<과학 구하기 Saving Science>는 현대 과학이 빠진 곤경에 대해 이야기 하는데, 그 기원을 거슬러 가면 미제스나 하이에크가 언급했던 <과학주의, scientism>, 즉 자연과학의 방법을 이용해 사회과학을 연구한 원죄에, 문제가 있다는 것을 발견하게 된다.

 

Saving Science

 

Science isn’t self-correcting, it’s self-destructing. To save the enterprise, scientists must come out of the lab and into the real world.

 

Daniel Sarewitz

 

 

과학적 성취가 모두 거짓이거나 과학적으로 아무 것도 찾아내지 못했다는 고백.

 

Einstein, We Have a Problem

The science world has been buffeted for nearly a decade by growing revelations that major bodies of scientific knowledge, published in peer-reviewed papers, may simply be wrong. Among recent instances: a cancer cell line used as the basis for over a thousand published breast cancer research studies was revealed to be actually a skin cancer cell line; a biotechnology company was able to replicate only six out of fifty-three “landmark” published studies it sought to validate; a test of more than one hundred potential drugs for treating amyotrophic lateral sclerosis in mice was unable to reproduce any of the positive findings that had been reported from previous studies; a compilation of nearly one hundred fifty clinical trials for therapies to block human inflammatory response showed that even though the therapies had supposedly been validated using mouse model experiments, every one of the trials failed in humans; a statistical assessment of the use of functional magnetic resonance imaging (fMRI) to map human brain function indicated that up to 70 percent of the positive findings reported in approximately 40,000 published fMRI studies could be false; and an article assessing the overall quality of basic and preclinical biomedical research estimated that between 75 and 90 percent of all studies are not reproducible. Meanwhile, a painstaking effort to assess the quality of one hundred peer-reviewed psychology experiments was able to replicate only 39 percent of the original papers’ results; annual mammograms, once the frontline of the war on breast cancer, have been shown to confer little benefit for women in their forties; and, of course, we’ve all been relieved to learn after all these years that saturated fat actually isn’t that bad for us. The number of retracted scientific publications rose tenfold during the first decade of this century, and although that number still remains in the mere hundreds, the growing number of studies such as those mentioned above suggests that poor quality, unreliable, useless, or invalid science may in fact be the norm in some fields, and the number of scientifically suspect or worthless publications may well be counted in the hundreds of thousands annually. While most of the evidence of poor scientific quality is coming from fields related to health, biomedicine, and psychology, the problems are likely to be as bad or worse in many other research areas. For example, a survey of statistical practices in economics research concluded that “the credibility of the economics literature is likely to be modest or even low.”

 

 

과학이 스스로를 파괴하고 있다.

 

C. Glenn Begley and John Ioannidis — researchers who have been courageous and visionary in exposing systemic weakness in biomedical science — concluded in a January 2015 article that “it is impossible to endorse an approach that suggests that we proceed with an ongoing research investment that is producing results the majority of which cannot be substantiated and will not stand the test of time.” Similarly, an economic analysis published in June 2015 estimates that $28 billion per year is wasted on biomedical research that is unreproducible. Science isn’t self-correcting; it’s self-destructing.

 

 

쥐를 대상으로 한 실험은 인간을 위한 신약 개발에는 아무 소용이 없었다.

 

More than one hundred different strains of mice have been developed for the purpose of studying Alzheimer’s, and numerous chemical compounds have been shown to slow the course of Alzheimer’s-like symptoms in mice. Yet despite the proliferation of mouse and other animal models, only one out of 244 compounds that made it to the trial stage in the decade between 2002 and 2012 was approved by the FDA as a treatment for humans — a 99.6 percent failure rate, and even the one drug approved for use in humans during that period doesn’t work very well.

 

 

 

와이버그의 트랜스 과학

 

In his 1972 article “Science and Trans-Science,” Weinberg observed that society would increasingly be calling upon science to understand and address the complex problems of modernity — many of which, of course, could be traced back to science and technology. But he accompanied this recognition with a much deeper and more powerful insight: that such problems “hang on the answers to questions that can be asked of science and yet which cannot be answered by science.” He called research into such questions “trans-science.” If traditional sciences aim for precise and reliable knowledge about natural phenomena, trans-science pursues realities that are contingent or in flux. The objects and phenomena studied by trans-science — populations, economies, engineered systems — depend on many different things, including the particular conditions under which they are studied at a given time and place, and the choices that researchers make about how to define and study them. This means that the objects and phenomena studied by trans-science are never absolute but instead are variable, imprecise, uncertain — and thus always potentially subject to interpretation and debate.

 

 

와이버그의 트랜스 과학이 바로 복잡계를 연구하는 학문이다. 복잡계는 변수가 많아 수학적 엄밀성으로 미래를 예측할 수가 없다. 하지만 과학자들은 자연과학을 탐구하던 방법으로, 즉 환원론적이고 결정론적이며 선형적인 모델로 복잡계를 탐구하려 한다. 당연히 실패할 수 밖에 없다.

 

내가 주장하는 복잡계 혁명이란 바로 과거 환원론적, 결정론적, 선형적 세계관이 무너지고, 복잡계적이고 비선형적, 비결정론적 세계관이 이를 대체하고 있다는 것이다.

 

 

 

 

Daniel Sarewitz is a professor of science and society at Arizona State University’s School for the Future of Innovation and Society, and the co-director of the university’s Consortium for Science, Policy, and Outcomes. He is also the co-editor of Issues in Science and Technology and a regular columnist for the journal Nature.

 

 

원문 전체를 보고 싶은 분:

Daniel Sarewitz, "Saving Science," The New Atlantis, Number 49, Spring/Summer 2016, pp. 4–40.