It's easy to point fingers at a very sick subset of scientific endeavors - biomedical research. The reasons it is messed up and not very productive are myriad. Fake and non-reproducible results that waste everyone's time are one facet of the problem. The big one I observed was that trying to make a useful tool to solve a real problem with the human body is NOT something that the traditional model can handle very well. The human body is so immensely complex. This means that "easy" solutions are not going to work. You can't repair a jet engine by putting sawdust in the engine oil or some other cheap trick, can you? Why would you think a very small molecule that can interact with any one of tens of thousands of proteins in an unpredictable manner could fix anything either? (or a beam of radiation, or chopping out an entire sub-system and replacing it with a shoddy substitute made by cannibalizing something else, or delivering crude electric shocks to a huge region. I've just named nearly every trick in the arsenal)
Most biomedical research is slanted towards this "cheap trick" solution, however. The reason is because the model encourages it. University research teams usually consist of a principle investigator and a small cadre of graduate students, and a relatively small budget. They are under a deadline to come up with something-anything useful within a few years, and the failures don't receive tenure and are fired. Pharmaceutical research teams also want a quick and cheap solution, generally, for a similar reason. Most of the low hanging fruit - small molecule drugs that are safe and effective - has already been plucked, and in any case there is a limit to the problems in biological systems that can actually be fixed with small molecules. If a complex machine is broken, you usually need to shut it off and replace major components. You are not going to be able to spray some magic oil and fix the fault.
For example, how might you plausible cure cancer? Well, what do cancer cells share in common? Markers on the outside of the cells? Nope, if there were, the immune system would usually detect them. Are the cells always making some foreign protein? Nope, same problem. All tumors share mutated genes, and thus have mRNAs present in the cells that you can detect.
So how might you exploit this? Somehow you have to build a tool that can get into cells near the tumor and detect the ones with these faulty mRNAs(and kills them). Also, this tool needs to not affect healthy cells.
If you break down the components of the tool, you realize it would have to be quite complex, with many sub-elements that have to be developed. You cannot solve this problem with 10 people and a few million dollars. You probably need many interrelated teams, all of whom are tasked with developing separate components of the tool. (with prizes if they succeed, and multiple teams working on each component using a different method to minimize risks)
No one is going to magically publish a working paper in Nature tomorrow where they have succeeded in such an effort overnight. Yet, this is basically what the current system expects. Somehow someone is going to cure cancer tomorrow without there being an actual integrated plan, with the billions of dollars in resources needed, and a sound game plan that minimizes risk and rewards individual successes.
Professors I have pointed this out to say that no central agency can possibly "know" what a successful cancer cure might look like. The current system just funds anyone who wants to try anything, assuming they pass review and have the right credentials. Thus a large variety of things are tried. I don't see it. I don't think there is a valid solution to cancer that can be found with a small team just trying things with a million or 2 of equipment, supplies, and personnel.
Growing replacement organs is a similar endeavor. Small teams have managed to show that it is viable - but they cannot actually solve the serious problems because they lack the resources to go about it in a systematic and likely to succeed way. While Wake Forest has demonstrated years ago that they can make a small heart that beats, there isn't a huge team of thousands systematically attacking each element of the problem that has to be solved to make full scale replacement hearts.
One final note : this ultimately points to gross misapplication of resources. Our society spends billions to kill a few Muslims who MIGHT kill some people violently. It spends billions to incarcerate millions of people for life who individually MIGHT commit some murders. It spends billions on nursing homes and end of life care to statistically extend the lives of millions by a matter of months.
Yet real solutions to problems that kill nearly everyone, for certain, are not worth the money to solve them in a systematic way.
The reason for this is lack of rationality. Human beings fear emotionally extremely rare causes of death much more than extremely likely, "natural" causes. They fear the idea of a few disgruntled Muslims or a criminal who was let out of prison murdering them far more than they fear their heart suddenly failing or their tissues developing a tumor when they are old.
Most biomedical research is slanted towards this "cheap trick" solution, however. The reason is because the model encourages it.
I'm pretty sure this also applies to machine learning research. See this.
From Gene Expression by Razib Khan who some of you may also know from the old gnxp site or perhaps from his BHTV debate with Eliezer.
Link to original post.