.

 

[Dr. Courtney]

I left out a key element which is that Popper's criterion hinges on falsifiability, not just testability. "X will evolve" is not a falsifiable claim.

One issue is that in evolution, the definition of evolution in specific predictions, as well as the specific nature of the predictions is harder to pin down. Usually, the claim of confirmation by prediction is made only AFTER the change is observed.

Using the definition of "change in allele frequencies over time" observation of evolution is trivial.

I think we can all agree that validated predictions of the future emergence of new species would be more impressive.

But even more interesting might be the ability to predict things like which species will evolve, which will move, and which will be extirpated in response to warming trends in specific regions.

If we really understood both evolution and global warming, shouldn't we be able to accurately predict which species have the capabilities to evolve fast enough to survive and which do not?

Aside from those mentioned by Dr. Courtney, a historical example of a concept in physics which had no predictive power at the time of its introduction yet developed into a core principle is Ockam/Buridan's theory of impetus.

Perhaps another example, if you'll accept it, is that of phlogiston. Of course, this theory was replaced rather than augmented as in the case of impetus, but the concept of of phlogiston (which is not too dissimilar to that of oxidation – backwards really) was widely accepted, had no predictive power and helped catalyze the development of more fruitful theories.

EDIT: Oh, and the theory of atoms progressed in a similar vain.

Great points. Scientists often miss the distinction between descriptive and predictive until the descriptive theory gets replaced with a better model with real predictive power.

Right, but in the case of medical research isn't there the risk of repeating studies on drugs (for example) that were shown to have no effect? It seems like having access to, and information about, null results could help streamline certain fields of research.

Of course. Null results should be published. But it seems to me that this requirement should be supported and enforced by the funding agencies rather than by external authorities. And in a business environment, why does one company who funded drug research care if another (competing) company wastes money on a dead end product?

Again, your examples aren't addressing the initial claim, that predictive power is somehow not a a defining element of science. The phlogiston hypothesis made predictions, thus it had predictive power, that just turned out to be wrong when experimentation tested those predictions.

I think you are confusing "predictive power" with falsifiability. Perhaps "predictive power" has not been defined as well as Popper defined "falsifiability." I do not see them as synonyms. For me, "predictive power" means able to reliably make CORRECT predictions of future events.

Falsifiability just means able to make predictions which are capable of being falsified in future experiments, whether or not they are.

So a theory that makes wrong predictions is falsifiable but has no predictive power.

A theory that makes right predictions is falsifiable and has predictive power.

 

[Evo]

One issue is that in evolution, the definition of evolution in specific predictions, as well as the specific nature of the predictions is harder to pin down. Usually, the claim of confirmation by prediction is made only AFTER the change is observed.

Using the definition of "change in allele frequencies over time" observation of evolution is trivial.

I think we can all agree that validated predictions of the future emergence of new species would be more impressive.

But even more interesting might be the ability to predict things like which species will evolve, which will move, and which will be extirpated in response to warming trends in specific regions.

If we really understood both evolution and global warming, shouldn't we be able to accurately predict which species have the capabilities to evolve fast enough to survive and which do not?

Since evolution doesn't fall into anything you mentioned, no. No, we don't understand either of them and so we will not discuss them.

If we really understood both evolution and global warming, shouldn't we be able to accurately predict which species have the capabilities to evolve fast enough to survive and which do not?

Why on Earth would you think that? I'm left without words. "We know how cancer forms, why can't we stop it?" And I could go on and on.

 

[Dr. Courtney]

Since evolution doesn't fall into anything you mentioned, no. No, we don't understand either of them and so we will not discuss them.

One issue is that in evolution, the definition of evolution in specific predictions, as well as the specific nature of the predictions is harder to pin down. Usually, the claim of confirmation by prediction is made only AFTER the change is observed.

Using the definition of "change in allele frequencies over time" observation of evolution is trivial.

I think we can all agree that validated predictions of the future emergence of new species would be more impressive.

But even more interesting might be the ability to predict things like which species will evolve, which will move, and which will be extirpated in response to warming trends in specific regions.

If we really understood both evolution and global warming, shouldn't we be able to accurately predict which species have the capabilities to evolve fast enough to survive and which do not?

Why on Earth would you think that? I'm left without words. "We know how cancer forms, why can't we stop it?" And I could go on and on.

We can only predict cancer in a probabilistic sense: a smoker has yy% chance of lung cancer, but a non-smoker has a zz% chance of lung cancer.

Our understanding will be much better when we can say, "Given your genome, you will (100%) or will not (0%) develop lung cancer if you smoke ZZ packs a day."

I have an identical twin with type 2 diabetes. That gives me a 95% chance of getting it myself. We know that in many cases, type 2 diabetes results from too much weight, too much unhealthy food, and too little exercise. But these are just risk factors that allow probabilistic risk assessments (at least for most folks without identical twins). I know with much more certainty than most that if I weigh over YY lbs, I will get type 2 diabetes. Won't we understand type 2 diabetes better when the same certainty of prediction is available for everyone?

And so it is with every theory (even your sacred cows), they will be better when they can make more definite and more reliable predictions.

And the fact that a scientific theory can be better in the future, means it is not as good as it can be now. For example, we've published work showing that cutthroat trout outcompete rainbow trout in lentic ecosystems. This allows the prediction that (in those systems), the genetic makeup will likely tend to shift in favor of cutthroat genetics, which is the opposite of what has shown to be happening in lotic ecosystems. In lotic ecosystems, rainbow trout outcompete and the genetics quickly shift away from cutthroat. At some point, improvements in understanding competitive and selection forces should allow more definite predictions in how allele frequencies change over time: which species will win and which will lose.

Theories with more specific predictions should always be favored over theories with only vague predictions or mere descriptions.

 

[brainpushups]

Again, your examples aren't addressing the initial claim, that predictive power is somehow not a a defining element of science.

Perhaps I didn't do a good job explaining myself at first. I'm not arguing that prediction is not an essential element of science. I was arguing that, in the early stages of scientific development the ideas are often (as Dr. Courtney mentioned) descriptive rather than predictive. Call it 'proto-science' if you'd like. I stand by my examples, but I don't want to waste space here arguing about it. Happy to do so elsewhere!

Getting back to the main point of the thread: it is impossible to tell which ideas will eventually become fruitful. The majority of them certainly do not. To quote myself:

As new conceptual frameworks emerge in science (even physics) they often don't have predictive power but can nonetheless develop into fruitful theories. I don't know when the right time for communication to the public about new conceptual schemes is appropriate. I see benefit here in generating excitement (perhaps just as the loathed-by-many popular accounts of modern physics do) but also danger based on what has been mentioned in this thread.

My main question was about the relationship between science reporting (especially of new ideas, but experimental confirmation could be part of this) and public perception. Taking the example of string theory - a widely written about subject in popular science - we have widespread discussion about a theory which, at the present time is arguably non-scientific (not because of prediction, but because of measurement). The idea generates interest in science while simultaneously (perhaps) harming public perception. So what is appropriate? As another historical side-note: Mach (who was a hard-core positivist) argued in the late 1800s that atomic theory was also non-scientific because there were, at the time, no measurement tools/techniques available to confirm or refute the hypothesis. Are we at the same stage here with string theory?

Also, getting back to education: the NGSS are attempting to focus student achievement on broader skills than just content knowledge. One thing that is not articulated well in any of the standards (to my recollection) is anything about how science progresses. If there was more focus on this then maybe the reporting of false findings or proto-science would be a non-issue because more people would understand how science evolves.

 

[Dr. Courtney]

Also, getting back to education: the NGSS are attempting to focus student achievement on broader skills than just content knowledge. One thing that is not articulated well in any of the standards (to my recollection) is anything about how science progresses. If there was more focus on this then maybe the reporting of false findings or proto-science would be a non-issue because more people would understand how science evolves.

One thing I love about the science portion of the ACT is that it requires very little content knowledge and focuses on the logical process of drawing inferences from given information in a scientific manner.

Students who have had strong lab courses and teachers who emphasized the scientific reasoning and thinking process tend to do much better on the science portion of the ACT than students from classes that focus overwhelmingly on content knowledge.

I like my students to read Bacon, Galileo, Wigner, etc. My preferred high school curriculum spends equal time on laboratory science as on content knowledge. Very expensive and labor intensive to implement though.

 

[brainpushups]

I'd be interested to look into this. Do you have any references that discuss it?

A Sourcebook in Medieval Science edited by Edward Grant. Page 275 contains excerpts from Buridan's treatise on the subject.

 

[brainpushups]

Of course. Null results should be published. But it seems to me that this requirement should be supported and enforced by the funding agencies rather than by external authorities. And in a business environment, why does one company who funded drug research care if another (competing) company wastes money on a dead end product?

But maybe running science like a business is part of the problem. I think that science would operate best if researchers could transcend capitalism. Knowledge for knowledge's sake! Hard to imagine getting back to that without scientists just being independently wealthy, but the profit motive of research is another one of the contributing factors to public distrust and dislike of science. I recall hearing years ago that certain drugs were being intentionally held back from the public because of patents. I don't know how true this is, but a quick google search uncovers a lot of popular articles on the subject.

 

[nikkkom]

What I see is that people doubt everything they hear or read - and this is a good thing.

Human civilization had HUGE problems when people were required to unquestioningly accept prevailing beliefs (religion, "the King has a divine right to rule over us", etc). It took many centuries to get rid of that.

Of course, in the population of billions of people, there will be crackpots which see a conspiracy and lies everywhere. (I just watched a flat earther youtube video which was discussing recent SpaceX launch and how "obviously fake" it is). Ignore the nutty ones (but accept that they will always exist); argue with those having doubts who nevertheless look rational.

 

[anorlunda]

Other factors:
- growing distrust of authority in general
- exposure to mass commercial media makes people skeptical of just about everything they hear
- binary vs spectral conditions: whether you accept creation or not is reasonably black and white, with climate change there are different positions: the climate isn't changing at all, the climate is changing, but humans aren't at fault, the climate is changing and humans are part of the problem, the climate is changing and carbon emission from human activities is the primary reason, etc.

I think you're on the right track. I attempt similar analysis, but my perspective is a bit different.

The most notorious clash between science and the public has to do with climate change. Climate science is one thing. Remedial actions (including possibly no action at all) is not science, it is a moral question having to do with values. Some scientists say publicly, "We predict climate change. Therefore you better do what we say regarding renewable energy or else you are an anti-science denier," I view that as scientific malpractice that misrepresents their opinions on human behavior and morality as being scientifically based. Even scientists whose field has nothing to do with climatology, are telling the public that only scientists should be allowed to have valid opinions about climate or climate remedies.

Another case. I know of a young girl studying MWI at Dartmouth. She plans to make MWI study her career. That means a lifetime living on public money, having no accountability or ever being required to produce a deliverable that advances the state of the art. When taxpayers object, they are told to shut up. As non-scientists they are not entitled to voice opinions. The public views science as yet another special interest group with their hands out demanding public money, but refusing to justify their demands except to fellow scientists. If you disagree, show me a scientific community that does not believe that more money, more power, more influence, more fame for themselves would not be a good thing.

I would not use the word authoritarian. I think "scientific priesthood" is a better description. Some in the public fear such a priesthood and imagine (rightly or wrongly) that they are being told by this priesthood "Hear, believe, and obey us on all matters that we deem science-related."

I also believe that we need a bit of realism in what we expect from public behavior. Public opinion is an extremely blunt instrument. There is no mechanism to accurately articulate the what and why of public opinion. When the public is angry at some group, their ire has no surgical precision, they simply lash out regarding anything and everything the target group does or says, often quite irrationally. By analogy, when lovers spat, it is common for them to say hurtful things that make no sense. Critics of the public focusing on such irrationality fail to address the root issues that cause the public anger in the first place.

 

[Dr. Courtney]

I would not use the word authoritarian. I think "scientific priesthood" is a better description. Some in the public fear such a priesthood and imagine (rightly or wrongly) that they are being told by this priesthood "Hear, believe, and obey us on all matters that we deem science-related."

Agreed. We have to reject attempts to construct and defend the "scientific priesthood" that is only accountable to other members of the "scientific priesthood." Some years ago, in arguing to retain Popper's falsifiability and Feynman's view experiment as the ultimate arbiter of science, a colleague and I wrote:

Defining science as “observationally constrained model building” is barely more specific than defining science as “what scientists do.” How far is this from defining sound science as “what scientists say” (with appropriate homage to peer review)? At this point, is science really a powerful, objective epistemology for exploring natural law, or have we merely replaced one set of authorities (the Catholic Church of the Middle Ages) with another (the scientists of the 21st century)?

See: https://arxiv.org/ftp/arxiv/papers/0812/0812.4932.pdf

 

[mheslep]

I think we can all agree that validated predictions of the future emergence of new species would be more impressive

Genetic changes are random and the long term natural process which selects them, leading to enitrely new species, is an interaction with a changing environment and other species which is non linear and chaotic. Predictions are not possible under those conditions. That is, sometimes KT impacts happen.

That said, I agree with the points above about predictive power association with the best science. If Evolution is weak in that regard, no apologies to Darwin.

 

[Dale]

Our understanding will be much better when we can say, "Given your genome, you will (100%) or will not (0%) develop lung cancer if you smoke ZZ packs a day."

If anybody ever says that then they are lying. That is not a reasonable expectation to set, we can't even say 100% that the sun will come up tomorrow.

There is nothing wrong with a probabilistic prediction. It is still predictive, and is more honest for inductive reasoning.

 

[Dale]

I think that there are three issues here, all three of which are contributors to a growing distrust of scientific institutions:

The first is an education problem. A lot of science instruction is teaching a collection Scientific Facts instead of teaching the scientific method and general inductive reasoning.

The second is the communication issue that has been hit on in the scicom discussion above.

The third is the current "replicability crisis". This is the one that I believe this generation of scientists most needs to address. However, I would take it in context. Scientific practice has been substantially refined over the years. Even a century ago it was uncommon to include error bars in any charts, today it is mandatory in many fields as a generation of scientists understood the importance. Similarly, statistical, reporting, and experimental methods addressing replicability are known within the community, and can be broadly adopted as their importance is recognized.

 

[Rive]

I would not use the word authoritarian. I think "scientific priesthood" is a better description. Some in the public fear such a priesthood and imagine (rightly or wrongly) that they are being told by this priesthood "Hear, believe, and obey us on all matters that we deem science-related."

I think it's a bit more difficult than that. If one wants to compare this to religious examples, then most scientists are not 'priests', but 'hermits' or 'saints' who study and develop the mystic knowledge. The priesthood was always a different class, which was expected to interpret and convey the mystic knowledge to the masses - but as can be seen in history this kind of relationship always ended in something else and so 'religion' (this case: science) always became a tool to keep up, promote or create authority.

Just look at the situation around GW and environmental protection...

 

[russ_watters]

If anybody ever says that then they are lying. That is not a reasonable expectation to set, we can't even say 100% that the sun will come up tomorrow.

There is nothing wrong with a probabilistic prediction. It is still predictive, and is more honest for inductive reasoning.

I agree with your point, but would clarify: "the sun will rise tomorrow" is not a probabilistic prediction, it is an exact calculation with a [small] potential experimental error in that the test might get interrupted by, say, Planet X careening through the solar system and splitting Earth in half. So it isn't a great example of a similar probability issue.

"Your odds of getting Type 2 diabetes are 95%" is a probabilistic prediction of exactly the same type as "This Pd103 atom has a 95% chance of decaying in 63 days." It is inherrently impossible for a probability to ever be 100% even excluding experimental error. That's just their nature -- they don't give exact answers. But if the question is framed differently, they can give predictions that are extraordinarily precise: "50% of the atoms in this 1g sample of Pd 103 will decay in 17 days".

So (agreeing with you) it is unfair to expect the prediction "95% of people with this gene sequence will get type 2 diabetes" to enable a high precision result for an individual in that population -- even setting aside confounding factors in the population, such as the individual subjects' ability to affect the outcome of the experiment!

@Dr. Courtney - the silver lining on your bad news that you are very likely to get type 2 diabetes is that your level of uncertainty is actually pretty low compared to others who get similar news: Angelina Jolie removed her breasts on more uncertain odds than that!

TL;DR - Probabilistic predictions can be extremely accurate, but they have to be used properly.

 

[Dr. Courtney]

@Dr. Courtney - the silver lining on your bad news that you are very likely to get type 2 diabetes is that your level of uncertainty is actually pretty low compared to others who get similar news: Angelina Jolie removed her breasts on more uncertain odds than that!

When someone assigns a 0% or 100% probability to an event, I give them the benefit of the doubt and do not assume dishonesty any more than I would if they assigned a 50% probability to an event. My tentative assumption is that they are rounding, hopefully using the rules of significant figures. This leads me to begin considering the uncertainty in the predicted probabilities.

But, being an optimist, I think there is a very good chance that behavioral modifications can put me in the 5% who do not get type 2 diabetes. Rather than take the science as an unavoidable sentence, I've used it to motivate effective action (which should be a big goal of most medical science). The error bars are bigger, but with exercise, dietary modifications, and weight loss, I can reduce my odds to well under 50%, at least within the first decade after a pre-diabetic diagnosis. And the way diabetes works, is an initial diagnosis at 60 rather than at 50 likely results in a much higher quality of life for the remaining years.

So, in some ways, it is about understanding the probabilities. In other ways, it is about reducing the uncertainties. Science is always better if scientists can better understand the probabilities and reduce the error bars. However, in a lot of fields, having an estimate of a probability with large error bars is great progress compared with the earlier state of affairs where there are no quantitative predictions or the quantitative predictions are really only guesses.

 

[anorlunda]

If I correctly interpret the subject of this thread is the public reputation of science. There are two themes running in the thread. Both are relevant to the thread's topic..

1. The difficulty of accurately conveying scientific knowledge to a public audience. Obviously, this applies only to the tiny subset of scientific knowledge that the public is interested in hearing about.
2. The public nonscientific behavior of some scientists acting individually or as a community. Science is but one of many communities vying for public trust and authority. In that sense, science competes with politicians, celebrities, journalists, religions, and others in a non-zero-sum-game of winning public trust.

The difference between the reputation of science and the reputation of scientists is a hair that I don't think is worth splitting.

 

[russ_watters]

When someone assigns a 0% or 100% probability to an event, I give them the benefit of the doubt and do not assume dishonesty any more than I would if they assigned a 50% probability to an event. My tentative assumption is that they are rounding, hopefully using the rules of significant figures. This leads me to begin considering the uncertainty in the predicted probabilities.

Ok...

But, being an optimist, I think there is a very good chance that behavioral modifications can put me in the 5% who do not get type 2 diabetes. Rather than take the science as an unavoidable sentence, I've used it to motivate effective action (which should be a big goal of most medical science). The error bars are bigger, but with exercise, dietary modifications, and weight loss, I can reduce my odds to well under 50%, at least within the first decade after a pre-diabetic diagnosis.

Agreed. But that's just a matter of how the doctor frames the discussion: indeed, that's probably the primary reason for having it!

The doctor is telling you the odds (if you don't attempt to change them) and telling you that you can change the odds. That isn't a flaw in the science, it is a separate/special power you are being given, to change the experiment!

So, in some ways, it is about understanding the probabilities. In other ways, it is about reducing the uncertainties. Science is always better if scientists can better understand the probabilities and reduce the error bars.

I don't want to make this pedantic, but it seems to me that the issue is more about understanding probabilities and therefore properly framing the question than about "error bars". Stating a half life of an isotope isn't a massively wide error bar (50% +/-50%?), it is extraordinarily precise probability. So:

However, in a lot of fields, having an estimate of a probability with large error bars is great progress compared with the earlier state of affairs where there are no quantitative predictions or the quantitative predictions are really only guesses.

I'd be curious as to what other issues/fields you would characterize probabilistic data/predictions as having wide "error bars" in a way similar to your genetic odds of diabetes... If you say "social sciences", then I think we really do disagree...

 

[Dale]

I agree with your point, but would clarify: "the sun will rise tomorrow" is not a probabilistic prediction, it is an exact calculation with a [small] potential experimental error in that the test might get interrupted by, say, Planet X careening through the solar system and splitting Earth in half. So it isn't a great example of a similar probability issue.

"Your odds of getting Type 2 diabetes are 95%" is a probabilistic prediction of exactly the same type as "This Pd103 atom has a 95% chance of decaying in 63 days." It is inherrently impossible for a probability to ever be 100% even excluding experimental error. That's just their nature -- they don't give exact answers

I think I understand what you are saying. You are drawing a distinction between cases where the uncertainty is due to lack of knowledge of the sources (experimental error) but the laws are exact compared to cases where the uncertainty is part of the laws themselves.

I am a "moderate" Bayesian, and the Bayesian approach strongly informs my thinking about the process of inductive reasoning. So, what I was getting at is that there is never a 100% posterior, regardless of the likelihood and the data (assuming an uncertain prior). This applies both to deterministic hypotheses and probabilistic hypotheses.

 

[anorlunda]

I am a "moderate" Bayesian

That would make an awesome t-shirt