"WHAT HAVE YOU CHANGED YOUR MIND ABOUT?"

DAVID G. MYERS
Social psychologist, Hope College; author, Psychology, 8th edition

Reading and reporting on psychological science has changed my mind many times, leading me now to believe that 

• newborns are not the blank slates I once presumed,
• electroconvulsive therapy often alleviates intractable depression,
• economic growth has not improved our morale,
• the automatic unconscious mind dwarfs the controlled conscious mind,
• traumatic experiences rarely get repressed,
• personality is unrelated to birth order,
• most folks have high self-esteem (which sometimes causes problems),
• opposites do not attract,
• sexual orientation is a natural, enduring disposition (most clearly so for men), not a choice.

In this era of science-religion conflict, such revelations underscore our need for what science and religion jointly mandate: humility. Humility, I remind my student audience, is fundamental to the empirical spirit advocated long ago by Moses: "If a prophet speaks in the name of the Lord and what he says does not come true, then it is not the Lord's message." Ergo, if our or anyone's ideas survive being put to the test, so much the better for them. If they crash against a wall of evidence, it is time to rethink.

DAVID DALRYMPLE
Student, MIT's Center for Bits and Atoms; Researcher, Internet 0, Fab Lab Thinner Clients for South Africa, Conformal Computing

Maybe MBAs Should Design Computers After All

Not that long ago, I was under the impression that the basic problem of computer architecture had been solved. After all, computers got faster every year, and gradually whole new application domains emerged. There was constantly more memory available, and software hungrily consumed it. Each new computer had a bigger power supply, and more airflow to extract the increasing heat from the processor.

Now, clock speeds aren't rising quite as quickly, and the progress that is made doesn't seem to help our computers start up or run any faster. The traditions of the computing industry, some going as far back as the first digital computers built by John von Neumann in the 1950s, are starting to grow obsolete. The slower computers seem to get faster, and the more deeply I understand the way things actually work, the more these problems become apparent to me. They really come to light when you think about a computer as a business.

Imagine if your company or organization had one fellow [the CPU] who sat in an isolated office, and refused to talk with anyone except his two most trusted deputies [the Northbridge and Southbridge], through which all the actual work the company does must be funneled. Because this one man — let's call him Bob — is so overloaded doing all the work of the entire company, he has several assistants [memory controllers] who remember everything for him. They do this through a complex system [virtual memory] of file cabinets of various sizes [physical memories], the organization over which they have strictly limited autonomy.

Because it is faster to find things in the smaller cabinets [RAM], where there is less to sift through, Bob asks them to put the most commonly used information there. But since he is constantly switching between different tasks, the assistants must swap in and out the files in the smaller cabinets with those in the larger ones whenever Bob works on something different ["thrashing"]. The largest file cabinet is humongous, and rotates slowly in front of a narrow slit [magnetic storage]. The assistant in charge of it must simply wait for the right folder to appear in front of him before passing it along [disk latency].

Any communication with customers must be handled through a team of receptionists [I/O controllers] who don't take the initiative to relay requests to one of Bob's deputies. When Bob needs customer input to continue on a difficult problem, he drops what he is doing to chase after his deputy to chase after a receptionist to chase down the customer, thus preventing work for other customers to be done in that time.

This model is clearly horrendous for numerous reasons. If any staff member goes out to lunch, the whole operation is likely to grind to a halt. Tasks that ought to be quite simple turn out to take a lot of time, since Bob must re-acquaint himself with the issues in question. If a spy gains Bob's trust, all is lost. The only way to make the model any better without giving up and starting over is to hire people who just do their work faster and spend more hours in the office. And yet, this is the way almost every computer in the world operates today.

It is much more sane to hire a large pool of individuals, and, depending on slow-changing customer needs, organize them into business units and assign them to customer accounts. Each person keeps track of his own small workload, and everyone can work on a separate task simultaneously. If the company suddenly acquires new customers, it can recruit more staff instead of forcing Bob to work overtime. If a certain customer demands more attention than was foreseen, more people can be devoted to the effort. And perhaps most importantly, collaboration with other businesses becomes far more meaningful than the highly coded, formal game of telephone that Bob must play with Frank, who works in a similar position at another corporation [a server]. Essentially, this is a business model problem as much as a computer science one.

These complaints only scratch the surface of the design flaws of today's computers. On an extremely low level, with voltages, charge, and transistors, energy is handled recklessly, causing tremendous heat, which would melt the parts in a matter of seconds were it not for the noisy cooling systems we find in most computers. And on a high level, software engineers have constructed a city of competing abstractions based on the fundamentally flawed "CPU" idea.

So I have changed my mind. I used to believe that computers were on the right track, but now I think the right thing to do is to move forward from our 1950s models to a ground-up, fundamentally distributed computing architecture. I started to use computers at 17 months of age and started programming them at 5, so I took the model for granted. But the present stagnation of perceptual computer performance, and the counter-intuitiveness of programming languages, led me to question what I was born into and wonder if there's a better way. Now I'm eager to help make it happen. When discontent changes your mind, that's innovation.

MAX TEGMARK
Physicist, MIT; Researcher, Precision Cosmology

Do we need to understand consciousness to understand physics?  I used to answer "yes", thinking that we could never figure out the elusive "theory of everything" for our external physical reality without first understanding the distorting mental lens through which we perceive it.

After all, physical reality has turned out to be very different from how it seems, and I feel that most of our notions about it have turned out to be illusions. The world looks like it has three primary colors, but that number three tells us nothing about the world out there, merely something about our senses: that our retina has three kinds of cone cells. The world looks like it has impenetrably solid and stationary objects, but all except a quadrillionth of the volume of a rock is empty space between particles in restless schizophrenic vibration. The world feels like a three-dimensional stage where events unfold over time, but Einstein's work suggests that change is an illusion, time being merely the fourth dimension of an unchanging space-time that just is, never created and never destroyed, containing our cosmic history like a DVD contains a movie. The quantum world feels random, but Everett's work suggests that randomness too is an illusion, being simply the way our minds feel when cloned into diverging parallel universes.

The ultimate triumph of physics would be to start with a mathematical description of the world from the "bird's eye view" of a mathematician studying the equations (which are ideally simple enough to fit on her T-shirt) and to derive from them the "frog's eye view" of the world, the way her mind subjectively perceives it. However, there is also a third and intermediate "consensus view" of the world. From your subjectively perceived frog perspective, the world turns upside down when you stand on your head and disappears when you close your eyes, yet you subconsciously interpret your sensory inputs as though there is an external reality that is independent of your orientation, your location and your state of mind. It is striking that although this third view involves both censorship (like rejecting dreams), interpolation (as between eye-blinks) and extrapolation (like attributing existence to unseen cities) of your frog's eye view, independent observers nonetheless appear to share this consensus view. Although the frog's eye view looks black-and-white to a cat, iridescent to a bird seeing four primary colors, and still more different to a bee seeing polarized light, a bat using sonar, a blind person with keener touch and hearing, or the latest robotic vacuum cleaner, all agree on whether the door is open.

This reconstructed consensus view of the world that humans, cats, aliens and future robots would all agree on is not free from some of the above-mentioned shared illusions. However, it is by definition free from illusions that are unique to biological minds, and therefore decouples from the issue of how our human consciousness works. This is why I've changed my mind: although understanding the detailed nature of human consciousness is a fascinating challenge in its own right, it is not necessary for a fundamental theory of physics, which need "only" derive the consensus view from its equations.

In other words, what Douglas Adams called "the ultimate question of life, the universe and everything" splits cleanly into two parts that can be tackled separately: the challenge for physics is deriving the consensus view from the bird's eye view, and the challenge for cognitive science is to derive the frog's eye view from the consensus view. These are two great challenges for the third millennium. They are each daunting in their own right, and I'm relieved that we need not solve them simultaneously.

ROBERT SAPOLSKY
Neuroscientist, Stanford University, Author, A Primate's Memoir

Well, my biggest change of mind came only a few years ago. It was the outcome of a painful journey of self-discovery, where my wife and children stood behind me and made it possible, where I struggled with all my soul, and all my heart and all my might. But that had to do with my realizing that Broadway musicals are not cultural travesties, so it's a little tangential here. Instead I'll focus on science.
 
I'm both a neurobiologist and a primatologist, and I've changed my mind about plenty of things in both of these realms. But the most fundamental change is one that transcends either of those disciplines — this was my realizing that the most interesting and important things in the life sciences are not going to be explained with sheer reductionism.

A specific change of mind concerned my work as a neurobiologist.

This came about 15 years ago, and it challenged neurobiological dogma that I had learned in pre-school, namely that the adult brain does not make new neurons. This fact had always been a point of weird pride in the field — hey, the brain is SO fancy and amazing that its elements are irreplaceable, not like some dumb-ass simplistic liver that's so totally fungible that it can regrow itself. And what this fact also reinforced, in passing, was the dogma that the brain is set in stone very early on in life, that there's all sorts of things that can't be changed once a certain time-window had passed.

Starting in the 1960's, a handful of crackpot scientists had been crying in the wilderness about how the adult brain does make new neurons. At best, their unorthodoxy was ignored; at worst, they were punished for it. But by the 1990's, it had become clear that they were right. And "adult neurogenesis" has turned into the hottest subject in the field — the brain makes new neurons, makes them under interesting circumstances, fails to under other interesting ones.

The new neurons function, are integrated into circuits, might even be required for certain types of learning. And the phenomenon is a cornerstone of a new type of neurobiological chauvinism — part of the very complexity and magnificence of the brain is how it can rebuild itself in response to the world around it.

So, I'll admit, this business about new neurons was a tough one for me to assimilate. I wasn't invested enough in the whole business to be in the crowd indignantly saying, No, this can't be true. Instead, I just tried to ignore it. "New neurons", christ, I can't deal with this, turn the page. And after an embarrassingly long time, enough evidence had piled up that I had to change my mind and decide that I needed to deal with it after all. And it's now one of the things that my lab studies.

The other change concerned my life as a primatologist, where I have been studying male baboons in East Africa. This also came in the early 90's. I study what social behavior has to do with health, and my shtick always was that if you want to know which baboons are going to be festering with stress-related disease, look at the low-ranking ones.  Rank is physiological destiny, and if you have a choice in the matter, you want to win some critical fights and become a dominant male, because you'll be healthier. And my change of mind involved two pieces.

The first was realizing, from my own data and that of others, that being dominant has far less to do with winning fights than with social intelligence and impulse control. The other was realizing that while health has something to do with social rank, it has far more to do with personality and social affiliation — if you want to be a healthy baboon, don't be a socially isolated one. This particular shift has something to do with the accretion of new facts, new statistical techniques for analyzing data, blah blah. Probably most importantly, it has to do with the fact that I was once a hermetic 22-year old studying baboons and now, 30 years later, I've changed my mind about a lot of things in my own life.

STEVE NADIS
Science writer; Contributing Editor, Astronomy Magazine


The Myth Of The "Open Mind"

When I was 21, I began working for the Union of Concerned Scientists (UCS) in Cambridge Massachusetts. I was still an undergraduate at the time, planning on doing a brief research stint in energy policy before finishing college and heading to graduate school in physics. That "brief research stint" lasted about seven years, off and on, and I never did make it to graduate school. But the experience was instructive nevertheless.

When I started at UCS in the 1970s, nuclear power safety was a hot topic, and I squared off in many debates against nuclear proponents from utility companies, nuclear engineering departments, and so forth regarding reactor safety, radioactive wastes, and the viability of renewable energy alternatives. The next issue I took on for UCS was the nuclear arms race, which was equally polarized. (The neocons of that day weren't "neo" back then; they were just cons.) As with nuclear safety, there was essentially no common ground between the two sides. Each faction was invariably trying to do the other in, through oral rhetoric and tendentious prose, always looking for new material to buttress their case or undermine that of their opponents.

Even though the organization I worked for was called the Union of Concern Scientists, and even though many of the staff members there referred to me as a "scientist" (despite my lack of academic credentials), I knew that what I was doing was not science. (Nor were the many physics PhD's in arms control and energy policy doing science either.) In the back of my head, I always assumed that "real science" was different — that scientists are guided by facts rather than by ideological positions, personal rivalries, and whatnot.

In the decades since, I've learned that while this may be true in many instances, oftentimes it's not. When it comes to the biggest, most contentious issues in physics and cosmology — such as the validity of inflationary theory, string theory, or the multiverse/landscape scenario — the image of the objective truth seeker, standing above the fray, calmly sifting through the evidence without preconceptions or prejudice, may be less accurate than the adversarial model of our justice system. Both sides, to the extent there are sides on these matters, are constantly assembling their briefs, trying to convince themselves as well as the jury at large, while at the same time looking for flaws in the arguments of the opposing counsel.

This fractionalization may stem from scientific intuition, political or philosophical differences,  personal grudges, or pure academic competition. It's not surprising that this happens, nor is it necessarily a bad thing. In fact, it's my impression that this approach works pretty well in the law and in science too. It means that, on the big things at least, science will be vetted; it has to withstand scrutiny, pass muster.

But it's not a cold, passionless exercise either. At its heart, science is a human endeavor, carried out by people. When the questions are truly ambitious, it takes a great personal commitment to make any headway — a big investment in energy and in emotion as well. I know from having met with many of the lead researchers that the debates can get heated, sometimes uncomfortably so. More importantly, when you're engaged in an epic struggle like this — trying, for instance, to put together a theory of broad sweep — it may be difficult, if not impossible, to keep an "open mind" because you may be well beyond that stage, having long since cast your lot with a particular line of reasoning. And after making an investment over the course of many years, it's natural to want to protect it. That doesn't mean you can't change your mind — and I know of several cases where this has occurred — but, no matter what you do, it's never easy to shift from forward to reverse.

Although I haven't worked as a scientist in any of these areas, I have written about many of the "big questions" and know how hard it is to get all the facts lined up so that they fit together into something resembling an organic whole. Doing that, even as a mere scribe, involves periods of single-minded exertion, and during that process the issues can almost take on a life of their own, at least while you're actively thinking about them. Before long, of course, you've moved onto the next story and the excitement of the former recedes. As the urgency fades, you start wondering why you felt so strongly about the landscape or eternal inflation or whatever it was that had taken over your desk some months ago.

It's different, of course, for researchers who may stake out an entire career — or at least big chunks thereof — in a certain field.  You're obliged to keep abreast of all that's going on of note, which means one's interest is continually renewed. As new data comes in, you try to see how it fits in with the pieces of the puzzle you're already grappling with. Or if something significant emerges from the opposing camp, you may instinctively seek out the weak spots, trying to see how those guys messed up this time.

It's possible, of course, that a day may come when, try as you might, you can't find the weak spots in the other guy's story. After many attempts and an equal number of setbacks, you may ultimately have to accede to the view of an intellectual, if not personal, rival. Not that you want to but rather because you can't see any way around it. On the one hand, you might chalk it up as a defeat, something that will hopefully build character down the road. But in the grand scheme of things, it's more of a victory — a sign that sometimes our adversarial system of science actually works.