http://www.wired.com/magazine/2011/12/ff_causation/all/1
I saw this article right after I checked my 23andme health updates based on my genome scan. The juxtaposition of the two was striking.
Excerpts:
"There was a vast amount of research behind Kindler’s bold proclamations. The cholesterol pathway is one of the best-understood biological feedback systems in the human body...Furthermore, torcetrapib had already undergone a small clinical trial, which showed that the drug could increase HDL and decrease LDL. Kindler told his investors that, by the second half of 2007, Pfizer would begin applying for approval from the FDA. The success of the drug seemed like a sure thing.
And then, just two days later, on December 2, 2006, Pfizer issued a stunning announcement: The torcetrapib Phase III clinical trial was being terminated. Although the compound was supposed to prevent heart disease, it was actually triggering higher rates of chest pain and heart failure and a 60 percent increase in overall mortality. The drug appeared to be killing people.
That week, Pfizer’s value plummeted by $21 billion."
"This assumption—that understanding a system’s constituent parts means we also understand the causes within the system—is not limited to the pharmaceutical industry or even to biology. It defines modern science. In general, we believe that the so-called problem of causation can be cured by more information, by our ceaseless accumulation of facts. Scientists refer to this process as reductionism. By breaking down a process, we can see how everything fits together"
"The problem with this assumption, however, is that causes are a strange kind of knowledge. This was first pointed out by David Hume, the 18th-century Scottish philosopher. Hume realized that, although people talk about causes as if they are real facts—tangible things that can be discovered—they’re actually not at all factual. Instead, Hume said, every cause is just a slippery story, a catchy conjecture, a “lively conception produced by habit"...a cause is not a fact—it’s a fiction that helps us make sense of facts"
"Though scientists constantly remind themselves that mere correlation is
not causation, if a correlation is clear and consistent, then they typically assume a cause has been found—that there really is some invisible association between the measurements."
It is interesting how we seem to know things - like "correlation does not imply causation" or "past performance is not an indication of future results" - and ignore them so often and readily within the disciplines that own these mantras. It's at the same time silly and understandable - we don't have any better tools to make sense of the world. But at least we should admit that to ourselves.
--
So I checked my 23andme updates today - I get regular messages from the company with new information on my genome scan based on new studies. Most disease risk lines come back with typical odds - I'm depressingly normal.
Today I have a red line for Primary Biliary Cirrhosis. It seems I have a 1.72x higher risk of contracting this form of cirrhosis than the average person, based on established research (meaning multiple studies with 750+ participants). Nearly twice the risk - that's not good, right?
Well, it turns out that it's not good but it's not really that bad either. Apparently the average person has a 0.3% risk while I have a 0.6% risk. It's not going to rock my life in any meaningful way, at least pre-diagnosis.
It does beg the question - is more information always better? I have tended to think yes in the past but the outcomes aren't always better when you know more. But then again, if information is available and curated, then someone needs to play curator. I don't know if I trust anyone else to play curator for me, and playing curator for myself obviates the question. And if we believe that more information tends to converge to the truth, perhaps we should just figure out how to deal with the information we receive rather than avoid it altogether.
I saw this article right after I checked my 23andme health updates based on my genome scan. The juxtaposition of the two was striking.
Excerpts:
"There was a vast amount of research behind Kindler’s bold proclamations. The cholesterol pathway is one of the best-understood biological feedback systems in the human body...Furthermore, torcetrapib had already undergone a small clinical trial, which showed that the drug could increase HDL and decrease LDL. Kindler told his investors that, by the second half of 2007, Pfizer would begin applying for approval from the FDA. The success of the drug seemed like a sure thing.
And then, just two days later, on December 2, 2006, Pfizer issued a stunning announcement: The torcetrapib Phase III clinical trial was being terminated. Although the compound was supposed to prevent heart disease, it was actually triggering higher rates of chest pain and heart failure and a 60 percent increase in overall mortality. The drug appeared to be killing people.
That week, Pfizer’s value plummeted by $21 billion."
"This assumption—that understanding a system’s constituent parts means we also understand the causes within the system—is not limited to the pharmaceutical industry or even to biology. It defines modern science. In general, we believe that the so-called problem of causation can be cured by more information, by our ceaseless accumulation of facts. Scientists refer to this process as reductionism. By breaking down a process, we can see how everything fits together"
"The problem with this assumption, however, is that causes are a strange kind of knowledge. This was first pointed out by David Hume, the 18th-century Scottish philosopher. Hume realized that, although people talk about causes as if they are real facts—tangible things that can be discovered—they’re actually not at all factual. Instead, Hume said, every cause is just a slippery story, a catchy conjecture, a “lively conception produced by habit"...a cause is not a fact—it’s a fiction that helps us make sense of facts"
"Though scientists constantly remind themselves that mere correlation is
not causation, if a correlation is clear and consistent, then they typically assume a cause has been found—that there really is some invisible association between the measurements."
It is interesting how we seem to know things - like "correlation does not imply causation" or "past performance is not an indication of future results" - and ignore them so often and readily within the disciplines that own these mantras. It's at the same time silly and understandable - we don't have any better tools to make sense of the world. But at least we should admit that to ourselves.
--
So I checked my 23andme updates today - I get regular messages from the company with new information on my genome scan based on new studies. Most disease risk lines come back with typical odds - I'm depressingly normal.
Today I have a red line for Primary Biliary Cirrhosis. It seems I have a 1.72x higher risk of contracting this form of cirrhosis than the average person, based on established research (meaning multiple studies with 750+ participants). Nearly twice the risk - that's not good, right?
Well, it turns out that it's not good but it's not really that bad either. Apparently the average person has a 0.3% risk while I have a 0.6% risk. It's not going to rock my life in any meaningful way, at least pre-diagnosis.
It does beg the question - is more information always better? I have tended to think yes in the past but the outcomes aren't always better when you know more. But then again, if information is available and curated, then someone needs to play curator. I don't know if I trust anyone else to play curator for me, and playing curator for myself obviates the question. And if we believe that more information tends to converge to the truth, perhaps we should just figure out how to deal with the information we receive rather than avoid it altogether.
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