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Weiye Loh

Fatalism (Stanford Encyclopedia of Philosophy) - 0 views

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Fatalism Philosophy

shared by Weiye Loh on 21 Oct 10 - Cached
  • This view may be argued for in various ways: by appeal to logical laws and metaphysical necessities; by appeal to the existence and nature of God; by appeal to causal determinism. When argued for in the first way, it is commonly called “Logical fatalism” (or, in some cases, “Metaphysical fatalism”); when argued for in the second way, it is commonly called “Theological fatalism”. When argued for in the third way it is not now commonly referred to as “fatalism” at all, and such arguments will not be discussed here.
  • Weiye Loh on 21 Oct 10
     
    "fatalism" is commonly used to refer to an attitude of resignation in the face of some future event or events which are thought to be inevitable
Weiye Loh

The hidden philosophy of David Foster Wallace - Salon.com Mobile - 0 views

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Philosophy Fatalism

shared by Weiye Loh on 02 Jan 11 - No Cached
  • Taylor's argument, which he himself found distasteful, was that certain logical and seemingly unarguable premises lead to the conclusion that even in matters of human choice, the future is as set in stone as the past. We may think we can affect it, but we can't.
  • human responsibility — that, with advances in neuroscience, is of increasing urgency in jurisprudence, social codes and personal conduct. And it also shows a brilliant young man struggling against fatalism, performing exquisite exercises to convince others, and maybe himself, that what we choose to do is what determines the future, rather than the future more or less determining what we choose to do. This intellectual struggle on Wallace's part seems now a kind of emotional foreshadowing of his suicide. He was a victim of depression from an early age — even during his undergraduate years — and the future never looks more intractable than it does to someone who is depressed.
  • "Fate, Time, and Language" reminded me of how fond philosophers are of extreme situations in creating their thought experiments. In this book alone we find a naval battle, the gallows, a shotgun, poison, an accident that leads to paraplegia, somebody stabbed and killed, and so on. Why not say "I have a pretzel in my hand today. Tomorrow I will have eaten it or not eaten it" instead of "I have a gun in my hand and I will either shoot you through the heart and feast on your flesh or I won't"? Well, OK — the answer is easy: The extreme and violent scenarios catch our attention more forcefully than pretzels do. Also, philosophers, sequestered and meditative as they must be, may long for real action — beyond beekeeping.
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  • Wallace, in his essay, at the very center of trying to show that we can indeed make meaningful choices, places a terrorist in the middle of Amherst's campus with his finger on the trigger mechanism of a nuclear weapon. It is by far the most narratively arresting moment in all of this material, and it says far more about the author's approaching antiestablishment explosions of prose and his extreme emotional makeup than it does about tweedy profs fantasizing about ordering their ships into battle. For, after all, who, besides everyone around him, would the terrorist have killed?
  • Weiye Loh on 02 Jan 11
     
    In 1962, a philosopher (and world-famous beekeeper) named Richard Taylor published a soon-to-be-notorious essay called "Fatalism" in the Philosophical Review.
Weiye Loh

"Cancer by the Numbers" by John Allen Paulos | Project Syndicate - 0 views

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Data Interpretation Statistics Cost Benefits Harm Cancer Screening Health

shared by Weiye Loh on 25 Apr 12 - No Cached
  • The USPSTF recently issued an even sharper warning about the prostate-specific antigen test for prostate cancer, after concluding that the test’s harms outweigh its benefits. Chest X-rays for lung cancer and Pap tests for cervical cancer have received similar, albeit less definitive, criticism.CommentsView/Create comment on this paragraphThe next step in the reevaluation of cancer screening was taken last year, when researchers at the Dartmouth Institute for Health Policy announced that the costs of screening for breast cancer were often minimized, and that the benefits were much exaggerated. Indeed, even a mammogram (almost 40 million are given annually in the US) that detects a cancer does not necessarily save a life.CommentsView/Create comment on this paragraphThe Dartmouth researchers found that, of the estimated 138,000 breast cancers detected annually in the US, the test did not help 120,000-134,000 of the afflicted women. The cancers either were growing so slowly that they did not pose a problem, or they would have been treated successfully if discovered clinically later (or they were so aggressive that little could be done).
Weiye Loh

Censorship of War News Undermines Public Trust - 20 views

I posted a bookmark on something related to this issue. http://www.todayonline.com/World/EDC090907-0000047/The-photo-thats-caused-a-stir AP decided to publish a photo of a fatally wounded young ...

censorship PR

started by Jude John on 31 Aug 09 2 follow-ups, last by Weiye Loh on 06 Sep 09
Weiye Loh

Is Pure Altruism Possible? - NYTimes.com - 0 views

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Altruism Philosophy Evolution

shared by Weiye Loh on 05 Nov 10 - No Cached
  • It’s undeniable that people sometimes act in a way that benefits others, but it may seem that they always get something in return — at the very least, the satisfaction of having their desire to help fulfilled.
  • Contemporary discussions of altruism quickly turn to evolutionary explanations. Reciprocal altruism and kin selection are the two main theories. According to reciprocal altruism, evolution favors organisms that sacrifice their good for others in order to gain a favor in return. Kin selection — the famous “selfish gene” theory popularized by Richard Dawkins — says that an individual who behaves altruistically towards others who share its genes will tend to reproduce those genes. Organisms may be altruistic; genes are selfish. The feeling that loving your children more than yourself is hard-wired lends plausibility to the theory of kin selection.
  • The defect of reciprocal altruism is clear. If a person acts to benefit another in the expectation that the favor will be returned, the natural response is: “That’s not altruism!”  Pure altruism, we think, requires a person to sacrifice for another without consideration of personal gain. Doing good for another person because something’s in it for the do-er is the very opposite of what we have in mind. Kin selection does better by allowing that organisms may genuinely sacrifice their interests for another, but it fails to explain why they sometimes do so for those with whom they share no genes
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  • When we ask whether human beings are altruistic, we want to know about their motives or intentions. Biological altruism explains how unselfish behavior might have evolved but, as Frans de Waal suggested in his column in The Stone on Sunday, it implies nothing about the motives or intentions of the agent: after all, birds and bats and bees can act altruistically. This fact helps to explain why, despite these evolutionary theories, the view that people never intentionally act to benefit others except to obtain some good for themselves still possesses a powerful lure over our thinking.
  • The lure of this view — egoism — has two sources, one psychological, the other logical. Consider first the psychological. One reason people deny that altruism exists is that, looking inward, they doubt the purity of their own motives. We know that even when we appear to act unselfishly, other reasons for our behavior often rear their heads: the prospect of a future favor, the boost to reputation, or simply the good feeling that comes from appearing to act unselfishly. As Kant and Freud observed, people’s true motives may be hidden, even (or perhaps especially) from themselves. Even if we think we’re acting solely to further another person’s good, that might not be the real reason. (There might be no single “real reason” — actions can have multiple motives.)
  • So the psychological lure of egoism as a theory of human action is partly explained by a certain humility or skepticism people have about their own or others’ motives
  • There’s also a less flattering reason: denying the possibility of pure altruism provides a convenient excuse for selfish behavior.
  • The logical lure of egoism is different: the view seems impossible to disprove. No matter how altruistic a person appears to be, it’s possible to conceive of her motive in egoistic terms.
  • The impossibility of disproving egoism may sound like a virtue of the theory, but, as philosophers of science know, it’s really a fatal drawback. A theory that purports to tell us something about the world, as egoism does, should be falsifiable. Not false, of course, but capable of being tested and thus proved false. If every state of affairs is compatible with egoism, then egoism doesn’t tell us anything distinctive about how things are.
  • s ambiguity in the concepts of desire and the satisfaction of desire. If people possess altruistic motives, then they sometimes act to benefit others without the prospect of gain to themselves. In other words, they desire the good of others for its own sake, not simply as a means to their own satisfaction.
  • Still, when our desires are satisfied we normally experience satisfaction; we feel good when we do good. But that doesn’t mean we do good only in order to get that “warm glow” — that our true incentives are self-interested (as economists tend to claim). Indeed, as de Waal argues, if we didn’t desire the good of others for its own sake, then attaining it wouldn’t produce the warm glow.
  • Common sense tells us that some people are more altruistic than others. Egoism’s claim that these differences are illusory — that deep down, everybody acts only to further their own interests — contradicts our observations and deep-seated human practices of moral evaluation.
  • At the same time, we may notice that generous people don’t necessarily suffer more or flourish less than those who are more self-interested.
  • The point is rather that the kind of altruism we ought to encourage, and probably the only kind with staying power, is satisfying to those who practice it. Studies of rescuers show that they don’t believe their behavior is extraordinary; they feel they must do what they do, because it’s just part of who they are. The same holds for more common, less newsworthy acts — working in soup kitchens, taking pets to people in nursing homes, helping strangers find their way, being neighborly. People who act in these ways believe that they ought to help others, but they also want to help, because doing so affirms who they are and want to be and the kind of world they want to exist. As Prof. Neera Badhwar has argued, their identity is tied up with their values, thus tying self-interest and altruism together. The correlation between doing good and feeling good is not inevitable— inevitability lands us again with that empty, unfalsifiable egoism — but it is more than incidental.
  • Altruists should not be confused with people who automatically sacrifice their own interests for others.
  • Weiye Loh on 05 Nov 10
     
    Is Pure Altruism Possible?
Weiye Loh

To Die of Having Lived: an article by Richard Rapport | The American Scholar - 0 views

www.theamericanscholar.org/to-die-of-having-lived

Bioethics Death Technology

shared by Weiye Loh on 17 Mar 10 - Cached
  • Although it may be a form of arrogance to attempt the management of one’s own death, is it better to surrender that management to the arrogance of someone else? We know we can’t avoid dying, but perhaps we can avoid dying badly.
  • Dodging a bad death has become more complicated over the past 30 or 40 years. Before the advent of technological creations that permit vital functions to be sustained so well artificially, medical ethics were less obstructed by abstract definitions of death.
  • generally agreed upon criteria for brain death have simplified some of these confusions, but they have not solved them. The broad middle ground between our usual health and consciousness as the expected norm on the one hand, and clear death of the brain on the other, lacks certainty.
    • Weiye Loh
      Weiye Loh on 17 Mar 10
       
      Isn't it always the case? That dichotomous relationships aren't clearly and equally demarcated but some how we attempt to split them up... through polemical discourses and rhetorics...
  • ...13 more annotations...
  • Doctors and other health-care workers can provide patients and families with probabilities for improvement or recovery, but statistics are hardly what is wanted. Even after profound injury or the diagnosis of an illness that statistically is nearly certain to be fatal, what people hear is the word nearly. How do we not allow the death of someone who might be saved? How do we avoid the equally intolerable salvation of a clinically dead person?
    • Weiye Loh
      Weiye Loh on 17 Mar 10
       
      In what situations do we hear the word "nearly" and in what situations do we hear the word "certain"? When we're dealing with a person's life, we hear "nearly", but when we're dealing with climate science we hear "certain"? 
  • Injecting political agendas into these end-of-life complexities only confuses the problem without providing a solution.
  • The questions are how, when, and on whose terms we depart. It is curious that people might be convinced to avoid confronting death while they are healthy, and that society tolerates ad hominem arguments that obstruct rational debate over an authentic problem of ethics in an uncertain world.
  • Any seriously ill older person who winds up in a modern CCU immediately yields his autonomy. Even if the doctors, nurses, and staff caring for him are intelligent, properly educated, humanistically motivated, and correct in the diagnosis, they are manipulated not only by the tyranny of technology but also by the rules established in their hospital. In addition, regulations of local and state licensing agencies and the federal government dictate the parameters of what the hospital workers do and how they do it, and every action taken is heavily influenced by legal experts committed to their client’s best interest—values frequently different from the patient’s. Once an acutely ill patient finds himself in this situation, everything possible will be done to save him; he is in no position to offer an opinion.
  • Eventually, after hours or days (depending on the illness and who is involved in the care), the wisdom of continuing treatment may come into question. But by then the patient will likely have been intubated and placed on a ventilator, a feeding tube may have been inserted, a catheter placed in the bladder, IVs started in peripheral veins or threaded through a major blood vessel near the heart, and monitors attached to record an EKG, arterial blood pressure, temperature, respirations, oxygen saturation, even pressure inside the skull. Sequential pressure devices will have been wrapped around the legs. All the digital marvels have alarms, so if one isn’t working properly, an annoying beep, like the sound of a backing truck, will fill the patient’s room. Vigilant nurses will add drugs by the dozens to the IV or push them into ports. Families will hover uncertainly. Meanwhile, tens and perhaps hundreds of thousands of dollars will have been transferred from one large corporation—an insurer of some kind—to another large corporation—a health care delivery system of some kind.
    • Weiye Loh
      Weiye Loh on 17 Mar 10
       
      Perhaps then, the value of life is not so much life in itself per se, but rather the transactive amount it generates. 
  • While the expense of the drugs, manpower, and technology required to make a diagnosis and deliver therapy does sop up resources and thereby deny treatment that might be more fruitful for others, including the 46.3 million Americans who, according to the Census Bureau, have no health insurance, that isn’t the real dilemma of the critical care unit.
  • the problem isn’t getting into or out of a CCU; the predicament is in knowing who should be there in the first place.
  • Before we become ill, we tend to assume that everything can be treated and treated successfully. The prelate in Willa Cather’s Death Comes for the Archbishop was wiser. Approaching the end, he said to a younger priest, “I shall not die of a cold, my son. I shall die of having lived.”
  • best way to avoid unwanted admission to a critical care unit at or near the end of life is to write an advance directive (a living will or durable power of attorney for health care) when healthy.
  • , not many people do this and, more regrettably, often the document is not included in the patient’s chart or it goes unnoticed.
  • Since we are sure to die of having lived, we should prepare for death before the last minute. Entire corporations are dedicated to teaching people how to retire well. All of their written materials, Web sites, and seminars begin with the same advice: start planning early. Shouldn’t we at least occasionally think about how we want to leave our lives?
  • Flannery O’Connor, who died young of systemic lupus, wrote, “Sickness before death is a very appropriate thing and I think those who don’t have it miss one of God’s mercies.”
  • Because we understand the metaphor of conflict so well, we are easily sold on the idea that we must resolutely fight against our afflictions (although there was once an article in The Onion titled “Man Loses Cowardly Battle With Cancer”). And there is a place to contest an abnormal metabolism, a mutation, a trauma, or an infection. But there is also a place to surrender. When the organs have failed, when the mind has dissolved, when the body that has faithfully housed us for our lifetime has abandoned us, what’s wrong with giving up?
  • Weiye Loh on 17 Mar 10
     
    Spring 2010 To Die of Having Lived A neurological surgeon reflects on what patients and their families should and should not do when the end draws near
Weiye Loh

Odds Are, It's Wrong - Science News - 0 views

www.sciencenews.org/...Odds_Are%2C_Its_Wrong

Statistics Science

shared by Weiye Loh on 20 Mar 10 - Cached
  • science has long been married to mathematics. Generally it has been for the better. Especially since the days of Galileo and Newton, math has nurtured science. Rigorous mathematical methods have secured science’s fidelity to fact and conferred a timeless reliability to its findings.
  • a mutant form of math has deflected science’s heart from the modes of calculation that had long served so faithfully. Science was seduced by statistics, the math rooted in the same principles that guarantee profits for Las Vegas casinos. Supposedly, the proper use of statistics makes relying on scientific results a safe bet. But in practice, widespread misuse of statistical methods makes science more like a crapshoot.
  • science’s dirtiest secret: The “scientific method” of testing hypotheses by statistical analysis stands on a flimsy foundation. Statistical tests are supposed to guide scientists in judging whether an experimental result reflects some real effect or is merely a random fluke, but the standard methods mix mutually inconsistent philosophies and offer no meaningful basis for making such decisions. Even when performed correctly, statistical tests are widely misunderstood and frequently misinterpreted. As a result, countless conclusions in the scientific literature are erroneous, and tests of medical dangers or treatments are often contradictory and confusing.
  • ...24 more annotations...
  • Experts in the math of probability and statistics are well aware of these problems and have for decades expressed concern about them in major journals. Over the years, hundreds of published papers have warned that science’s love affair with statistics has spawned countless illegitimate findings. In fact, if you believe what you read in the scientific literature, you shouldn’t believe what you read in the scientific literature.
  • “There are more false claims made in the medical literature than anybody appreciates,” he says. “There’s no question about that.”Nobody contends that all of science is wrong, or that it hasn’t compiled an impressive array of truths about the natural world. Still, any single scientific study alone is quite likely to be incorrect, thanks largely to the fact that the standard statistical system for drawing conclusions is, in essence, illogical. “A lot of scientists don’t understand statistics,” says Goodman. “And they don’t understand statistics because the statistics don’t make sense.”
  • In 2007, for instance, researchers combing the medical literature found numerous studies linking a total of 85 genetic variants in 70 different genes to acute coronary syndrome, a cluster of heart problems. When the researchers compared genetic tests of 811 patients that had the syndrome with a group of 650 (matched for sex and age) that didn’t, only one of the suspect gene variants turned up substantially more often in those with the syndrome — a number to be expected by chance.“Our null results provide no support for the hypothesis that any of the 85 genetic variants tested is a susceptibility factor” for the syndrome, the researchers reported in the Journal of the American Medical Association.How could so many studies be wrong? Because their conclusions relied on “statistical significance,” a concept at the heart of the mathematical analysis of modern scientific experiments.
  • Statistical significance is a phrase that every science graduate student learns, but few comprehend. While its origins stretch back at least to the 19th century, the modern notion was pioneered by the mathematician Ronald A. Fisher in the 1920s. His original interest was agriculture. He sought a test of whether variation in crop yields was due to some specific intervention (say, fertilizer) or merely reflected random factors beyond experimental control.Fisher first assumed that fertilizer caused no difference — the “no effect” or “null” hypothesis. He then calculated a number called the P value, the probability that an observed yield in a fertilized field would occur if fertilizer had no real effect. If P is less than .05 — meaning the chance of a fluke is less than 5 percent — the result should be declared “statistically significant,” Fisher arbitrarily declared, and the no effect hypothesis should be rejected, supposedly confirming that fertilizer works.Fisher’s P value eventually became the ultimate arbiter of credibility for science results of all sorts
  • But in fact, there’s no logical basis for using a P value from a single study to draw any conclusion. If the chance of a fluke is less than 5 percent, two possible conclusions remain: There is a real effect, or the result is an improbable fluke. Fisher’s method offers no way to know which is which. On the other hand, if a study finds no statistically significant effect, that doesn’t prove anything, either. Perhaps the effect doesn’t exist, or maybe the statistical test wasn’t powerful enough to detect a small but real effect.
  • Soon after Fisher established his system of statistical significance, it was attacked by other mathematicians, notably Egon Pearson and Jerzy Neyman. Rather than testing a null hypothesis, they argued, it made more sense to test competing hypotheses against one another. That approach also produces a P value, which is used to gauge the likelihood of a “false positive” — concluding an effect is real when it actually isn’t. What  eventually emerged was a hybrid mix of the mutually inconsistent Fisher and Neyman-Pearson approaches, which has rendered interpretations of standard statistics muddled at best and simply erroneous at worst. As a result, most scientists are confused about the meaning of a P value or how to interpret it. “It’s almost never, ever, ever stated correctly, what it means,” says Goodman.
  • experimental data yielding a P value of .05 means that there is only a 5 percent chance of obtaining the observed (or more extreme) result if no real effect exists (that is, if the no-difference hypothesis is correct). But many explanations mangle the subtleties in that definition. A recent popular book on issues involving science, for example, states a commonly held misperception about the meaning of statistical significance at the .05 level: “This means that it is 95 percent certain that the observed difference between groups, or sets of samples, is real and could not have arisen by chance.”
  • That interpretation commits an egregious logical error (technical term: “transposed conditional”): confusing the odds of getting a result (if a hypothesis is true) with the odds favoring the hypothesis if you observe that result. A well-fed dog may seldom bark, but observing the rare bark does not imply that the dog is hungry. A dog may bark 5 percent of the time even if it is well-fed all of the time. (See Box 2)
    • Weiye Loh
      Weiye Loh on 20 Mar 10
       
      Does the problem then, lie not in statistics, but the interpretation of statistics? Is the fallacy of appeal to probability is at work in such interpretation? 
  • Another common error equates statistical significance to “significance” in the ordinary use of the word. Because of the way statistical formulas work, a study with a very large sample can detect “statistical significance” for a small effect that is meaningless in practical terms. A new drug may be statistically better than an old drug, but for every thousand people you treat you might get just one or two additional cures — not clinically significant. Similarly, when studies claim that a chemical causes a “significantly increased risk of cancer,” they often mean that it is just statistically significant, possibly posing only a tiny absolute increase in risk.
  • Statisticians perpetually caution against mistaking statistical significance for practical importance, but scientific papers commit that error often. Ziliak studied journals from various fields — psychology, medicine and economics among others — and reported frequent disregard for the distinction.
  • “I found that eight or nine of every 10 articles published in the leading journals make the fatal substitution” of equating statistical significance to importance, he said in an interview. Ziliak’s data are documented in the 2008 book The Cult of Statistical Significance, coauthored with Deirdre McCloskey of the University of Illinois at Chicago.
  • Multiplicity of mistakesEven when “significance” is properly defined and P values are carefully calculated, statistical inference is plagued by many other problems. Chief among them is the “multiplicity” issue — the testing of many hypotheses simultaneously. When several drugs are tested at once, or a single drug is tested on several groups, chances of getting a statistically significant but false result rise rapidly.
  • Recognizing these problems, some researchers now calculate a “false discovery rate” to warn of flukes disguised as real effects. And genetics researchers have begun using “genome-wide association studies” that attempt to ameliorate the multiplicity issue (SN: 6/21/08, p. 20).
  • Many researchers now also commonly report results with confidence intervals, similar to the margins of error reported in opinion polls. Such intervals, usually given as a range that should include the actual value with 95 percent confidence, do convey a better sense of how precise a finding is. But the 95 percent confidence calculation is based on the same math as the .05 P value and so still shares some of its problems.
  • Statistical problems also afflict the “gold standard” for medical research, the randomized, controlled clinical trials that test drugs for their ability to cure or their power to harm. Such trials assign patients at random to receive either the substance being tested or a placebo, typically a sugar pill; random selection supposedly guarantees that patients’ personal characteristics won’t bias the choice of who gets the actual treatment. But in practice, selection biases may still occur, Vance Berger and Sherri Weinstein noted in 2004 in ControlledClinical Trials. “Some of the benefits ascribed to randomization, for example that it eliminates all selection bias, can better be described as fantasy than reality,” they wrote.
  • Randomization also should ensure that unknown differences among individuals are mixed in roughly the same proportions in the groups being tested. But statistics do not guarantee an equal distribution any more than they prohibit 10 heads in a row when flipping a penny. With thousands of clinical trials in progress, some will not be well randomized. And DNA differs at more than a million spots in the human genetic catalog, so even in a single trial differences may not be evenly mixed. In a sufficiently large trial, unrandomized factors may balance out, if some have positive effects and some are negative. (See Box 3) Still, trial results are reported as averages that may obscure individual differences, masking beneficial or harm­ful effects and possibly leading to approval of drugs that are deadly for some and denial of effective treatment to others.
  • nother concern is the common strategy of combining results from many trials into a single “meta-analysis,” a study of studies. In a single trial with relatively few participants, statistical tests may not detect small but real and possibly important effects. In principle, combining smaller studies to create a larger sample would allow the tests to detect such small effects. But statistical techniques for doing so are valid only if certain criteria are met. For one thing, all the studies conducted on the drug must be included — published and unpublished. And all the studies should have been performed in a similar way, using the same protocols, definitions, types of patients and doses. When combining studies with differences, it is necessary first to show that those differences would not affect the analysis, Goodman notes, but that seldom happens. “That’s not a formal part of most meta-analyses,” he says.
  • Meta-analyses have produced many controversial conclusions. Common claims that antidepressants work no better than placebos, for example, are based on meta-analyses that do not conform to the criteria that would confer validity. Similar problems afflicted a 2007 meta-analysis, published in the New England Journal of Medicine, that attributed increased heart attack risk to the diabetes drug Avandia. Raw data from the combined trials showed that only 55 people in 10,000 had heart attacks when using Avandia, compared with 59 people per 10,000 in comparison groups. But after a series of statistical manipulations, Avandia appeared to confer an increased risk.
  • combining small studies in a meta-analysis is not a good substitute for a single trial sufficiently large to test a given question. “Meta-analyses can reduce the role of chance in the interpretation but may introduce bias and confounding,” Hennekens and DeMets write in the Dec. 2 Journal of the American Medical Association. “Such results should be considered more as hypothesis formulating than as hypothesis testing.”
  • Some studies show dramatic effects that don’t require sophisticated statistics to interpret. If the P value is 0.0001 — a hundredth of a percent chance of a fluke — that is strong evidence, Goodman points out. Besides, most well-accepted science is based not on any single study, but on studies that have been confirmed by repetition. Any one result may be likely to be wrong, but confidence rises quickly if that result is independently replicated.“Replication is vital,” says statistician Juliet Shaffer, a lecturer emeritus at the University of California, Berkeley. And in medicine, she says, the need for replication is widely recognized. “But in the social sciences and behavioral sciences, replication is not common,” she noted in San Diego in February at the annual meeting of the American Association for the Advancement of Science. “This is a sad situation.”
  • Most critics of standard statistics advocate the Bayesian approach to statistical reasoning, a methodology that derives from a theorem credited to Bayes, an 18th century English clergyman. His approach uses similar math, but requires the added twist of a “prior probability” — in essence, an informed guess about the expected probability of something in advance of the study. Often this prior probability is more than a mere guess — it could be based, for instance, on previous studies.
  • it basically just reflects the need to include previous knowledge when drawing conclusions from new observations. To infer the odds that a barking dog is hungry, for instance, it is not enough to know how often the dog barks when well-fed. You also need to know how often it eats — in order to calculate the prior probability of being hungry. Bayesian math combines a prior probability with observed data to produce an estimate of the likelihood of the hunger hypothesis. “A scientific hypothesis cannot be properly assessed solely by reference to the observational data,” but only by viewing the data in light of prior belief in the hypothesis, wrote George Diamond and Sanjay Kaul of UCLA’s School of Medicine in 2004 in the Journal of the American College of Cardiology. “Bayes’ theorem is ... a logically consistent, mathematically valid, and intuitive way to draw inferences about the hypothesis.” (See Box 4)
  • In many real-life contexts, Bayesian methods do produce the best answers to important questions. In medical diagnoses, for instance, the likelihood that a test for a disease is correct depends on the prevalence of the disease in the population, a factor that Bayesian math would take into account.
  • But Bayesian methods introduce a confusion into the actual meaning of the mathematical concept of “probability” in the real world. Standard or “frequentist” statistics treat probabilities as objective realities; Bayesians treat probabilities as “degrees of belief” based in part on a personal assessment or subjective decision about what to include in the calculation. That’s a tough placebo to swallow for scientists wedded to the “objective” ideal of standard statistics. “Subjective prior beliefs are anathema to the frequentist, who relies instead on a series of ad hoc algorithms that maintain the facade of scientific objectivity,” Diamond and Kaul wrote.Conflict between frequentists and Bayesians has been ongoing for two centuries. So science’s marriage to mathematics seems to entail some irreconcilable differences. Whether the future holds a fruitful reconciliation or an ugly separation may depend on forging a shared understanding of probability.“What does probability mean in real life?” the statistician David Salsburg asked in his 2001 book The Lady Tasting Tea. “This problem is still unsolved, and ... if it remains un­solved, the whole of the statistical approach to science may come crashing down from the weight of its own inconsistencies.”
  • Weiye Loh on 20 Mar 10
     
    Odds Are, It's Wrong Science fails to face the shortcomings of statistics
Weiye Loh

Meet the Ethical Placebo: A Story that Heals | NeuroTribes - 0 views

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Medicine Placebo Research

shared by Weiye Loh on 24 Dec 10 - No Cached
  • In modern medicine, placebos are associated with another form of deception — a kind that has long been thought essential for conducting randomized clinical trials of new drugs, the statistical rock upon which the global pharmaceutical industry was built. One group of volunteers in an RCT gets the novel medication; another group (the “control” group) gets pills or capsules that look identical to the allegedly active drug, but contain only an inert substance like milk sugar. These faux drugs are called placebos.
  • Inevitably, the health of some people in both groups improves, while the health of others grows worse. Symptoms of illness fluctuate for all sorts of reasons, including regression to the mean.
  • Since the goal of an RCT, from Big Pharma’s perspective, is to demonstrate the effectiveness of a new drug, the return to robust health of a volunteer in the control group is considered a statistical distraction. If too many people in the trial get better after downing sugar pills, the real drug will look worse by comparison — sometimes fatally so for the purpose of earning approval from the Food and Drug Adminstration.
  • ...12 more annotations...
  • For a complex and somewhat mysterious set of reasons, it is becoming increasingly difficult for experimental drugs to prove their superiority to sugar pills in RCTs
  • in recent years, however, has it become obvious that the abatement of symptoms in control-group volunteers — the so-called placebo effect — is worthy of study outside the context of drug trials, and is in fact profoundly good news to anyone but investors in Pfizer, Roche, and GlaxoSmithKline.
  • The emerging field of placebo research has revealed that the body’s repertoire of resilience contains a powerful self-healing network that can help reduce pain and inflammation, lower the production of stress chemicals like cortisol, and even tame high blood pressure and the tremors of Parkinson’s disease.
  • more and more studies each year — by researchers like Fabrizio Benedetti at the University of Turin, author of a superb new book called The Patient’s Brain, and neuroscientist Tor Wager at the University of Colorado — demonstrate that the placebo effect might be potentially useful in treating a wide range of ills. Then why aren’t doctors supposed to use it?
  • The medical establishment’s ethical problem with placebo treatment boils down to the notion that for fake drugs to be effective, doctors must lie to their patients. It has been widely assumed that if a patient discovers that he or she is taking a placebo, the mind/body password will no longer unlock the network, and the magic pills will cease to do their job.
  • For “Placebos Without Deception,” the researchers tracked the health of 80 volunteers with irritable bowel syndrome for three weeks as half of them took placebos and the other half didn’t.
  • In a previous study published in the British Medical Journal in 2008, Kaptchuk and Kirsch demonstrated that placebo treatment can be highly effective for alleviating the symptoms of IBS. This time, however, instead of the trial being “blinded,” it was “open.” That is, the volunteers in the placebo group knew that they were getting only inert pills — which they were instructed to take religiously, twice a day. They were also informed that, just as Ivan Pavlov trained his dogs to drool at the sound of a bell, the body could be trained to activate its own built-in healing network by the act of swallowing a pill.
  • In other words, in addition to the bogus medication, the volunteers were given a true story — the story of the placebo effect. They also received the care and attention of clinicians, which have been found in many other studies to be crucial for eliciting placebo effects. The combination of the story and a supportive clinical environment were enough to prevail over the knowledge that there was really nothing in the pills. People in the placebo arm of the trial got better — clinically, measurably, significantly better — on standard scales of symptom severity and overall quality of life. In fact, the volunteers in the placebo group experienced improvement comparable to patients taking a drug called alosetron, the standard of care for IBS. Meet the ethical placebo: a powerfully effective faux medication that meets all the standards of informed consent.
  • The study is hardly the last word on the subject, but more like one of the first. Its modest sample size and brief duration leave plenty of room for followup research. (What if “ethical” placebos wear off more quickly than deceptive ones? Does the fact that most of the volunteers in this study were women have any bearing on the outcome? Were any of the volunteers skeptical that the placebo effect is real, and did that affect their response to treatment?) Before some eager editor out there composes a tweet-baiting headline suggesting that placebos are about to drive Big Pharma out of business, he or she should appreciate the fact that the advent of AMA-approved placebo treatments would open numerous cans of fascinatingly tangled worms. For example, since the precise nature of placebo effects is shaped largely by patients’ expectations, would the advertised potency and side effects of theoretical products like Placebex and Therastim be subject to change by Internet rumors, requiring perpetual updating?
  • It’s common to use the word “placebo” as a synonym for “scam.” Economists talk about placebo solutions to our economic catastrophe (tax cuts for the rich, anyone?). Online skeptics mock the billion-dollar herbal-medicine industry by calling it Big Placebo. The fact that our brains and bodies respond vigorously to placebos given in warm and supportive clinical environments, however, turns out to be very real.
  • We’re also discovering that the power of narrative is embedded deeply in our physiology.
  • in the real world of doctoring, many physicians prescribe medications at dosages too low to have an effect on their own, hoping to tap into the body’s own healing resources — though this is mostly acknowledged only in whispers, as a kind of trade secret.
Weiye Loh

Skepticblog » A Creationist Challenge - 0 views

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Creationism Evolution Logic

shared by Weiye Loh on 01 Mar 11 - No Cached
  • The commenter starts with some ad hominems, asserting that my post is biased and emotional. They provide no evidence or argument to support this assertion. And of course they don’t even attempt to counter any of the arguments I laid out. They then follow up with an argument from authority – he can link to a PhD creationist – so there.
  • The article that the commenter links to is by Henry M. Morris, founder for the Institute for Creation Research (ICR) – a young-earth creationist organization. Morris was (he died in 2006 following a stroke) a PhD – in civil engineering. This point is irrelevant to his actual arguments. I bring it up only to put the commenter’s argument from authority into perspective. No disrespect to engineers – but they are not biologists. They have no expertise relevant to the question of evolution – no more than my MD. So let’s stick to the arguments themselves.
  • The article by Morris is an overview of so-called Creation Science, of which Morris was a major architect. The arguments he presents are all old creationist canards, long deconstructed by scientists. In fact I address many of them in my original refutation. Creationists generally are not very original – they recycle old arguments endlessly, regardless of how many times they have been destroyed.
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  • Morris also makes heavy use of the “taking a quote out of context” strategy favored by creationists. His quotes are often from secondary sources and are incomplete.
  • A more scholarly (i.e. intellectually honest) approach would be to cite actual evidence to support a point. If you are going to cite an authority, then make sure the quote is relevant, in context, and complete.
  • And even better, cite a number of sources to show that the opinion is representative. Rather we get single, partial, and often outdated quotes without context.
  • (nature is not, it turns out, cleanly divided into “kinds”, which have no operational definition). He also repeats this canard: Such variation is often called microevolution, and these minor horizontal (or downward) changes occur fairly often, but such changes are not true “vertical” evolution. This is the microevolution/macroevolution false dichotomy. It is only “often called” this by creationists – not by actual evolutionary scientists. There is no theoretical or empirical division between macro and micro evolution. There is just evolution, which can result in the full spectrum of change from minor tweaks to major changes.
  • Morris wonders why there are no “dats” – dog-cat transitional species. He misses the hierarchical nature of evolution. As evolution proceeds, and creatures develop a greater and greater evolutionary history behind them, they increasingly are committed to their body plan. This results in a nestled hierarchy of groups – which is reflected in taxonomy (the naming scheme of living things).
  • once our distant ancestors developed the basic body plan of chordates, they were committed to that body plan. Subsequent evolution resulted in variations on that plan, each of which then developed further variations, etc. But evolution cannot go backward, undo evolutionary changes and then proceed down a different path. Once an evolutionary line has developed into a dog, evolution can produce variations on the dog, but it cannot go backwards and produce a cat.
  • Stephen J. Gould described this distinction as the difference between disparity and diversity. Disparity (the degree of morphological difference) actually decreases over evolutionary time, as lineages go extinct and the surviving lineages are committed to fewer and fewer basic body plans. Meanwhile, diversity (the number of variations on a body plan) within groups tends to increase over time.
  • the kind of evolutionary changes that were happening in the past, when species were relatively undifferentiated (compared to contemporary species) is indeed not happening today. Modern multi-cellular life has 600 million years of evolutionary history constraining their future evolution – which was not true of species at the base of the evolutionary tree. But modern species are indeed still evolving.
  • Here is a list of research documenting observed instances of speciation. The list is from 1995, and there are more recent examples to add to the list. Here are some more. And here is a good list with references of more recent cases.
  • Next Morris tries to convince the reader that there is no evidence for evolution in the past, focusing on the fossil record. He repeats the false claim (again, which I already dealt with) that there are no transitional fossils: Even those who believe in rapid evolution recognize that a considerable number of generations would be required for one distinct “kind” to evolve into another more complex kind. There ought, therefore, to be a considerable number of true transitional structures preserved in the fossils — after all, there are billions of non-transitional structures there! But (with the exception of a few very doubtful creatures such as the controversial feathered dinosaurs and the alleged walking whales), they are not there.
  • I deal with this question at length here, pointing out that there are numerous transitional fossils for the evolution of terrestrial vertebrates, mammals, whales, birds, turtles, and yes – humans from ape ancestors. There are many more examples, these are just some of my favorites.
  • Much of what follows (as you can see it takes far more space to correct the lies and distortions of Morris than it did to create them) is classic denialism – misinterpreting the state of the science, and confusing lack of information about the details of evolution with lack of confidence in the fact of evolution. Here are some examples – he quotes Niles Eldridge: “It is a simple ineluctable truth that virtually all members of a biota remain basically stable, with minor fluctuations, throughout their durations. . . .“ So how do evolutionists arrive at their evolutionary trees from fossils of organisms which didn’t change during their durations? Beware the “….” – that means that meaningful parts of the quote are being omitted. I happen to have the book (The Pattern of Evolution) from which Morris mined that particular quote. Here’s the rest of it: (Remember, by “biota” we mean the commonly preserved plants and animals of a particular geological interval, which occupy regions often as large as Roger Tory Peterson’s “eastern” region of North American birds.) And when these systems change – when the older species disappear, and new ones take their place – the change happens relatively abruptly and in lockstep fashion.”
  • Eldridge was one of the authors (with Gould) of punctuated equilibrium theory. This states that, if you look at the fossil record, what we see are species emerging, persisting with little change for a while, and then disappearing from the fossil record. They theorize that most species most of the time are at equilibrium with their environment, and so do not change much. But these periods of equilibrium are punctuated by disequilibrium – periods of change when species will have to migrate, evolve, or go extinct.
  • This does not mean that speciation does not take place. And if you look at the fossil record we see a pattern of descendant species emerging from ancestor species over time – in a nice evolutionary pattern. Morris gives a complete misrepresentation of Eldridge’s point – once again we see intellectual dishonesty in his methods of an astounding degree.
  • Regarding the atheism = religion comment, it reminds me of a great analogy that I first heard on twitter from Evil Eye. (paraphrase) “those that say atheism is a religion, is like saying ‘not collecting stamps’ is a hobby too.”
  • Morris next tackles the genetic evidence, writing: More often is the argument used that similar DNA structures in two different organisms proves common evolutionary ancestry. Neither argument is valid. There is no reason whatever why the Creator could not or would not use the same type of genetic code based on DNA for all His created life forms. This is evidence for intelligent design and creation, not evolution.
  • Here is an excellent summary of the multiple lines of molecular evidence for evolution. Basically, if we look at the sequence of DNA, the variations in trinucleotide codes for amino acids, and amino acids for proteins, and transposons within DNA we see a pattern that can only be explained by evolution (or a mischievous god who chose, for some reason, to make life look exactly as if it had evolved – a non-falsifiable notion).
  • The genetic code is essentially comprised of four letters (ACGT for DNA), and every triplet of three letters equates to a specific amino acid. There are 64 (4^3) possible three letter combinations, and 20 amino acids. A few combinations are used for housekeeping, like a code to indicate where a gene stops, but the rest code for amino acids. There are more combinations than amino acids, so most amino acids are coded for by multiple combinations. This means that a mutation that results in a one-letter change might alter from one code for a particular amino acid to another code for the same amino acid. This is called a silent mutation because it does not result in any change in the resulting protein.
  • It also means that there are very many possible codes for any individual protein. The question is – which codes out of the gazillions of possible codes do we find for each type of protein in different species. If each “kind” were created separately there would not need to be any relationship. Each kind could have it’s own variation, or they could all be identical if they were essentially copied (plus any mutations accruing since creation, which would be minimal). But if life evolved then we would expect that the exact sequence of DNA code would be similar in related species, but progressively different (through silent mutations) over evolutionary time.
  • This is precisely what we find – in every protein we have examined. This pattern is necessary if evolution were true. It cannot be explained by random chance (the probability is absurdly tiny – essentially zero). And it makes no sense from a creationist perspective. This same pattern (a branching hierarchy) emerges when we look at amino acid substitutions in proteins and other aspects of the genetic code.
  • Morris goes for the second law of thermodynamics again – in the exact way that I already addressed. He responds to scientists correctly pointing out that the Earth is an open system, by writing: This naive response to the entropy law is typical of evolutionary dissimulation. While it is true that local order can increase in an open system if certain conditions are met, the fact is that evolution does not meet those conditions. Simply saying that the earth is open to the energy from the sun says nothing about how that raw solar heat is converted into increased complexity in any system, open or closed. The fact is that the best known and most fundamental equation of thermodynamics says that the influx of heat into an open system will increase the entropy of that system, not decrease it. All known cases of decreased entropy (or increased organization) in open systems involve a guiding program of some sort and one or more energy conversion mechanisms.
  • Energy has to be transformed into a usable form in order to do the work necessary to decrease entropy. That’s right. That work is done by life. Plants take solar energy (again – I’m not sure what “raw solar heat” means) and convert it into food. That food fuels the processes of life, which include development and reproduction. Evolution emerges from those processes- therefore the conditions that Morris speaks of are met.
  • But Morris next makes a very confused argument: Evolution has neither of these. Mutations are not “organizing” mechanisms, but disorganizing (in accord with the second law). They are commonly harmful, sometimes neutral, but never beneficial (at least as far as observed mutations are concerned). Natural selection cannot generate order, but can only “sieve out” the disorganizing mutations presented to it, thereby conserving the existing order, but never generating new order.
  • The notion that evolution (as if it’s a thing) needs to use energy is hopelessly confused. Evolution is a process that emerges from the system of life – and life certainly can use solar energy to decrease its entropy, and by extension the entropy of the biosphere. Morris slips into what is often presented as an information argument.  (Yet again – already dealt with. The pattern here is that we are seeing a shuffling around of the same tired creationists arguments.) It is first not true that most mutations are harmful. Many are silent, and many of those that are not silent are not harmful. They may be neutral, they may be a mixed blessing, and their relative benefit vs harm is likely to be situational. They may be fatal. And they also may be simply beneficial.
  • Morris finishes with a long rambling argument that evolution is religion. Evolution is promoted by its practitioners as more than mere science. Evolution is promulgated as an ideology, a secular religion — a full-fledged alternative to Christianity, with meaning and morality . . . . Evolution is a religion. This was true of evolution in the beginning, and it is true of evolution still today. Morris ties evolution to atheism, which, he argues, makes it a religion. This assumes, of course, that atheism is a religion. That depends on how you define atheism and how you define religion – but it is mostly wrong. Atheism is a lack of belief in one particular supernatural claim – that does not qualify it as a religion.
  • But mutations are not “disorganizing” – that does not even make sense. It seems to be based on a purely creationist notion that species are in some privileged perfect state, and any mutation can only take them farther from that perfection. For those who actually understand biology, life is a kluge of compromises and variation. Mutations are mostly lateral moves from one chaotic state to another. They are not directional. But they do provide raw material, variation, for natural selection. Natural selection cannot generate variation, but it can select among that variation to provide differential survival. This is an old game played by creationists – mutations are not selective, and natural selection is not creative (does not increase variation). These are true but irrelevant, because mutations increase variation and information, and selection is a creative force that results in the differential survival of better adapted variation.
  • Weiye Loh on 01 Mar 11
     
    One of my earlier posts on SkepticBlog was Ten Major Flaws in Evolution: A Refutation, published two years ago. Occasionally a creationist shows up to snipe at the post, like this one:i read this and found it funny. It supposedly gives a scientific refutation, but it is full of more bias than fox news, and a lot of emotion as well.here's a scientific case by an actual scientists, you know, one with a ph. D, and he uses statements by some of your favorite evolutionary scientists to insist evolution doesn't exist.i challenge you to write a refutation on this one.http://www.icr.org/home/resources/resources_tracts_scientificcaseagainstevolution/Challenge accepted.
Weiye Loh

The Duty to Be Happy - Brainiac - 0 views

www.boston.com/...the_duty_to_be.html

Happiness Philosophy Deontology

shared by Weiye Loh on 16 Mar 11 - No Cached
  • Is the importance of happiness overstated? That's the question the French philosopher Pascal Bruckner asks in Perpetual Euphoria: On the Duty to Be Happy, a book-length essay on happiness and its place in our lives.
  • For centuries, Bruckner explains, Western society focused on heavenly things. Happiness, if you were lucky enough to get some in this life, was understood only as a nice bonus, fleeting and illusory. What really mattered was the state of your soul - and it was suffering, not happiness, that would bring your soul closer to God. Bruckner quotes his namesake, Pascal, who wrote: "It is not shameful to die in pain - it is shameful to die in pleasure."
  • Modern Westerners, for good reason, look at things differently. Most people, even the very religious, are focused on getting the most out of our earthly lives: we want to be happy. The problem, Bruckner argues, is that pursuing your own happiness is actually harder and less satisfying than trying to perfect your soul. The old way of thinking made something useful out of suffering; the new way of thinking sees suffering as a senseless waste
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  • And the truth about happiness, as Bruckner sees it, is that it's rarely very effectively pursued. Happiness is really about luck and grace; you can be thankful for happiness, but you can't manufacture it. In fact, thinking of being happy as the sole aim of life makes happiness less meaningful. "Now that it has become the only horizon of our democratic societies," Bruckner writes, happiness, "being connected with work, will, and effort... is necessarily a source of anguish." We work at being happy - and, in working at it, rob ourselves of everything spontaneous and really joyful about happiness.
  • Bruckner isn't saying that we shouldn't be happy; what outrages him is the way modern society can turn happiness into a competition. Happy people, he thinks, tend to lord their happiness over unhappy people; unhappy people tend to feel that, if they aren't happy, then their lives are failures. In fact, many unhappy people lead very valuable lives, and assiduously cultivated happiness is sometimes not particularly valuable
  • Suffering is a natural part of life; it counts as living, too.
Weiye Loh

Science, Strong Inference -- Proper Scientific Method - 0 views

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Science Statistics Media Representation Methodolatry Falsifiability

shared by Weiye Loh on 20 Mar 11 - No Cached
  • Scientists these days tend to keep up a polite fiction that all science is equal. Except for the work of the misguided opponent whose arguments we happen to be refuting at the time, we speak as though every scientist's field and methods of study are as good as every other scientist's and perhaps a little better. This keeps us all cordial when it comes to recommending each other for government grants.
  • Why should there be such rapid advances in some fields and not in others? I think the usual explanations that we tend to think of - such as the tractability of the subject, or the quality or education of the men drawn into it, or the size of research contracts - are important but inadequate. I have begun to believe that the primary factor in scientific advance is an intellectual one. These rapidly moving fields are fields where a particular method of doing scientific research is systematically used and taught, an accumulative method of inductive inference that is so effective that I think it should be given the name of "strong inference." I believe it is important to examine this method, its use and history and rationale, and to see whether other groups and individuals might learn to adopt it profitably in their own scientific and intellectual work. In its separate elements, strong inference is just the simple and old-fashioned method of inductive inference that goes back to Francis Bacon. The steps are familiar to every college student and are practiced, off and on, by every scientist. The difference comes in their systematic application. Strong inference consists of applying the following steps to every problem in science, formally and explicitly and regularly: Devising alternative hypotheses; Devising a crucial experiment (or several of them), with alternative possible outcomes, each of which will, as nearly is possible, exclude one or more of the hypotheses; Carrying out the experiment so as to get a clean result; Recycling the procedure, making subhypotheses or sequential hypotheses to refine the possibilities that remain, and so on.
  • On any new problem, of course, inductive inference is not as simple and certain as deduction, because it involves reaching out into the unknown. Steps 1 and 2 require intellectual inventions, which must be cleverly chosen so that hypothesis, experiment, outcome, and exclusion will be related in a rigorous syllogism; and the question of how to generate such inventions is one which has been extensively discussed elsewhere (2, 3). What the formal schema reminds us to do is to try to make these inventions, to take the next step, to proceed to the next fork, without dawdling or getting tied up in irrelevancies.
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  • It is clear why this makes for rapid and powerful progress. For exploring the unknown, there is no faster method; this is the minimum sequence of steps. Any conclusion that is not an exclusion is insecure and must be rechecked. Any delay in recycling to the next set of hypotheses is only a delay. Strong inference, and the logical tree it generates, are to inductive reasoning what the syllogism is to deductive reasoning in that it offers a regular method for reaching firm inductive conclusions one after the other as rapidly as possible.
  • "But what is so novel about this?" someone will say. This is the method of science and always has been, why give it a special name? The reason is that many of us have almost forgotten it. Science is now an everyday business. Equipment, calculations, lectures become ends in themselves. How many of us write down our alternatives and crucial experiments every day, focusing on the exclusion of a hypothesis? We may write our scientific papers so that it looks as if we had steps 1, 2, and 3 in mind all along. But in between, we do busywork. We become "method- oriented" rather than "problem-oriented." We say we prefer to "feel our way" toward generalizations. We fail to teach our students how to sharpen up their inductive inferences. And we do not realize the added power that the regular and explicit use of alternative hypothesis and sharp exclusion could give us at every step of our research.
  • A distinguished cell biologist rose and said, "No two cells give the same properties. Biology is the science of heterogeneous systems." And he added privately. "You know there are scientists, and there are people in science who are just working with these over-simplified model systems - DNA chains and in vitro systems - who are not doing science at all. We need their auxiliary work: they build apparatus, they make minor studies, but they are not scientists." To which Cy Levinthal replied: "Well, there are two kinds of biologists, those who are looking to see if there is one thing that can be understood and those who keep saying it is very complicated and that nothing can be understood. . . . You must study the simplest system you think has the properties you are interested in."
  • At the 1958 Conference on Biophysics, at Boulder, there was a dramatic confrontation between the two points of view. Leo Szilard said: "The problems of how enzymes are induced, of how proteins are synthesized, of how antibodies are formed, are closer to solution than is generally believed. If you do stupid experiments, and finish one a year, it can take 50 years. But if you stop doing experiments for a little while and think how proteins can possibly be synthesized, there are only about 5 different ways, not 50! And it will take only a few experiments to distinguish these." One of the young men added: "It is essentially the old question: How small and elegant an experiment can you perform?" These comments upset a number of those present. An electron microscopist said. "Gentlemen, this is off the track. This is philosophy of science." Szilard retorted. "I was not quarreling with third-rate scientists: I was quarreling with first-rate scientists."
  • Any criticism or challenge to consider changing our methods strikes of course at all our ego-defenses. But in this case the analytical method offers the possibility of such great increases in effectiveness that it is unfortunate that it cannot be regarded more often as a challenge to learning rather than as challenge to combat. Many of the recent triumphs in molecular biology have in fact been achieved on just such "oversimplified model systems," very much along the analytical lines laid down in the 1958 discussion. They have not fallen to the kind of men who justify themselves by saying "No two cells are alike," regardless of how true that may ultimately be. The triumphs are in fact triumphs of a new way of thinking.
  • the emphasis on strong inference
  • is also partly due to the nature of the fields themselves. Biology, with its vast informational detail and complexity, is a "high-information" field, where years and decades can easily be wasted on the usual type of "low-information" observations or experiments if one does not think carefully in advance about what the most important and conclusive experiments would be. And in high-energy physics, both the "information flux" of particles from the new accelerators and the million-dollar costs of operation have forced a similar analytical approach. It pays to have a top-notch group debate every experiment ahead of time; and the habit spreads throughout the field.
  • Historically, I think, there have been two main contributions to the development of a satisfactory strong-inference method. The first is that of Francis Bacon (13). He wanted a "surer method" of "finding out nature" than either the logic-chopping or all-inclusive theories of the time or the laudable but crude attempts to make inductions "by simple enumeration." He did not merely urge experiments as some suppose, he showed the fruitfulness of interconnecting theory and experiment so that the one checked the other. Of the many inductive procedures he suggested, the most important, I think, was the conditional inductive tree, which proceeded from alternative hypothesis (possible "causes," as he calls them), through crucial experiments ("Instances of the Fingerpost"), to exclusion of some alternatives and adoption of what is left ("establishing axioms"). His Instances of the Fingerpost are explicitly at the forks in the logical tree, the term being borrowed "from the fingerposts which are set up where roads part, to indicate the several directions."
  • ere was a method that could separate off the empty theories! Bacon, said the inductive method could be learned by anybody, just like learning to "draw a straighter line or more perfect circle . . . with the help of a ruler or a pair of compasses." "My way of discovering sciences goes far to level men's wit and leaves but little to individual excellence, because it performs everything by the surest rules and demonstrations." Even occasional mistakes would not be fatal. "Truth will sooner come out from error than from confusion."
  • Nevertheless there is a difficulty with this method. As Bacon emphasizes, it is necessary to make "exclusions." He says, "The induction which is to be available for the discovery and demonstration of sciences and arts, must analyze nature by proper rejections and exclusions, and then, after a sufficient number of negatives come to a conclusion on the affirmative instances." "[To man] it is granted only to proceed at first by negatives, and at last to end in affirmatives after exclusion has been exhausted." Or, as the philosopher Karl Popper says today there is no such thing as proof in science - because some later alternative explanation may be as good or better - so that science advances only by disproofs. There is no point in making hypotheses that are not falsifiable because such hypotheses do not say anything, "it must be possible for all empirical scientific system to be refuted by experience" (14).
  • The difficulty is that disproof is a hard doctrine. If you have a hypothesis and I have another hypothesis, evidently one of them must be eliminated. The scientist seems to have no choice but to be either soft-headed or disputatious. Perhaps this is why so many tend to resist the strong analytical approach and why some great scientists are so disputatious.
  • Fortunately, it seems to me, this difficulty can be removed by the use of a second great intellectual invention, the "method of multiple hypotheses," which is what was needed to round out the Baconian scheme. This is a method that was put forward by T.C. Chamberlin (15), a geologist at Chicago at the turn of the century, who is best known for his contribution to the Chamberlain-Moulton hypothesis of the origin of the solar system.
  • Chamberlin says our trouble is that when we make a single hypothesis, we become attached to it. "The moment one has offered an original explanation for a phenomenon which seems satisfactory, that moment affection for his intellectual child springs into existence, and as the explanation grows into a definite theory his parental affections cluster about his offspring and it grows more and more dear to him. . . . There springs up also unwittingly a pressing of the theory to make it fit the facts and a pressing of the facts to make them fit the theory..." "To avoid this grave danger, the method of multiple working hypotheses is urged. It differs from the simple working hypothesis in that it distributes the effort and divides the affections. . . . Each hypothesis suggests its own criteria, its own method of proof, its own method of developing the truth, and if a group of hypotheses encompass the subject on all sides, the total outcome of means and of methods is full and rich."
  • The conflict and exclusion of alternatives that is necessary to sharp inductive inference has been all too often a conflict between men, each with his single Ruling Theory. But whenever each man begins to have multiple working hypotheses, it becomes purely a conflict between ideas. It becomes much easier then for each of us to aim every day at conclusive disproofs - at strong inference - without either reluctance or combativeness. In fact, when there are multiple hypotheses, which are not anyone's "personal property," and when there are crucial experiments to test them, the daily life in the laboratory takes on an interest and excitement it never had, and the students can hardly wait to get to work to see how the detective story will come out. It seems to me that this is the reason for the development of those distinctive habits of mind and the "complex thought" that Chamberlin described, the reason for the sharpness, the excitement, the zeal, the teamwork - yes, even international teamwork - in molecular biology and high- energy physics today. What else could be so effective?
  • Unfortunately, I think, there are other other areas of science today that are sick by comparison, because they have forgotten the necessity for alternative hypotheses and disproof. Each man has only one branch - or none - on the logical tree, and it twists at random without ever coming to the need for a crucial decision at any point. We can see from the external symptoms that there is something scientifically wrong. The Frozen Method, The Eternal Surveyor, The Never Finished, The Great Man With a Single Hypothcsis, The Little Club of Dependents, The Vendetta, The All-Encompassing Theory Which Can Never Be Falsified.
  • a "theory" of this sort is not a theory at all, because it does not exclude anything. It predicts everything, and therefore does not predict anything. It becomes simply a verbal formula which the graduate student repeats and believes because the professor has said it so often. This is not science, but faith; not theory, but theology. Whether it is hand-waving or number-waving, or equation-waving, a theory is not a theory unless it can be disproved. That is, unless it can be falsified by some possible experimental outcome.
  • the work methods of a number of scientists have been testimony to the power of strong inference. Is success not due in many cases to systematic use of Bacon's "surest rules and demonstrations" as much as to rare and unattainable intellectual power? Faraday's famous diary (16), or Fermi's notebooks (3, 17), show how these men believed in the effectiveness of daily steps in applying formal inductive methods to one problem after another.
  • Surveys, taxonomy, design of equipment, systematic measurements and tables, theoretical computations - all have their proper and honored place, provided they are parts of a chain of precise induction of how nature works. Unfortunately, all too often they become ends in themselves, mere time-serving from the point of view of real scientific advance, a hypertrophied methodology that justifies itself as a lore of respectability.
  • We speak piously of taking measurements and making small studies that will "add another brick to the temple of science." Most such bricks just lie around the brickyard (20). Tables of constraints have their place and value, but the study of one spectrum after another, if not frequently re-evaluated, may become a substitute for thinking, a sad waste of intelligence in a research laboratory, and a mistraining whose crippling effects may last a lifetime.
  • Beware of the man of one method or one instrument, either experimental or theoretical. He tends to become method-oriented rather than problem-oriented. The method-oriented man is shackled; the problem-oriented man is at least reaching freely toward that is most important. Strong inference redirects a man to problem-orientation, but it requires him to be willing repeatedly to put aside his last methods and teach himself new ones.
  • anyone who asks the question about scientific effectiveness will also conclude that much of the mathematizing in physics and chemistry today is irrelevant if not misleading. The great value of mathematical formulation is that when an experiment agrees with a calculation to five decimal places, a great many alternative hypotheses are pretty well excluded (though the Bohr theory and the Schrödinger theory both predict exactly the same Rydberg constant!). But when the fit is only to two decimal places, or one, it may be a trap for the unwary; it may be no better than any rule-of-thumb extrapolation, and some other kind of qualitative exclusion might be more rigorous for testing the assumptions and more important to scientific understanding than the quantitative fit.
  • Today we preach that science is not science unless it is quantitative. We substitute correlations for causal studies, and physical equations for organic reasoning. Measurements and equations are supposed to sharpen thinking, but, in my observation, they more often tend to make the thinking noncausal and fuzzy. They tend to become the object of scientific manipulation instead of auxiliary tests of crucial inferences.
  • Many - perhaps most - of the great issues of science are qualitative, not quantitative, even in physics and chemistry. Equations and measurements are useful when and only when they are related to proof; but proof or disproof comes first and is in fact strongest when it is absolutely convincing without any quantitative measurement.
  • you can catch phenomena in a logical box or in a mathematical box. The logical box is coarse but strong. The mathematical box is fine-grained but flimsy. The mathematical box is a beautiful way of wrapping up a problem, but it will not hold the phenomena unless they have been caught in a logical box to begin with.
  • Of course it is easy - and all too common - for one scientist to call the others unscientific. My point is not that my particular conclusions here are necessarily correct, but that we have long needed some absolute standard of possible scientific effectiveness by which to measure how well we are succeeding in various areas - a standard that many could agree on and one that would be undistorted by the scientific pressures and fashions of the times and the vested interests and busywork that they develop. It is not public evaluation I am interested in so much as a private measure by which to compare one's own scientific performance with what it might be. I believe that strong inference provides this kind of standard of what the maximum possible scientific effectiveness could be - as well as a recipe for reaching it.
  • The strong-inference point of view is so resolutely critical of methods of work and values in science that any attempt to compare specific cases is likely to sound but smug and destructive. Mainly one should try to teach it by example and by exhorting to self-analysis and self-improvement only in general terms
  • one severe but useful private test - a touchstone of strong inference - that removes the necessity for third-person criticism, because it is a test that anyone can learn to carry with him for use as needed. It is our old friend the Baconian "exclusion," but I call it "The Question." Obviously it should be applied as much to one's own thinking as to others'. It consists of asking in your own mind, on hearing any scientific explanation or theory put forward, "But sir, what experiment could disprove your hypothesis?"; or, on hearing a scientific experiment described, "But sir, what hypothesis does your experiment disprove?"
  • It is not true that all science is equal; or that we cannot justly compare the effectiveness of scientists by any method other than a mutual-recommendation system. The man to watch, the man to put your money on, is not the man who wants to make "a survey" or a "more detailed study" but the man with the notebook, the man with the alternative hypotheses and the crucial experiments, the man who knows how to answer your Question of disproof and is already working on it.
  • Weiye Loh on 20 Mar 11
     
    There is so much bad science and bad statistics information in media reports, publications, and shared between conversants that I think it is important to understand about facts and proofs and the associated pitfalls.
Weiye Loh

BioCentre - 0 views

www.bioethics.ac.uk/...reject-radical-enhancement.php

Human Technology Transhumanism Bioethics

shared by Weiye Loh on 14 Apr 11 - No Cached
  • Humanity’s End. The main premise of the book is that proposals that would supposedly promise to make us smarter like never before or add thousands of years to our live seem rather far fetched and the domain of mere fantasy. However, it is these very proposals which form the basis of many of the ideas and thoughts presented by advocates of radical enhancement and which are beginning to move from the sidelines to the centre of main stream discussion. A variety of technologies and therapies are being presented to us as options to expand our capabilities and capacities in order for us to become something other than human.
  • Agar takes issue with this and argues against radical human enhancement. He structures his analysis and discussion by focusing on four key figures and their proposals which help to form the core of the case for radical enhancement debate.  First to be examined by Agar is Ray Kurzweil who argues that Man and Machine will become one as technology allows us to transcend our biology. Second, is Aubrey de Grey who is a passionate advocate and pioneer of anti-ageing therapies which allow us to achieve “longevity escape velocity”. Next is Nick Bostrom, a leading transhumanist who defends the morality and rationality of enhancement and finally James Hughes who is a keen advocate of a harmonious democracy of the enhanced and un-enhanced.
  • He avoids falling into any of the pitfalls of basing his argument solely upon the “playing God” question but instead seeks to posit a well founded argument in favour of the precautionary principle.
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  • Agar directly tackles Hughes’ ideas of a “democratic transhumanism.” Here as post-humans and humans live shoulder to shoulder in wonderful harmony, all persons have access to the technologies they want in order to promote their own flourishing.  Under girding all of this is the belief that no human should feel pressurised to become enhance. Agar finds no comfort with this and instead can foresee a situation where it would be very difficult for humans to ‘choose’ to remain human.  The pressure to radically enhance would be considerable given the fact that the radically enhanced would no doubt be occupying the positions of power in society and would consider the moral obligation to utilise to the full enhancement techniques as being a moral imperative for the good of society.  For those who were able to withstand then a new underclass would no doubt emerge between the enhanced and the un-enhanced. This is precisely the kind of society which Hughes appears to be overly optimistic will not emerge but which is more akin to Lee Silver’s prediction of the future with the distinction made between the "GenRich" and the "naturals”.  This being the case, the author proposes that we have two options: radical enhancement is either enforced across the board or banned outright. It is the latter option which Agar favours but crucially does not elaborate further on so it is unclear as to how he would attempt such a ban given the complexity of the issue. This is disappointing as any general initial reflections which the author felt able to offer would have added to the discussion and added further strength to his line of argument.
  • A Transhuman Manifesto The final focus for Agar is James Hughes, who published his transhumanist manifesto Citizen Cyborg in 2004. Given the direct connection with politics and public policy this for me was a particularly interesting read. The basic premise to Hughes argument is that once humans and post humans recognise each other as citizens then this will mark the point at which they will be able to get along with each other.
  • Agar takes to task the argument Bostrom made with Toby Ord, concerning claims against enhancement. Bostrom and Ord argue that it boils down to a preference for the status quo; current human intellects and life spans are preferred and deemed best because they are what we have now and what we are familiar with (p. 134).  Agar discusses the fact that in his view, Bostrom falls into a focalism – focusing on and magnifying the positives whilst ignoring the negative implications.  Moreover, Agar goes onto develop and reiterate his earlier point that the sort of radical enhancements Bostrom et al enthusiastically support and promote take us beyond what is human so they are no longer human. It therefore cannot be said to be human enhancement given the fact that the traits or capacities that such enhancement afford us would be in many respects superior to ours, but they would not be ours.
  • With his law of accelerating returns and talk of the Singularity Ray Kurzweil proposes that we are speeding towards a time when our outdated systems of neurons and synapses will be traded for far more efficient electronic circuits, allowing us to become artificially super-intelligent and transferring our minds from brains into machines.
  • Having laid out the main ideas and thinking behind Kurzweil’s proposals, Agar makes the perceptive comment that despite the apparent appeal of greater processing power it would nevertheless be no longer human. Introducing chips to the human body and linking into the human nervous system to computers as per Ray Kurzweil’s proposals will prove interesting but it goes beyond merely creating a copy of us in order to that future replication and uploading can take place. Rather it will constitute something more akin to an upgrade. Electrochemical signals that the brain use to achieve thought travel at 100 metres per second. This is impressive but contrast this with the electrical signals in a computer which travel at 300 million metres per second then the distinction is clear. If the predictions are true how will such radically enhanced and empowered beings live not only the unenhanced but also what will there quality of life really be? In response, Agar favours something what he calls “rational biological conservatism” (pg. 57) where we set limits on how intelligent we can become in light of the fact that it will never be rational to us for human beings to completely upload their minds onto computers.
  • Agar then proceeds to argue that in the pursuit of Kurzweil enhanced capacities and capabilities we might accidentally undermine capacities of equal value. This line of argument would find much sympathy from those who consider human organisms in “ecological” terms, representing a profound interconnectedness which when interfered with presents a series of unknown and unexpected consequences. In other words, our specifies-specific form of intelligence may well be linked to species-specific form of desire. Thus, if we start building upon and enhancing our capacity to protect and promote deeply held convictions and beliefs then due to the interconnectedness, it may well affect and remove our desire to perform such activities (page 70). Agar’s subsequent discussion and reference to the work of Jerry Foder, philosopher and cognitive scientist is particularly helpful in terms of the functioning of the mind by modules and the implications of human-friendly AI verses human-unfriendly AI.
  • In terms of the author’s discussion of Aubrey de Grey, what is refreshing to read from the outset is the author’s clear grasp of Aubrey’s ideas and motivation. Some make the mistake of thinking he is the man who wants to live forever, when in actual fact this is not the case.  De Grey wants to reverse the ageing process - Strategies for Engineered Negligible Senescence (SENS) so that people are living longer and healthier lives. Establishing this clear distinction affords the author the opportunity to offer more grounded critiques of de Grey’s than some of his other critics. The author makes plain that de Grey’s immediate goal is to achieve longevity escape velocity (LEV), where anti-ageing therapies add years to life expectancy faster than age consumes them.
  • In weighing up the benefits of living significantly longer lives, Agar posits a compelling argument that I had not fully seen before. In terms of risk, those radically enhanced to live longer may actually be the most risk adverse and fearful people to live. Taking the example of driving a car, a forty year-old senescing human being who gets into their car to drive to work and is involved in a fatal accident “stands to lose, at most, a few healthy, youthful years and a slightly larger number of years with reduced quality” (p.116). In stark contrast should a negligibly senescent being who drives a car and is involved in an accident resulting in their death, stands to lose on average one thousand, healthy, youthful years (p.116).  
  • De Grey’s response to this seems a little flippant; with the end of ageing comes an increased sense of risk-aversion so the desire for risky activity such as driving will no longer be prevalent. Moreover, plus because we are living for longer we will not be in such a hurry to get to places!  Virtual reality comes into its own at this point as a means by which the negligibly senescent being ‘adrenaline junkie’ can be engaged with activities but without the associated risks. But surely the risk is part of the reason why they would want to engage in snow boarding, bungee jumping et al in the first place. De Grey’s strategy seemingly fails to appreciate the extent to which human beings want “direct” contact with the “real” world.
  • Continuing this idea further though, Agar’s subsequent discussion of the role of fire-fighters is an interesting one.  A negligibly senescent fire fighter may stand to loose more when they are trapped in a burning inferno but being negligibly senescent means that they are better fire-fighters by virtue of increase vitality. Having recently heard de Grey speak and had the privilege of discussing his ideas further with him, Agar’s discussion of De Grey were a particular highlight of the book and made for an engaging discussion. Whilst expressing concern and doubt in relation to De Grey’s ideas, Agar is nevertheless quick and gracious enough to acknowledge that if such therapies could be achieved then De Grey is probably the best person to comment on and achieve such therapies given the depth of knowledge and understanding that he has built up in this area.
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