Traditionally, one proud boast of science has been that it offers a refreshing alternative to the dogmatism so prevalent in other realms of human endeavor. Nothing is sacred in science, its practitioners like to say, since any prevailing theory is shown the door when a usurping theory with greater explanatory power arrives on the scene.
That sounds sporting enough. However, in recent years the spirit of earnest self-correction has all too often suffered the grimy imprimatur of human nature. Study findings have been exaggerated or statistically massaged. Problematic data points go AWOL when they undermine desired outcomes. Would you believe money often plays a leading role? Say it isn’t so! That’s right. White lab coats are not always indicative of antiseptic integrity because, well, absent grant money, they risk getting retired to the closet. Big Money doesn’t just finance Big Science. Often, between the lines it buys predetermined outcomes. Then it’s a hop, skip and a jump to bad O-rings en route to Mars.
As a recent study showed (to paraphrase the Dentyne ads of yore), four out of five scientists surveyed are all-too human. In other words, we’re all prone to cavities — and influences. Take Dutch social psychologist Diederik Stapel. Not satisfied with merely disappearing a handful of nettlesome outlier data points, Stapel conjured ex nihilo entire schools from which whole-cloth data were then presented as fact. As Sarah Estes of The Atlantic described it (“The Myth of Self-Correcting Science” 20 December 2012) Stapel’s mea culpa was more Shakespearian than Copernican. Far from his Bunsen burner breaking mid-experiment, he succumbed to the usual garden variety character flaws: “reckless, ruthless ambition and playing the odds against getting caught.”
If New Good Science can’t be trusted to hack away the detritus of Bad Old Science, perhaps we need to exit fully-appointed laboratories altogether for unfunded but informed speculation. That’s where Editor John Brockman’s This Idea Must Die fits the bill nicely.
This Idea Must Die is a fascinating collection of mini-essays from 175 scientific luminaries describing which scientific idea they deem most eligible for falling by the wayside, cushy grants and prevailing vogues be damned. In that sense this book puts speculative self-correction back in the driver’s seat. Think of a Pruner’s Digest that argues for clearing away old brush to make room for the green shoots of tomorrow.
The collection is something between a Faustian romp and a dilettante’s bedside companion. That’s right. You too can sound like Michio Kaku at your next cocktail party—though the Einstein mane is between you and your hairdresser.
In “Artificial Intelligence”, (sardonic/ironic quotes the author’s) longtime AI theorist Roger Schank attacks the efficacy of the term itself, feeling it a misnomer that served a priori to poison the inquiry. Part of the dilemma stems from emulating an altogether human phenomenon—intelligence—that science is far from comprehending within the hairy ape himself. It’s like attempting to paint a reproduction of a Picasso that’s kept in a dark room. Schank suggests changing the name of the endeavor to “getting computers to do really cool stuff” would better illustrate the nature of the inquiry.
One of the key fascinations of this collection is how some essays subtly contradict one another. For example, physicist Frank Wilczek is more sympathetic to AI than Schank, suggesting (in “Mind Versus Matter”) that one of the three developments responsible for collapsing the mind versus matter demarcation stemmed from the realization that, “many accomplishments once viewed as prerogatives of the mind, from playing chess to planning itineraries to suggesting friends and sharing interests, are things that machines… by pure computation, can do quite well.”
Yet another take on the intelligence conundrum is suggested in Alexander Wissner-Gross’ “Intelligence as a Property”, wherein he suggests intelligence itself is misunderstood as a “static property”, when it’s better thought of as a “dynamic process”. Tool use, for example, may not be a first-order static goal of intelligence so much as it is the, “side effect of a deeper, dynamical process that attempts to maximize future freedom of action.” Now that’s heavy. Where’s my hand-truck?
In the scientific humility department, physicists Geoffrey West and Martin Rees weigh in from slightly different vantages in “The Theory of Everything” and “We’ll Never Hit Barriers to Scientific Understanding”, respectively. Both men puncture the hubris of a science that believes it will one day sit astride all things. West suggests the quest for a Grand Unified Theory has telltale echoes of religion’s monotheistic vision and therefore is “intellectually dangerous”. Like calculus’ asymptotic function, something will always be missing such that the goal of encapsulating everything will forever be left splitting an infinite difference.
Rees takes another tack, suggesting that even if science was capable of converging on everything, it is, in the end, constrained by the limitations of the observer: “Nonetheless—and here I’m sticking my neck out—maybe some aspects of reality are intrinsically beyond us, in that their comprehension would require some posthuman intellect.”
Technology Forecaster Paul Saffo inverts the question altogether by discarding the notion of scientific progress as being some imposing, ever-growing noosphere that threatens to subdue everything. He focuses instead on how scientific advance, paradoxically, accentuates how little of the mystery has acceded to our grasp. In short, science, suggests Saffo, highlights with each new discovery the “profundity of our ignorance”. Awe and wonder are still the appropriate responses.
Interestingly (particularly, one would think, for a PopMatters audience), two essays appear under the name ‘Culture’ that is to say, the latter is marked for white smock death. Twice. The first by Anthropologist/Psychologist Pascal Boyer, starts off oddly enough: “Culture is like trees. Yes, there are trees around. But that doesn’t mean we can have a science of trees.” But don’t we have a science of trees, dendrology or forestry? Though I lack the expertise to identify the grievance or turf war, Boyer seems to be wielding a professional axe against culture as science, suggesting the phenomena therein are more than addressed by sociology, anthropology, evolutionary biology, neurology and others. He may be right.
In the second essay, Anthropologist Laura Betzig is beautifully prosaic in her polite disavowal of culture as a creditable science. But is there the slightest hint of condescension in relegating culture scientists to a chorus line? Let the reader be the judge:
…it has seemed to me that ‘culture’ is a seven-letter word for God. Good people (some of the best) and intelligent people (some of the smartest) have found meaning in religion: They have faith that something supernatural guides what we do. Other good, intelligent people have found meaning in culture: They believe that something superzoological shapes the course of human events. Their voices are often beautiful, and it’s wonderful to be part of a chorus. But in the end, I don’t get it. For me, the laws that apply to animals apply to us. And in that view of life there is grandeur enough.
Bringing this review full-circle—back to the sociology of science, two interesting essays draw some rather sanguine conclusions about how science is presently conducted. In “The Way We Produce and Advance Science”, anthropologist Kathryn Clancy reports on her disturbing recent study which found 60 percent of the respondents had been sexually harassed and 20 percent sexually assaulted while on field study sites. Other forms of exploitation are rife in the field promulgated typically by scientists in positions of power over others. Tenure is often held as a bargaining chip.
The implications are rather obvious. The quality of scientific study has to suffer in an environment where human beings’ welfare is not paramount.
Clancy points to other studies that reveal environments conducive to womens’ contributions produce more papers and better research. In “Allocating Funds via Peer Review”, Gerontologist Aubrey De Grey exposes a peer review process that favors low-risk, low-ambition projects for all the familiar bureaucratic reasons. Too much energy gets devoted to submission protocols and pleasing peer review panels that may lack the necessary expertise to assess the project’s merits. Alas, this risk-aversion bias is endemic across culture and is hardly a peculiarity of science.
This review barely scrapes the surface of what lies in store for the intrepid reader. The strength of the essays lies both in their disciplined brevity as well as the remarkable ability of these very brilliant thought-leaders to convey their areas of inquiry in a manner general readers can understand. For those who tend to stereotype the planet’s empiricists as plodding, observation-driven technicians, the elasticity of thought and imaginative excursions on display here easily dispel that notion. Buckminster Fuller once said, “You never change things by fighting the existing reality. To change something, build a new model that makes the existing model obsolete.”
Perhaps this non-confrontational, end-run approach is the optimal path to establishing new paradigms. But surely recognizing and articulating the sacred cows in our midst, as happens here, is one step towards constructing newer, better models.