You probably don't want to become immortal. At first glance it may sound desirable, but once you start actually thinking about it, you quickly realize that you were probably pretty naive about that. You may however want to live a bit longer than what your current life expectation grants you.
Has using a quote from 4 centuries ago to try to prove a point ever worked out for anyone? It sounds about as effective as "Newton didn't use vaccines, so why should we?". Perhaps there is some merit to the idea, but talking about 17th century science is probably not the most convincing way to make the point. That aside, here is Newton's actual quote from Cohen and Whitman's translation of Principia:
> I have not as yet been able to discover the reason for these properties of gravity from phenomena, and I do not feign hypotheses. For whatever is not deduced from the phenomena must be called a hypothesis; and hypotheses, whether metaphysical or physical, or based on occult qualities, or mechanical, have no place in experimental philosophy. In this philosophy particular propositions are inferred from the phenomena, and afterwards rendered general by induction. [1]
To me, this appears to be a very different sentiment. Newton seems to be saying "I don't try to guess about things I don't understand", not "You don't need to have a clear plan before doing research". Even if it is true that Newton never framed a hypothesis in his life (which strikes me as blatantly false), he didn't live in a world with thousands and thousands of researchers funded by taxpayer money. When commitees have to decide how to spend money, of course it's more logical to fund a project with a well-formed question.
A little further into the article, the author presents many other arguments in support of his point, and discusses why some types of experiment (e.g., typical medical investigations) may need hypotheses, while others need not (the Hubble telescope was not built to investigate a specific hypothesis.) This article deserves more of a response than one that ignores anything not mentioned in the title.
I'm reminded of research in Computer Science, that generally looks like this:
"In this paper we investigate the hypothesis: Is it possible to build something cool? First, we briefly summarize cool things that already exist, then we show how we were able to build something cool, we measure how cool it is (it's cooler than a bunch of competing things!), and finally conclude with some cool ideas that we or you might pursue the future."
It seems to me that Newton did frame hypotheses. The inverse square law is a hypothesis - a proposed explanation of phenomena (the orbits of the planets). It's just that Newton stopped there - he didn't propose a hypothesis for why gravity follows an inverse square law.
In neuroimaging research, I often would rather think of myself as a kind of explorer/cartographer, just weakly mapping the brain in order to fuel future strong hypothesis testing. That is one reason why I think opening and sharing our data is so fundamental to the lasting value of our work.
The article answers its own question with this bit -- "Yet grant-writing experts universally stress that proposals should be built around hypotheses and warn that those not written this way risk rejection as “fishing expeditions.”
"Fishing Expedition" is code for a project that spends a bunch of money and has no tangible result. Typically that is called wasted money. When you have a patron that wants you go out and follow your curiosity, where ever it might lead, that is great. But if you're spending the tax payer's dollar, the folks who gave it to you have to explain to the congressional budget office why they gave it to you and what they hoped to achieve by giving it to you.
The easiest way to express that value proposition is with a hypothesis statement. Building equipment that is known to work (like the Hubble) doesn't require a hypothesis, it requires a credible statement that it will be able to do something that other equipment cannot. Or that you could not build the same capability in a different more cost effective way.
The Space Program has CBO-friendly reason for existing (beat the Russkies to the moon), but 99% of its value was unrelated to that reason.
AT&T invented huge swaths of technology motivated simply by something valuable would come own of free-range research.
PhDs and tenured professors do the same, usually when their research area happens to be inexpensive.
Maybe flimflamming and petty rivalries are not the best justification for basic science?
> Maybe flimflamming and petty rivalries are not the best justification for basic science?
Getting value for taxpayer money is not flimflamming, and it's not petty. There are a lot of good things to spend that money on, and if scientists want a piece of it they should provide a convincing justification.
Basic research in hard sciences is a justification in itself. Maybe drop doing phds in social sciences and humanities and use only for hard sciences is getting value for taxpayer money?
STEM problems are better defined by their nature, which makes them more appealing - they are easier to see and understand, both the problems and solutions. In business, I find people frequently make the mistake of latching onto well-defined, easy-to-measure distractions, rather than the actual problem at hand which is frustratingly hard to measure and which will never have a clear solution.
Social sciences and humanities are hard to measure, but they are often the most important problems: Peace and war; prosperity and opportunity; truth, freedom and justice; politics and policy. I'll observe that the problems of the world today aren't due to a lack of technology - we're doing very well with that - but to the very problems addressed by humanities and social sciences. (And perhaps that's not unrelated to the shift in focus from those fields to technology in recent decades.)
Here's an alternative perspective: STEM only allows precisely-measured problems; if you can't measure it, it's not STEM. Arguably, STEM is taking the low-hanging fruit and leaving the hard stuff, the problems you can't measure but which absolutely must be solved, to the other fields.
EDIT: Major revision; sorry if you read the first version.
1) They often aren't that predictable and highly depending on cultural norms i.e. more or less anything goes for a study or a report and the standards that are in place just doesn't produce as much value to society compared to how much we spend on it IMO.
2) They even more often aren't actually re-producable but are rather pop-scientific studies that are more based on personal interpretation than any reproducible results.
2) They can often be studied on your own without need for guidance that can't be solved in a self study. (We are at a point were I would argue most humanities and social sciences doesn't actually need a university to happen on. Plenty of available knowledge for that today online and in various foras.
3) They don't produce value for society that can be reproduced by society, instead they are used often for political reasons or based on biases we have already that can't be tested.
Don't get me wrong, philosophy, social sciences, psychology etc all have an important role to play in society, but they do not need to be PHD's IMO. For the most cases they aren't rigorous enough which amongst other things is because they are more often than not coming from disciplines where the actual scientific rigor that is required to say anything along the lines of "we know".
Not sure in what way you think social sciences and humanities help solve those problems. In what way can we rely on those fields (rather than our own independent thinking) to "solve" the problems that you claim we have?
Most problems we have are solved (and created) by technology and most problems that technology can't solve neither social sciences nor humanities at large can solve (there are obvious exceptions)
> more or less anything goes for a study or a report
> pop-scientific studies that are more based on personal interpretation than any reproducible results
> They can often be studied on your own without need for guidance that can't be solved in a self study.
What are these claims based on? From my limited personal involvement and my more extensive reading, they are not at all true. They also conflate many very different fields, from comparative literature to behavioral psychology to ancient history to anthropology to archaeology to philosophy ...
A basic requirement, just to get your foot in the door of the lobby, is expert knowledge of prior research and in techniques, something that does require a PhD (which is rewarded for original research - so the parent is almost saying that you don't need a PhD to get a PhD) and years of study. The idea that someone can learn these things (or acquire real expertise in any field) on their own, without mentoring and guidance from existing experts, access to research libraries, communication with peers, access to resources like labs and lab assistants, is hard to fathom and at best extremely inefficient. And that's just the first step.
> In what way can we rely on those fields (rather than our own independent thinking)
These fields are 'independent thinking'. They are individuals who care to spend years reading deeply, consult with experts, master the literature, practice the techniques, etc. If someone on HN posted that they had done those things, you'd give them some credit. If they got a PhD out of it, perhaps the credit should be taken away.
> Most problems we have are solved (and created) by technology
That is true, if we overlook minor challenges like government, human rights, education, laws, war, peace, politics, international relations, religion, truth, knowledge, freedom ...
You last answer kind of illuminates that you are talking about something very different than me. Academia didn't solve any of those areas and I never said that academia doesn't have important areas we are talking about whether it should get funding which my claim is that it doesn't need these days compared to basic research in the hard sciences.
The worlds problems aren't going to be solved with another expert in peace or a political science major, understanding how to get fusion to work on the other hand is.
That doesn't mean we shouldn't have experts in peace or political science and that they can't be instrumental in bringing something to reality but we don't need funding to learn to be a political major or to acquire knowledge.
Getting an education and educating yourself isn't the same.
> The worlds problems aren't going to be solved with another expert in peace or a political science major
You keep saying that, but what is it based on? How can we ignore the long history of the opposite? Who do you think makes peace and solves these problems? I read a lot of international relations literature (for someone not in that field); these problems are technical, require a lot of expertise (especially because it must be applied it under great uncertainty), and the stakes are incredibly high. In fact, one widely accepted view of many wars up through WWII is that they were caused by amateurs in international relations who made amateur mistakes and ended up with wars they didn't want. I encourage you: Educate yourself; read the literature; learn how international relations, for example, and social policy actually happen.
It's easy to write that we should dismiss expertise but before we throw out centuries of knowledge, and lifetimes of acquired expertise for lay amateurs reading Reddit on the weekend, perhaps we should consider it more carefully. The lives, freedom and prosperity of billions of people are at stake.
> we don't need funding to learn to be a political major or to acquire knowledge.
> Getting an education and educating yourself isn't the same.
We need funding to pay professors, to provide resources for their research, and to teach the next generation; and to provide housing and other services and resources for students. The idea that you could learn it on your own without guidance is unfounded and, as I said, extremely inefficient at best. Tell you what: I'll work with someone who has decades of expertise and you do it on your own, and we'll see who gets to the finish line first. My guess is you'll end up way off course and never reach the finish line.
And you keep missing the point. Please read the parent I was responding to.
We are talking about fundamental research today and about academia today.
What many problems of society is academia helping solve today? What peace have academia solved? What really big problems in international relations have academia solved today?
Peace isn't a byproduct of some academic persons phd it's a byproduct of amongst other things technology making live more livable for more and more people.
You don't need to go to the university today to learn to be an expert in international relations technology have ironically enough made it possible to learn about more or less any academic field you want without ever needing a university degree in it.
Respectfully, I disagree. An example I'd like to set forth as particularly relevant is work which falls in fields such as the medical humanities, STS (science, technology, and society), and similar fields which utilize a methodology called actor-network theory. This sort of work falls heavily in the realm of social science or humanities as it draws on philosophy, sociology, but also ultimately and intimately STEM fields and subjects. This sort of work often analyzes the role of technology, and more importantly the uptake of technology, /scientific advancement/, the network of actors which influence how, when, etc this happens. In a general sense these fields tend to yield work which elucidates the context of technology and science, how this context and actors in it influence or have influenced technology.
For example, Bruno Latour wrote a book more or less on the temporally specific factors which lead to the acceptance of the vaccination in scientific communities and in society. Essentially, what I'm saying is something similar or parallel to Thomas Kuhn. Scientific advancement and technological advancement in society and the acceptance of a research achievement as /scientific advancement/ is less about the literal research achievement/advancement and the science, but about social context and temporal specificity. I.e. Kuhn's "paradigm shift".
Annemarie Mol's work, who is both an MD and non-STEM PhD, often highlights the very unscientificness of medical science and technology in practice. Though it's not really her goal, I believe, her examinations illuminate how the guidelines of medical science and the abstract understandings of specific diseases are incongruous with the reality of disease pathology in real patients, even when looked at on a large scale.
I don't see how humanities, social science, etc are somehow less worthy of PhD study. I don't experience STEM as somehow much more difficult to self-study, nor doctoral programs as strictly about knowledge, understanding, nor the validation of general information within a field. Doctoral programs are often about reaching toward mastery of a specific subject to the point of researching it, and there's a lot of networking, career-oriented stuff, and teaching involved. There's a somewhat apprenticeship-like quality to it. Then a committee validates that this research contributes something to the field in a general sense, and also meets bare minimum ethical standards in research, and other similar standards. They ask questions to validate that the candidate has knowledge and can answer questions about whatever highly-specific subject they're working with. It's not an end-all degree; it's one which certifies in whatever specific field that the recipient can master required comps or quals at a minimum standard and then plan, execute, and draw conclusions about research in written form done at a bare minimum standard required for peer-reviewed publishing. In pure math that can mean proving something and then explaining it, but actually most pure math phds I know completed their degrees in less time than say... I think 10-12 years is average or expected fast degree completion for doctoral candidates in Anthropology at my institution. In pure Math it's something like 6-7. Though all that varies by individual program.
I think it's also relevant to note that I think you're a bit jaded about social science research. It's like anything, there's useless, thoughtless, and downright unethical research, and there's also research which the researchers are attempting to engage in best practices and the most accurate understandings of their research. Like, if you look at something like quantitative Sociological research, it's often done via online self-report surveys. No less, sociology phds now are taught to methodologically consider the potential or downright likelihood of the unreliable self-reporter, in addition to the ways that the framing of a ...
I agree on most of what you write but thats not really my point either.
My point isn't that we shouldn't have the arts or humanities or social sciences, these are very important areas. The discussion was whether it needs funding or whether we could use the money for basic research instead.
Again not because it's not important but because it can be done in other ways such as self studies.
The biggest issue for the non-stem fields is that they have no external reality check and that opens up for the most absurd studies to be done and more importantly often affect society without any solid base because they can't be reproduced yet might affect policy.
This is not just a problem for social sciences this is also a problem in real sciences but there are checks and balances in place that allow you to test that not so for humanities and social sciences.
And again I am not saying the fields under humanities, art and social sciences aren't important they are just not science.
> The biggest issue for the non-stem fields is that they have no external reality check
Huh? They predict things about reality all the time; that's mostly what they do (at least the social sciences; humanities can be more analytical). And they base the predictions on observations about reality. I wonder what the parent is referring to.
No social sciences don't predict things all the time that's the point they do so much less than what is normally thought exactly because of the many problems of not being able to replicate their studies.
P.S. Instead of downvoting me just because you don't agree why not just have the argument. I dont' downvote you just because i disagree with you.
If you are doing research, you cannot, by definition, put a firm value on it beforehand. At best, with applied research, you can estimate a loose upper bound in the case of it being successful. Without exploratory science, we would not even have the basis to make hypotheses.
Being charitable, I think the parent wasn't saying it should be. But even in some fantasy ideal-government world, the budget is finite and zero-sum. By giving money to some fishing expedition with no clear expectation of any result, we are taking it from some other use.
> There are a lot of good things to spend that money on, and if scientists want a piece of it they should provide a convincing justification.
But that's not the right way to frame it. We have some amount of money to spend, and we need to figure out how to deploy it. We know that in aggregate basic research has resulted in astronomical payoffs over time. Therefore it's in our interest to put money into basic research. It's not the scientists who should provide convincing justification on why they deserve our money. It's us who should provide convincing justification why more people should become scientists.
I meant that separately. As in, we should encourage more people to become scientists and increase science funding. But for any given amount of funding we still have to pick how to allocate the money, which seems like a very important problem to solve to me.
If you say "all basic research is good and needs no justification", you can't thereby get rid of the threshold for what gets funded. You're just refusing to talk about what the criteria may be and what they should be.
The problem with that is that when you propose a hypothesis and someone pays you to prove it, anything other than a positive result is also considered wasted money. This is the reason why we have all the paid-for junk science out there today.
At least the grants I am directly aware of there was no pressure to 'confirm' the hypothesis, on the individual researcher they may have felt they wouldn't get a paper out of it if it didn't confirm but the grant was written to the experiment proposal and experimental controls.
For the non-STEM (e.g. social) research grants there always seemed to be a bit of a nudge to get the hypothesis confirmed because it was often political (government) or purpose driven (NGO or patron). I sometimes have wondered if the same dynamic had crept into STEM research grants.
I think it would be really useful. And if the giving pledge is real, it seems plausible that a couple of hundred million might be pledged for "pure science"
When taking science classes in school, I never understood why a hypothesis had to take a side. It could not be a question, like "hypothesis: does hot water freeze faster than cold water?", but had to take a position on the issue: "hypothesis: hot water freezes faster than cold water". I never got why this was the case; it sets the experiment up for failure: "oh no, I proved my hypothesis wrong". Who cares? As long as you show something (even not reflecting the null hypothesis is _something_) with a well-designed experiment, why does it matter if your guess is right or not?
I'd much rather prove a hypothesis like "a chalk circle drawn around sugar does nothing to inhibit ants" wrong, than to prove it right! That would be much more interesting!
> When taking science classes in school, I never understood why a hypothesis had to take a side. It could not be a question, like "hypothesis: does hot water freeze faster than cold water?",
Because a hypothesis is a falsifiable answer, not a question.
> I never got why this was the case; it sets the experiment up for failure:
Setting up an explanation for falsification is exactly why. But falsification isn't failure of the experiment, only the hypothesis.
I'm not sure what level of schooling you're talking about, but I think there's two reasons to take a side. First, I think in early school it prepares you to think in a way that makes sense with null/alternative hypotheses and all of those z and t stats hypothesis tests. The second reason is to have you think about what you expect to happen. If you're doing an experiment, you likely have some information to come up with what you think will happen, and what the explanation for that is. If you get a result that goes against what your reasoning was beforehand, then you have a misconception and have to adjust what you think you know. If you don't take a side, then you could potentially say that you believed that would happen all along, even if it doesn't make sense with how you understand things. Taking a side makes you confront your confusion when it doesn't work out as you thought.
That part was probably more about using the scientific method in personal life, I got a bit off track. But to answer you, the idea is that you should have a belief beforehand, and the experiment is how you test beliefs. The experiment should be designed to falsify a specific idea. Like say for example your code doesn't work. You have to have an idea of where it could be broken in order to test that belief. So you know there's a method with complex decisions, and it should call foo, but you believe that it isn't. To test this you throw a print at the top of foo, and see what happens. The belief is necessary to create the experiment - you won't make efficient progress if you put print statements after every line. The experiment is designed to differentiate between "this idea wrong" and "this idea is probably right".
I suppose in the case of programming, there should be a belief in what a function does, because somebody wrote the function in the first place. I'm thinking about my own work, in areas such as physics and electronics. On one fine day, I measured the characteristics of about 100 Zener diodes, to inform a design decision with about 3 or 4 possible outcomes. I don't see where pinning myself down to a particular opinion of the expected outcome before making the measurement would have changed the outcome.
You need a statement because a question is not falsifiable. Asking students to come up with a statement rather than a question is one step closer to coming up with a falsifiable proposition.
Your high school self stumbled onto a serious debate in the philosophy of science of course. What I have said is fairly accepted, but if you're interested in the philosophy & arguments behind it you should read some Karl Popper[0].
Isn’t answering a question functionally the same as falsifying one of the possible hypotheses held in he question? Yes falsifies one half, no the other.
I’m no scientist, so this is really conjecture. I remember being confused as well; and in elementary and even middle school, many students were convinced the hypothesis had to be the right answer, so they wouldn’t fill it out until after the experiment.
But, at least at my schools, we never did any real experiment. We did demonstrations and tried to shoehorn them into the scientific method. We never started with an observation (say, mice live longer when given reduced calorie diets), worked out a hypothetical explanation for that observation, and then designed an experiment to prove or disprove our hypothesis. I’m sure that’s done at some level, but not in any science class I took.
This is just a matter of perspective. Usually the hypothesis you set up is indeed the null hypothesis, and an observation to disprove the null is what you "seek".
Scientific theory is based around the idea that you can never, 100% prove anything absolutely true.* The best we can do is to be "less wrong" by learning how we're wrong. It's a perspective on acquiring knowledge that prioritizes false negatives over false positives.
You don't prove yourself right, you just fail to prove yourself wrong. Trying to prove yourself wrong is a much more reliable way for a human, with all our biases, to end up closer to the truth.
It seems like the idealist model of science - observable data, falsifiable hypothesis, repeatable experiment - is often not how science works. Aeon has a good article on this subject.
Scientific funding is actually one of the things I would want to cut to fund a UBI.
I feel like a lot of "college professor/researcher" work is dealing with the paperwork of justifying why someone should give you enough money that you can pay an undergrad or master's student enough money to cover half of tuition so that you can get them to do some experiments with you.
If people didn't have to worry about rent or putting food on the table, they wouldn't have to spend time on government paperwork and could just focus on advancing science instead.
Neither -- I am saying that scientific funding primarily serves to keep scientists housed and alive (okay, and a little equipment too) and the money would go further without the overhead of means testing (that is, squabbling over which research is "worth funding" and which is not).
I think the poster is suggesting that if people didn't have to work for money, many scientists would continue doing scientific research for free, and they'd have more time to spend on it because they wouldn't have to play the grants game.
This might actually be true for a field like math, where you just need paper/computer to make a major discovery. Probably not for a field like biology that involves a lot of web lab materials -- paying the humans is only a tiny sliver of the cost of making a discovery in the biosciences.
People who do science aren't some weird platonic ideal of scientists who are only motivated by science. They have spouses, kids they want to send to college, friends, social reputations, and a mortgage. I don't know any scientist who is willing to live in a crappy house (which is highly likely with only UBI) and crappy salary so that they can do science 100% of the time.
It's actually not a terrible article. But argh is the framing in the title awful.
Fine, fine. Isaac ?!@# Newton can get away with theorizing ab initio and turn out useful theories. You can't.
More to the point, and relevant to the practice of modern science and not the Work of Giants: experiments designed without an eye to a clear hypothesis are pretty much guaranteed to be exercises in p-hacking.
And then there's the Broad Institute[1]. For some research a hypothesis is too reductionist. Sometimes you need to catalog at exhaustive scale: sequence the entire human genome, catalogue the structure of all cell types[5], and their pathways[6], log all gene expression for every tissue type in as many states of disease as possible[3], examine repurposing drugs by exposing every type of cell to every compound in the US Pharmacopoeia to look for novel effects (via transcriptomics)[2]
Genomic sequencing, microfluidic liquid handling[4,7], and novel statistical approaches allow for scientific knowledge to be generated at an astounding pace. After the data exist, then we can make hypotheses. This is the new model for biomedical big science.
This model of science is often criticized for not being hypothesis-driven, either as "stamp collecting," or as a force for vacuuming up funding that would otherwise support myriad small labs. It does bear fruit for schizophrenia[8], depression [9], as well as diabetes, obesity, and heart disease [10].
Where are the most interesting, most complex, and most challenging data problems these days? Not advertising. Not finance. Not crypto. Biology. (And many from cryptography, math, CS, and physics have switched gears to work on biological problems.) We run on messy stochastic software, and we finally have the tools to read the source code and save edits. It's an exciting time.
> The success of a grant proposal shouldn’t hinge on whether the research is driven by a hypothesis, especially in the physical sciences.
You're looking at it the wrong way. If one call for proposal (meaning availability to fund only one project) receives a hundred proposals, then the acceptance rate is going to be 1% no matter what. Requirements like hypothesis inclusion are just ways to split the weed out work into two phases, e.g., eliminate 50 of the 100 proposals because they don't have hypothesis, and then eliminate 49 out of the remaining 50 after more careful reading. If you don't have the hypothesis requirement, that only means 99 out of 100 are eliminated after full reading. And what do you think the likelihood is going to be that the reviewers would accept your hypothesis-free proposal over dozens others that have one (all other things considered equal)?
The problem is lack of funding (or alternatively, too many researchers and not enough research work to go around, depending on how you look at it; Masters degree is the new Bachelors degree, PhD is the new Masters, etc, etc). What you're focusing on are marginal issues.
I finally 'got' the concept of hypotheses after a couple stupid public policy experiments here in India. The 'Odd-Even' car rationing experiment in Delhi to reduce pollution was praised because it reduced traffic. Then the country-wide demonetization disaster meant to reduce undeclared income was later touted as a way to enable digital transactions. So to generalize, if you're not clear on what you're trying to achieve, you can claim success by retrofitting your results to any stated purpose.
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[ 2.9 ms ] story [ 123 ms ] threadhttps://en.wikipedia.org/wiki/Isaac_Newton's_occult_studies
> I have not as yet been able to discover the reason for these properties of gravity from phenomena, and I do not feign hypotheses. For whatever is not deduced from the phenomena must be called a hypothesis; and hypotheses, whether metaphysical or physical, or based on occult qualities, or mechanical, have no place in experimental philosophy. In this philosophy particular propositions are inferred from the phenomena, and afterwards rendered general by induction. [1]
To me, this appears to be a very different sentiment. Newton seems to be saying "I don't try to guess about things I don't understand", not "You don't need to have a clear plan before doing research". Even if it is true that Newton never framed a hypothesis in his life (which strikes me as blatantly false), he didn't live in a world with thousands and thousands of researchers funded by taxpayer money. When commitees have to decide how to spend money, of course it's more logical to fund a project with a well-formed question.
[1] https://en.wikipedia.org/wiki/Hypotheses_non_fingo
It's not logical to me at all. It might be true, but it excludes every creative invention by every tinker, explorer, and artist.
"Fishing Expedition" is code for a project that spends a bunch of money and has no tangible result. Typically that is called wasted money. When you have a patron that wants you go out and follow your curiosity, where ever it might lead, that is great. But if you're spending the tax payer's dollar, the folks who gave it to you have to explain to the congressional budget office why they gave it to you and what they hoped to achieve by giving it to you.
The easiest way to express that value proposition is with a hypothesis statement. Building equipment that is known to work (like the Hubble) doesn't require a hypothesis, it requires a credible statement that it will be able to do something that other equipment cannot. Or that you could not build the same capability in a different more cost effective way.
AT&T invented huge swaths of technology motivated simply by something valuable would come own of free-range research. PhDs and tenured professors do the same, usually when their research area happens to be inexpensive.
Maybe flimflamming and petty rivalries are not the best justification for basic science?
Getting value for taxpayer money is not flimflamming, and it's not petty. There are a lot of good things to spend that money on, and if scientists want a piece of it they should provide a convincing justification.
Social sciences and humanities are hard to measure, but they are often the most important problems: Peace and war; prosperity and opportunity; truth, freedom and justice; politics and policy. I'll observe that the problems of the world today aren't due to a lack of technology - we're doing very well with that - but to the very problems addressed by humanities and social sciences. (And perhaps that's not unrelated to the shift in focus from those fields to technology in recent decades.)
Here's an alternative perspective: STEM only allows precisely-measured problems; if you can't measure it, it's not STEM. Arguably, STEM is taking the low-hanging fruit and leaving the hard stuff, the problems you can't measure but which absolutely must be solved, to the other fields.
EDIT: Major revision; sorry if you read the first version.
1) They often aren't that predictable and highly depending on cultural norms i.e. more or less anything goes for a study or a report and the standards that are in place just doesn't produce as much value to society compared to how much we spend on it IMO.
2) They even more often aren't actually re-producable but are rather pop-scientific studies that are more based on personal interpretation than any reproducible results. 2) They can often be studied on your own without need for guidance that can't be solved in a self study. (We are at a point were I would argue most humanities and social sciences doesn't actually need a university to happen on. Plenty of available knowledge for that today online and in various foras.
3) They don't produce value for society that can be reproduced by society, instead they are used often for political reasons or based on biases we have already that can't be tested.
Don't get me wrong, philosophy, social sciences, psychology etc all have an important role to play in society, but they do not need to be PHD's IMO. For the most cases they aren't rigorous enough which amongst other things is because they are more often than not coming from disciplines where the actual scientific rigor that is required to say anything along the lines of "we know".
Not sure in what way you think social sciences and humanities help solve those problems. In what way can we rely on those fields (rather than our own independent thinking) to "solve" the problems that you claim we have?
Most problems we have are solved (and created) by technology and most problems that technology can't solve neither social sciences nor humanities at large can solve (there are obvious exceptions)
> pop-scientific studies that are more based on personal interpretation than any reproducible results
> They can often be studied on your own without need for guidance that can't be solved in a self study.
What are these claims based on? From my limited personal involvement and my more extensive reading, they are not at all true. They also conflate many very different fields, from comparative literature to behavioral psychology to ancient history to anthropology to archaeology to philosophy ...
A basic requirement, just to get your foot in the door of the lobby, is expert knowledge of prior research and in techniques, something that does require a PhD (which is rewarded for original research - so the parent is almost saying that you don't need a PhD to get a PhD) and years of study. The idea that someone can learn these things (or acquire real expertise in any field) on their own, without mentoring and guidance from existing experts, access to research libraries, communication with peers, access to resources like labs and lab assistants, is hard to fathom and at best extremely inefficient. And that's just the first step.
> In what way can we rely on those fields (rather than our own independent thinking)
These fields are 'independent thinking'. They are individuals who care to spend years reading deeply, consult with experts, master the literature, practice the techniques, etc. If someone on HN posted that they had done those things, you'd give them some credit. If they got a PhD out of it, perhaps the credit should be taken away.
> Most problems we have are solved (and created) by technology
That is true, if we overlook minor challenges like government, human rights, education, laws, war, peace, politics, international relations, religion, truth, knowledge, freedom ...
https://www.nature.com/news/over-half-of-psychology-studies-...
You last answer kind of illuminates that you are talking about something very different than me. Academia didn't solve any of those areas and I never said that academia doesn't have important areas we are talking about whether it should get funding which my claim is that it doesn't need these days compared to basic research in the hard sciences.
The worlds problems aren't going to be solved with another expert in peace or a political science major, understanding how to get fusion to work on the other hand is.
That doesn't mean we shouldn't have experts in peace or political science and that they can't be instrumental in bringing something to reality but we don't need funding to learn to be a political major or to acquire knowledge.
Getting an education and educating yourself isn't the same.
> The worlds problems aren't going to be solved with another expert in peace or a political science major
You keep saying that, but what is it based on? How can we ignore the long history of the opposite? Who do you think makes peace and solves these problems? I read a lot of international relations literature (for someone not in that field); these problems are technical, require a lot of expertise (especially because it must be applied it under great uncertainty), and the stakes are incredibly high. In fact, one widely accepted view of many wars up through WWII is that they were caused by amateurs in international relations who made amateur mistakes and ended up with wars they didn't want. I encourage you: Educate yourself; read the literature; learn how international relations, for example, and social policy actually happen.
It's easy to write that we should dismiss expertise but before we throw out centuries of knowledge, and lifetimes of acquired expertise for lay amateurs reading Reddit on the weekend, perhaps we should consider it more carefully. The lives, freedom and prosperity of billions of people are at stake.
> we don't need funding to learn to be a political major or to acquire knowledge.
> Getting an education and educating yourself isn't the same.
We need funding to pay professors, to provide resources for their research, and to teach the next generation; and to provide housing and other services and resources for students. The idea that you could learn it on your own without guidance is unfounded and, as I said, extremely inefficient at best. Tell you what: I'll work with someone who has decades of expertise and you do it on your own, and we'll see who gets to the finish line first. My guess is you'll end up way off course and never reach the finish line.
We are talking about fundamental research today and about academia today.
What many problems of society is academia helping solve today? What peace have academia solved? What really big problems in international relations have academia solved today?
Peace isn't a byproduct of some academic persons phd it's a byproduct of amongst other things technology making live more livable for more and more people.
You don't need to go to the university today to learn to be an expert in international relations technology have ironically enough made it possible to learn about more or less any academic field you want without ever needing a university degree in it.
For example, Bruno Latour wrote a book more or less on the temporally specific factors which lead to the acceptance of the vaccination in scientific communities and in society. Essentially, what I'm saying is something similar or parallel to Thomas Kuhn. Scientific advancement and technological advancement in society and the acceptance of a research achievement as /scientific advancement/ is less about the literal research achievement/advancement and the science, but about social context and temporal specificity. I.e. Kuhn's "paradigm shift".
Annemarie Mol's work, who is both an MD and non-STEM PhD, often highlights the very unscientificness of medical science and technology in practice. Though it's not really her goal, I believe, her examinations illuminate how the guidelines of medical science and the abstract understandings of specific diseases are incongruous with the reality of disease pathology in real patients, even when looked at on a large scale.
I don't see how humanities, social science, etc are somehow less worthy of PhD study. I don't experience STEM as somehow much more difficult to self-study, nor doctoral programs as strictly about knowledge, understanding, nor the validation of general information within a field. Doctoral programs are often about reaching toward mastery of a specific subject to the point of researching it, and there's a lot of networking, career-oriented stuff, and teaching involved. There's a somewhat apprenticeship-like quality to it. Then a committee validates that this research contributes something to the field in a general sense, and also meets bare minimum ethical standards in research, and other similar standards. They ask questions to validate that the candidate has knowledge and can answer questions about whatever highly-specific subject they're working with. It's not an end-all degree; it's one which certifies in whatever specific field that the recipient can master required comps or quals at a minimum standard and then plan, execute, and draw conclusions about research in written form done at a bare minimum standard required for peer-reviewed publishing. In pure math that can mean proving something and then explaining it, but actually most pure math phds I know completed their degrees in less time than say... I think 10-12 years is average or expected fast degree completion for doctoral candidates in Anthropology at my institution. In pure Math it's something like 6-7. Though all that varies by individual program.
I think it's also relevant to note that I think you're a bit jaded about social science research. It's like anything, there's useless, thoughtless, and downright unethical research, and there's also research which the researchers are attempting to engage in best practices and the most accurate understandings of their research. Like, if you look at something like quantitative Sociological research, it's often done via online self-report surveys. No less, sociology phds now are taught to methodologically consider the potential or downright likelihood of the unreliable self-reporter, in addition to the ways that the framing of a ...
My point isn't that we shouldn't have the arts or humanities or social sciences, these are very important areas. The discussion was whether it needs funding or whether we could use the money for basic research instead.
Again not because it's not important but because it can be done in other ways such as self studies.
The biggest issue for the non-stem fields is that they have no external reality check and that opens up for the most absurd studies to be done and more importantly often affect society without any solid base because they can't be reproduced yet might affect policy.
https://www.nature.com/news/social-sciences-suffer-from-seve...
This is not just a problem for social sciences this is also a problem in real sciences but there are checks and balances in place that allow you to test that not so for humanities and social sciences.
And again I am not saying the fields under humanities, art and social sciences aren't important they are just not science.
Huh? They predict things about reality all the time; that's mostly what they do (at least the social sciences; humanities can be more analytical). And they base the predictions on observations about reality. I wonder what the parent is referring to.
P.S. Instead of downvoting me just because you don't agree why not just have the argument. I dont' downvote you just because i disagree with you.
But that's not the right way to frame it. We have some amount of money to spend, and we need to figure out how to deploy it. We know that in aggregate basic research has resulted in astronomical payoffs over time. Therefore it's in our interest to put money into basic research. It's not the scientists who should provide convincing justification on why they deserve our money. It's us who should provide convincing justification why more people should become scientists.
> When you have a patron that wants you go out and follow your curiosity, where ever it might lead, that is great.
I'd much rather prove a hypothesis like "a chalk circle drawn around sugar does nothing to inhibit ants" wrong, than to prove it right! That would be much more interesting!
Because a hypothesis is a falsifiable answer, not a question.
> I never got why this was the case; it sets the experiment up for failure:
Setting up an explanation for falsification is exactly why. But falsification isn't failure of the experiment, only the hypothesis.
How does that harm anything? The result is the result. Pretending to have a belief so it can potentially be disproven seems contrived.
Your high school self stumbled onto a serious debate in the philosophy of science of course. What I have said is fairly accepted, but if you're interested in the philosophy & arguments behind it you should read some Karl Popper[0].
[0]: https://plato.stanford.edu/entries/popper/
But, at least at my schools, we never did any real experiment. We did demonstrations and tried to shoehorn them into the scientific method. We never started with an observation (say, mice live longer when given reduced calorie diets), worked out a hypothetical explanation for that observation, and then designed an experiment to prove or disprove our hypothesis. I’m sure that’s done at some level, but not in any science class I took.
You don't prove yourself right, you just fail to prove yourself wrong. Trying to prove yourself wrong is a much more reliable way for a human, with all our biases, to end up closer to the truth.
* mathematicians disagree
https://aeon.co/essays/a-fetish-for-falsification-and-observ...
I feel like a lot of "college professor/researcher" work is dealing with the paperwork of justifying why someone should give you enough money that you can pay an undergrad or master's student enough money to cover half of tuition so that you can get them to do some experiments with you.
If people didn't have to worry about rent or putting food on the table, they wouldn't have to spend time on government paperwork and could just focus on advancing science instead.
This might actually be true for a field like math, where you just need paper/computer to make a major discovery. Probably not for a field like biology that involves a lot of web lab materials -- paying the humans is only a tiny sliver of the cost of making a discovery in the biosciences.
Fine, fine. Isaac ?!@# Newton can get away with theorizing ab initio and turn out useful theories. You can't.
More to the point, and relevant to the practice of modern science and not the Work of Giants: experiments designed without an eye to a clear hypothesis are pretty much guaranteed to be exercises in p-hacking.
Genomic sequencing, microfluidic liquid handling[4,7], and novel statistical approaches allow for scientific knowledge to be generated at an astounding pace. After the data exist, then we can make hypotheses. This is the new model for biomedical big science.
This model of science is often criticized for not being hypothesis-driven, either as "stamp collecting," or as a force for vacuuming up funding that would otherwise support myriad small labs. It does bear fruit for schizophrenia[8], depression [9], as well as diabetes, obesity, and heart disease [10].
Where are the most interesting, most complex, and most challenging data problems these days? Not advertising. Not finance. Not crypto. Biology. (And many from cryptography, math, CS, and physics have switched gears to work on biological problems.) We run on messy stochastic software, and we finally have the tools to read the source code and save edits. It's an exciting time.
1. https://www.broadinstitute.org/about-us
2. https://clue.io/repurposing
3. https://www.gtexportal.org/home/
4. https://www.broadinstitute.org/news/dronc-seq-microfluidic-s...
5. https://www.broadinstitute.org/news/international-human-cell...
6. https://www.broadinstitute.org/klarman-cell-observatory/appr...
7. https://www.broadinstitute.org/files/patents/WO2016149661.pd...
8. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4112379/pdf/ems...
9. https://www.nature.com/articles/s41588-018-0090-3
10. (Via profile of common author in several fields) https://scholar.google.com/citations?hl=en&user=EISUuucAAAAJ...
You're looking at it the wrong way. If one call for proposal (meaning availability to fund only one project) receives a hundred proposals, then the acceptance rate is going to be 1% no matter what. Requirements like hypothesis inclusion are just ways to split the weed out work into two phases, e.g., eliminate 50 of the 100 proposals because they don't have hypothesis, and then eliminate 49 out of the remaining 50 after more careful reading. If you don't have the hypothesis requirement, that only means 99 out of 100 are eliminated after full reading. And what do you think the likelihood is going to be that the reviewers would accept your hypothesis-free proposal over dozens others that have one (all other things considered equal)?
The problem is lack of funding (or alternatively, too many researchers and not enough research work to go around, depending on how you look at it; Masters degree is the new Bachelors degree, PhD is the new Masters, etc, etc). What you're focusing on are marginal issues.