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KARL SABBAGH
Writer and Television Producer; Author, The Riemann Hypothesis

I used to believe that there were experts and non-experts and that, on the whole, the judgment of experts is more accurate, more valid, and more correct than my own judgment. But over the years, thinking — and I should add, experience — has changed my mind. What experts have that I don't are knowledge and experience in some specialized area. What, as a class, they don't have any more than I do is the skills of judgment, rational thinking and wisdom.
Many people enroll for MBA's to become more successful businessmen. An article in Fortune magazine a couple of years ago compared the academic qualifications of people in business and found the qualification that correlated most highly with success was a philosophy degree.

MICHAEL SHERMER
Publisher of Skeptic magazine, monthly columnist for Scientific American; Author, Why Darwin Matters

I have thus changed my mind about this theory of human nature in its extreme form. Human nature is more evolutionarily determined, more cognitively irrational, and more morally complex than I thought.

JAMES O'DONNELL
Classicist; Cultural Historian; Provost, Georgetown University; Author, Augustine: A New Biography

When you do that, you find that the past is more a tissue of choices and chances than we had imagined, that fifty or a hundred years of bad times can happen — and can end and be replaced by the united work of people with heads and hearts that makes society peaceful and prosperous again; or the opportunity can be kicked away.
And we should remember that when we root for the Romans, there are contradictory impulses at work. Rome brought the ancient world a secure environment (Pompey cleaning up the pirates in the Mediterranean was a real service), a standard currency, and a huge free trade zone. Its taxes were heavy, but the wealth it taxed so immense that it could support a huge bureaucracy for a long time without damaging local prosperity. Fine: but it was an empire by conquest, ruled as a military dictatorship, fundamentally dependent on a slave economy, and with no clue whatever about the realities of economic development and management. A prosperous emperor was one who managed by conquest or taxation to bring a flood of wealth into the capital city and squander it as ostentatiously as possible. Rome "fell", if that's the right word for it, partly because it ran out of ideas for new peoples to plunder, and fell into a funk of outrage at the thought that some of the neighboring peoples preferred to move inside the empire's borders, settle down, buy fixer-upper houses, send their kids to the local schools, and generally enjoy the benefits of civilization. (The real barbarians stayed outside.) Much of the worst damage to Rome was done by Roman emperors and armies thrashing about, thinking they were preserving what they were in fact destroying.
So now I have a new mantra for my students: "two hundred years is a long time." When we talk about Shakespeare's time or the Crusades or the Roman Empire or the ancient Israelites, it's all too easy to talk about centuries as objects, a habit we bring even closer to our own time, but real human beings live in the short window of a generation, and with ancient lifespans shorter than our own, that window was brief. We need to understand and respect just how much possibility was there and how much accomplishment was achieved if we are to understand as well the opportunities that were squandered. Learning to do that, learning to sift the finest grains of evidence with care, learning to learn from and debate with others — that's how history gets done.

The excitement begins when you discover that the past is constantly changing.

COLIN TUDGE
Science Writer; Author, The Tree: A Natural History of What Trees Are, How They Live, and Why They Matter

Science proceeds in general by being reductionist. This term is used in different ways in different contexts but here I take it to mean that scientists begin by observing a world that seems infinitely complex and inchoate, and in order to make sense of it they first "reduce" it to a series of bite-sized problems, each of which can then be made the subject of testable hypotheses which, as far as possible, take mathematical form.
Fair enough. The approach is obviously powerful, and it is hard to see how solid progress of a factual kind could be made in any other way. It produces answers of the kind known as "robust". "Robust" does not of course mean "unequivocally true" and still less does it meet the lawyers' criteria — "the whole truth, and nothing but the truth". But robustness is pretty good; certainly good enough to be going on with.
The limitation is obvious, however. Scientists produce robust answers only because they take great care to tailor the questions. As Sir Peter Medawar said, "Science is the art of the soluble" (within the time and with the tools available).
Clearly it is a huge mistake to assume that what is soluble is all there is — but some scientists make this mistake routinely.
Or to put the matter another way: they tend conveniently to forget that they arrived at their "robust" conclusions by ignoring as a matter of strategy all the complexities of a kind that seemed inconvenient. But all too often, scientists then are apt to extrapolate from the conclusions they have drawn from their strategically simplified view of the world, to the whole, real world.
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Behind all this nonsense and horror lies the simplistic belief, of a lot of scientists (though by no means all, to be fair) and politicians and captains of industry, that science understands all (ie is omniscient, or soon will be) and that its high technologies can dig us out of any hole we may dig ourselves into (ie is omnipotent).
Absolutely not.

IRENE PEPPERBERG
Research Associate, Psychology, Harvard University; Author, The Alex Studies

I've learned that the scientific community's emphasis on hypothesis-based research leads too many scientists to devise experiments to prove, rather than test, their hypotheses. Many journal submissions lack any discussion of alternative competing hypotheses: Researchers don't seem to realize that collecting data that are consistent with their original hypothesis doesn't mean that it is unconditionally true. Alternatively, they buy into the fallacy that absence of evidence for something is always evidence of its absence.
I'm all for rigor in scientific research — but let's emphasize the gathering of knowledge rather than the proving of a point.

MARCELO GLEISER
Physicist, Dartmouth College; Author, The Prophet and the Astronomer

To Unify or Not: That is the Question
I grew up infused with the idea of unification. It came first from religion, from my Jewish background. God was all over, was all-powerful, and had a knack for interfering with human affairs, at least in the Old Testament. He then appeared to have decided to be a bit shyer, sending a Son instead, and only revealing Himself through visions and prophecies. Needless to say, when, as a teenager, I started to get interested in science, this vision of an all-pervading God, stories of floods, commandments and plagues, started to become very suspicious. I turned to physics, idolizing Einstein and his science; here was a Jew that saw further, that found a way of translating this old monotheistic tradition into the universal language of science.
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All of my recent anti-unification convictions can crumble during the next few years, after our big new machine, the Large Hadron Collider, is turned on. Many colleagues hope that supersymmetry will finally show its face. Others even bet on possible signs of extra dimensions revealed. However, I have a feeling things won't turn out so nicely. The model of unification, which is so aesthetically appealing, may be simply this, an aesthetically appealing description of Nature, which, unfortunately, doesn't correspond to physical reality. Nature doesn't share our myths. The stakes are high indeed. But being a mild agnostic, I don't believe until there is evidence. And then, there is no need to believe any longer, which is precisely the beauty of science.

ED REGIS
Science Writer, Author, Nano

I used to think you could predict the future. In "Profiles of the Future," Arthur C. Clarke made it seem so easy. And so did all those other experts who confidently predicted the paperless office, the artificial intelligentsia who for decades predicted "human equivalence in ten years," the nanotechnology prophets who kept foreseeing major advances toward molecular manufacturing within fifteen years, and so on.
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But at last, after watching all those forecasts not come true, and in fact become falsified in a crashing, breathtaking manner, I began to question the entire business of making predictions. I mean, if even Nobel prizewinning scientists such as Ernest Rutherford, who gave us essentially the modern concept of the nuclear atom, could say, as he did in 1933, that "We cannot control atomic energy to an extent which would be of any value commercially, and I believe we are not likely ever to be able to do so," and be so spectacularly wrong about it, what hope was there for the rest of us?
And then I finally decided that I knew the source of this incredible mismatch between confident forecast and actual result. The universe is a complex system in which countless causal chains are acting and interacting independently and simultaneously (the ultimate nature of some of them unknown to science even today). There are in fact so many causal sequences and forces at work, all of them running in parallel, and each of them often affecting the course of the others, that it is hopeless to try to specify in advance what's going to happen as they jointly work themselves out. In the face of that complexity, it becomes difficult if not impossible to know with any assurance the future state of the system except in those comparatively few cases in which the system is governed by ironclad laws of nature such as those that allow us to predict the phases of the moon, the tides, or the position of Jupiter in tomorrow night's sky. Otherwise, forget it.
Further, it's an illusion to think that supercomputer modeling is up to the task of truly reliable crystal-ball gazing. It isn't. Witness the epidemiologists who predicted that last year's influenza season would be severe (in fact it was mild); the professional hurricane-forecasters whose models told them that the last two hurricane seasons would be monsters (whereas instead they were wimps). Certain systems in nature, it seems, are computationally irreducible phenomena, meaning that there is no way of knowing the outcome short of waiting for it to happen.
Formerly, when I heard or read a prediction, I believed it. Nowadays I just roll my eyes, shake my head, and turn the page.

NICK BOSTROM
Philosopher, University of Oxford; Author,

Everything
For me, belief is not an all or nothing thing — believe or disbelieve, accept or reject. Instead, I have degrees of belief, a subjective probability distribution over different possible ways the world could be. This means that I am constantly changing my mind about all sorts of things, as I reflect or gain more evidence. While I don't always think explicitly in terms of probabilities, I often do so when I give careful consideration to some matter. And when I reflect on my own cognitive processes, I must acknowledge the graduated nature of my beliefs.
The commonest way in which I change my mind is by concentrating my credence function on a narrower set of possibilities than before. This occurs every time I learn a new piece of information. Since I started my life knowing virtually nothing, I have changed my mind about virtually everything. For example, not knowing a friend's birthday, I assign a 1/365 chance (approximately) of it being the 11th of August. After she tells me that the 11th of August is her birthday, I assign that date a probability of close to 100%. (Never exactly 100%, for there is always a non-zero probability of miscommunication, deception, or other error.)
It can also happen that I change my mind by smearing out my credence function over a wider set of possibilities. I might forget the exact date of my friend's birthday but remember that it is sometime in the summer. The forgetting changes my credence function, from being almost entirely concentrated on 11th of August to being spread out more or less evenly over all the summer months. After this change of mind, I might assign a 1% probability to my friend's birthday being on the 11th of August.
My credence function can become more smeared out not only by forgetting but also by learning — learning that what I previously took to be strong evidence for some hypothesis is in fact weak or misleading evidence. (This type of belief change can often be mathematically modeled as a narrowing rather than a broadening of credence function, but the technicalities of this are not relevant here.)
For example, over the years I have become moderately more uncertain about the benefits of medicine, nutritional supplements, and much conventional health wisdom. This belief change has come about as a result of several factors. One of the factors is that I have read some papers that cast doubt on the reliability of the standard methodological protocols used in medical studies and their reporting. Another factor is my own experience of following up on MEDLINE some of the exciting medical findings reported in the media — almost always, the search of the source literature reveals a much more complicated picture with many studies showing a positive effect, many showing a negative effect, and many showing no effect. A third factor is the arguments of a health economist friend of mine, who holds a dim view of the marginal benefits of medical care.
Typically, my beliefs about big issues change in small steps. Ideally, these steps should approximate a random walk, like the stock market. It should be impossible for me to predict how my beliefs on some topic will change in the future. If I believed that a year hence I will assign a higher probability to some hypothesis than I do today — why, in that case I could raise the probability right away. Given knowledge of what I will believe in the future, I would defer to the beliefs of my future self, provided that I think my future self will be better informed than I am now and at least as rational.
I have no crystal ball to show me what my future self will believe. But I do have access to many other selves, who are better informed than I am on many topics. I can defer to experts. Provided they are unbiased and are giving me their honest opinion, I should perhaps always defer to people who have more information than I do — or to some weighted average of expert opinion if there is no consensus. Of course, the proviso is a very big one: often I have reason to disbelieve that other people are unbiased or that they are giving me their honest opinion. However, it is also possible that I am biased and self-deceiving. An important unresolved question is how much epistemic weight a wannabe Bayesian thinker should give to the opinions of others. I'm looking forward to changing my mind on that issue, hopefully by my credence function becoming concentrated on the correct answer.