BRIAN GREENE
Physicist, String Theorist, Columbia University; Author, The Fabric of the Cosmos

The Power of Our Creative and Analytic Abilities

As I help raise my two year old son, I witness a basic truth familiar to parents through the ages and across the continents — we begin life as uninhibited explorers with a boundless fascination for the ever-growing world to which we have access. And what I find amazing is that if that fascination is fed, and if it's challenged, and if it's nurtured, it can grow to an intellect capable of grappling with such marvels as the quantum nature of reality, the energy locked inside the atom, the curved spacetime of the cosmos, the elementary constituents of matter, the genetic code underlying life, the neural circuitry responsible for consciousness, and perhaps even the very origin of the universe. While we evolved to survive, once we have the luxury of taking such survival for granted, the ability of our species to unravel mysteries grand and deep is awe inspiring. I'm optimistic that the world will increasingly value the power of such rational thought and will increasingly rely on its insights in making the most critical decisions.

DAVID BUSS
Psychologist, University of Texas, Austin; Author, The Murderer Next Door

The Future of Human Mating

BART KOSKO
Electrical Engineer, USC; Author, Noise


Computers Will Let Data Tell More Of Their Own Story

I am optimistic that the rapid growth in computing power will let measured data tell more of their own story—rather than tell the story of the "model" that someone imposes on the data. The slow but steady movement away from classical model-based science tracks the growth in computers and digital processors.

Almost all traditional science and engineering has been model-based. Equations define the simplest models or functional relationships among input and output variables. Usually some super-smart thinker first makes an inspired guess at the model equations. The grand examples are Newton's guess at the inverse-square law of gravity and then Einstein's later and even bolder guess at the non-Euclidean geometry of the spacetime continuum.
Most models have lesser scope and far humbler origins. The modeler often guesses at a linear or quadratic or other simple relationship between the inputs and outputs even though the world itself appears to be quite nonlinear in general and often nonstationary as well. A standard modeling trick is to let a random noise term account for the difference between the nonlinear and largely unknown world and the far simpler model. Thus the humble noise or nuisance term carries much of the model's explanatory burden. Then the modeler compares the model to some data and looks for a pattern match to some degree. Other models can compete with the first model based on their pattern matches with the data.
          
Model-based science has produced most of our technological achievements. And it will likely always be at the core of the science curriculum. But it does rely on an arcane ability to guess at nature with symbolic mathematics. It is hard to see a direct evolutionary basis for such refined symbol manipulation although there may be several indirect bases that involve language skills and spatial reasoning.

A more immediate issue is that we tend to over-teach models in the science and engineering curriculum. One reason for this is that it is easy to teach closed-form equations and related technical theorems. Just state and derive the model result and apply it to examples based on numbers or on other equations. Equations make for wonderful homework problems. And it is especially easy to test on model equations and their consequences. It is not so easy to teach or test on data-intensive problems that can involve large tables of numerical data.

Another reason for over-teaching models is that so many of our textbooks in science and engineering have their roots in the pre-computing era surrounding World War II. That was the Shannon era of great analytical minds and authors such as probabilist Joseph Doob and chemist Linus Pauling and economist Paul Samuelson and many others. Students performed computations with slide rulers and then later with pocket calculators. Science and engineering textbooks today still largely build on those earlier texts from the pre-computer age where so often mathematical assumptions trumped raw data.

Rising computer power led to the first large break with the math-model approach in various species of artificial intelligence. Computer scientists programmed expert-system search trees directly from words. Some put uncertainty math models on the trees but the tree structure itself used words or text strings. The non-numerical structure let experts directly encode their expertise in verbal rules. That removed the old math models but still left the problem of literally doing only what the expert or modeler said to do.
Adaptive fuzzy rule-based systems allowed experts to state rules in words while the fuzzy system itself remained numeric. Data could in principle overcome modeler bias by adapting the rule structure in new directions as the data poured in. That reduced expert or modeler input to little more than giving initial conditions and occasional updates to the inference structure. Still all these AI tree-based knowledge systems suffer from the curse of dimensionality in some form of combinatorial rule explosion.

Feedforward neural networks further reduced the expert to a supervisor who gives the network preferred input-output pairs to train its synaptic throughput structure. But this comes at the expense of having no logical audit trail in the network's innards that can explain what patterns the network encodes or what patterns it partly or wholly forgets when it learns new input-output patterns. Unsupervised neural networks tend to be less powerful but omit more modeler bias because the user does not give the network preferred outputs or teaching signals. All these AI systems are model-free in the sense that the user does not need to state a math model of the process at hand. But each still has some form of a functional math model that converts inputs to outputs.

Statistics has arguably been the real leader in the shift from models to data --even though classical linear regression has been imposing lines and planes on the world for over two centuries. Neural and fuzzy learning systems turn out ultimately to have the structure of nonlinear but still statistical approximators. Closed-form statistics also produced Bayesian models as a type of equation-based expert system where the expert can inject his favorite probability curve on the problem at hand. These models have the adaptive benefit that successive data often washes away the expert's initial math guesses just as happens in an adaptive fuzzy system. The AI systems are Bayesian in this sense of letting experts encode expertise directly into a knowledge structure—but again the knowledge structure itself is a model of sorts and thus an imposition on the data.

The hero of data-based reasoning is the bootstrap resample. The bootstrap has produced a revolution of sorts in statistics since statistician Bradley Efron introduced it in 1979 when personal computers were becoming more available. The bootstrap in effect puts the data set in a bingo hopper and lets the user sample from the data set over and over again just so long as the user puts the data back in the hopper after drawing and recording it. Computers easily let one turn an initial set of 100 data points into tens of thousands of resampled sets of 100 points each. Efron and many others showed that these virtual samples contain further information about the original data set. This gives a statistical free lunch except for the extensive computation involved—but that grows a little less expensive each day. A glance at most multi-edition textbook on statistics will show the growing influence of the bootstrap and related resampling techniques in the later editions.

Consider the model-based baggage that goes into the standard 95% confidence interval for a population mean. Such confidence intervals appear expressly in most medical studies and reports and appear implicitly in media poll results as well as appearing throughout science and engineering. The big assumption is that the data come reasonably close to a bell curve even if it has thick tails. A similar assumption occurs when instructors grade on a "curve" even the student grades often deviate substantially from a bell curve (such as clusters of good and poor grades). Sometimes one or more statistical tests will justify the bell-curve assumption to varying degrees — and some of the tests themselves make assumptions about the data. The simplest bootstrap confidence interval makes no such assumption. The user computes a sample mean for each of the thousands of virtual data sets. Then the user rank-orders these thousands of computed sample means from smallest to largest and picks the appropriate percentile estimates. Suppose there were a 1000 virtual sample sets and thus 1000 computed sample means. The bootstrap interval picks the 25th — largest sample mean for the lower bound of the 95% confidence interval and picks the 975th — largest sample mean for the upper bound. Done.

Bootstrap intervals tend to give similar results as model-based intervals for test cases where the user generates the original data from a normal bell curve or the like. The same holds for bootstrap hypothesis tests. But in the real world we do not know the "true" distribution that generated the observed data. So why not avoid the clear potential for modeler bias and just use the bootstrap estimate in the first place?

Bootstrap resampling has started to invade almost every type of statistical decision making. Statisticians have even shown how to apply it in complex cases of time-series and dependent data. It still tends to appear in statistics texts as a special topic after the student learns the traditional model-based methods. And there may be no easy way to give student scientists and engineers an in-class exam on bootstrap resampling with real data.

Still the trend is toward ever more data-based methods in science and engineering — and thus towards letting the data tell more of their own story (if there is a story to tell). Math models have tradition and human psychology on their side. But our math models grow at an approximate linear rate while data processing grows exponentially.

Computing power will out.

OLIVER MORTON
Chief News and Features Editor, Nature; Author, Mapping Mars

Sunshine State

I am not, by default, optimistic; it is an attribute that I take on as a duty more than out of temperament. Left to myself I do not look out at the world and see a hopeful place—and did not do so even when the geopolitical state we are in was not so dreadful. But I have been convinced over the years that an outlook that gives play to hopefulness is by and large a better tool with which to help improve the future than the alternatives. You are more likely to find solutions if you believe they are there than not. The trick for those of us without the sunny state of mind naturally suited to such an outlook is to find objects for our optimism that make the duty feel less dutiful.

My current optimism is for solar energy. The simple facts of the matter are that the sun provides more energy to the earth in an hour than humanity makes use of in a year. Of the non-fossil-fuel energy sources, all the big players that are not nuclear—biomass, hydroelectric, wind—are ultimately driven by the sun. I am optimistic that direct solar conversion—photovoltaic cells and their future analogues—will come to take its place among and then surpass these more established technologies a lot more quickly than most people outside the area currently imagine. I'am hoping for at least a terawatt of solar by 2025, two if we're lucky, and dramatic cuts in carbon dioxide emissions as a result.

The locus for this optimism is California. A history of generous and far-sighted subsidy has built up the silicon-based Japanese and German solar industries over the past decades. Something similar now looks to be happening on the West Coast, where newer technologies are poised to benefit. There couldn't be a better suited place: California, and in particular the Bay area, boasts a near-unique concentration of world class research universities and national laboratories and a large number of people well versed in the solid-state trades who are ready and able to move from semiconductors that deal with information to those that deal with energy. It is also very well endowed with business angels and venture capitalists, many of whom combine their desire to make money with an urge to change the world. They largely share a network-first, build-from-the-periphery, revolutionise-the-whole-shebang mindset well suited to (and shaped by) the development of the Internet, an attitude which ports itself easily to the idea of decentralised solar power generation. The optimism to which I need to psych myself up seems to come naturally to such people in such places.

New materials and new material-processing techniques should allow the cost of installed photovoltaic capacity to be halved in the next few years, and there is room for considerable further improvement after that: while wind power, nuclear power and dams are not going to become radically cheaper to install, solar power capacity is. It is also going to become more flexible, both physically and metaphorically, with new applications on new surfaces, from windows to clothing. Some of these applications may well be gimmicky and unsustainable, but one of the great advantages of the coming solar power boom is that it offers the possibility for a wide range of technologies both to compete for the main prize—cheap domestic and light industrial electricity in developed and developing countries alike—and also to find and to create new niches.

The boom will not just be a matter of lower cost manufacture or better efficiency. System-wide solutions need to be found—new ways of accommodating solar materials architecturally, new technologies for storing energy, smart approaches to the electric grid, new financial arrangements and instruments that will allow people to get the benefits of solar electricity without necessarily taking on the capital costs of installation themselves. The sort of imagination that gets such things happening is far from unique to California—but it is abundant there, and can be put to use.

STUART A. KAUFFMAN
Director, The Institute for Biocomplexity and Informatics, The University of Calgary; Author, At Home in the Universe


Cancer Stem Cells and Novel Cancer Therapies

In the past few years evidence has increased that "cancer stem cells" play a fundamental role in cancer. Typically comprising about 1% or less of a total tumor mass, these cancer stem cells appear to have unlimited proliferation potential, and the capacity to drive cancer growth. In addition, cancer stem cells have been implicated in metastasis. Cancer stem cells have already been found in the leukemias, lung, colon, prostate, breast, skin, ovarian, and neural cancers. They may be present in all cancers.  Their discovery may be the most important discovery in cancer biology in the past half century. Cancer stem cells are likely to afford entirely new cancer therapies in the modestly near future.

Given cancer stem cells, it becomes obvious that merely reducing the mass of a tumor without eliminating the cancer stem cells will almost surely lead to a recurrence of the disease. Thus, increasing numbers of investigators, including myself, are now focusing effort in three related directions: 1) Find means to selectively kill cancer stem cells. 2) Find means to stop cancer stem cells from proliferating. 3) Find means to induce cancer stem cells to differentiate—or change cell type—to non-malignant cell types.

While it is simply foolish to think cancer is simple, I believe it is a realistic hope that work on cancer stem cell therapy has a strong chance to dramatically improve cancer therapy within the next few decades. There are a number of approaches to this attempt. Among them, it is now possible using a new discovery, siRNA, to "turn off" the translation of the messenger RNA of any specific gene into its protein product. In addition, using other molecular biology techniques it is possible to over express any gene. These molecular techniques mean that investigators can now try to perturb the activities of specific genes that control cancer stem cell behavior in an attempt to attain the three aims above.

Further, high throughput screening via robotics now allow small molecule and other chemical libraries of high diversity to be screened to search for molecular perturbations which, if applied to cancer stem cells, achieves selective killing, cessation of proliferation, or differentiation to benign cell types. Our own laboratory and an increasing number of other laboratories are undertaking this work.

Differentiation therapy is already clinically effective in the case of treatment of acute myelogenous leukemia, AML, with vitamin A. The cancer cells differentiate into normal blood cells that do not proliferate. In addition, a research group recently screened a mere 1700 chemicals and found eight that caused AML cells to differentiate to or towards normal non-proliferating blood cells. Thus it is not improbable that by screening chemical libraries with thousands to hundreds of thousands of distinct compounds, molecules capable of selectively killing, shutting down proliferation, or inducing differentiation of cancer stem cells will be found in the modestly near future.

These approaches, however, must, as ever, be viewed with cautious optimism. For example, it may be the case that other cancer cells in a tumor can differentiate back into cancer stem cells. If so, they would require treatment, perhaps making cancer a chronic disease. The "same" cancer from diverse patients may typically have accumulated different subsets of gene mutations, rendering the hope of finding a single magic bullet good for all cases of that cancer moot. Conversely, vitamin A is widely useful in AML, raising the hope that a modest number of compounds might treat most cases of the "same" cancer in diverse patients. Further, the relation between cancer stem cells and normal adult stem cells remains to be clarified. A treatment that eliminated both cancer stem cells and normal stem cells of a given tissue could have untoward effects. Elimination of leukemic cancer stem cells might eliminate normal blood (hematopoetic) stem cells and affect the normal processes of these normal stem cells in blood formation. Conversely, one can hope that techniques will be found that can sustain the patient during therapy and regenerate normal, here blood, stem cells from other stem cells in a patient, transplant them into the patient after cancer therapy, and overcome the normal stem cell loss induced by therapy. And for some tissues, prostate, ovaries, uterus, loss of normal stem cells may not be grave.

 The potential implications of cancer stem cell therapy are enormous. And the world scientific community is rapidly grasping the potential significance. It is important to stress that this effort will be "big biology", for techniques such as high throughput screening and tests of patterns of gene activities using genetic microarrays are very expensive. Adequate funding will be required. Overall, I am deeply optimistic as a doctor and biological scientist that we will, at last, find subtle ways to treat cancer either as stand alone therapies, or in conjunction with familiar surgery, radiation and chemotherapy.

NANCY ETCOFF
Psychologist, Harvard Medical School & Harvard University’s Mind/Brain/Behavior Initiative; Author, Survival of the Prettiest: The Science of Beauty


The Hedonic Set Point Can Be Raised

Most people are pretty happy and the rest distribute into the very unhappy, pretty unhappy or very happy categories. Wherever they fall on the happiness scales, people keep pursuing happiness. They want more. Can they get it? I offer a cautiously optimistic yes.

I'll admit that the initial yield from the new science of happiness did little to support my optimism. It showed that happiness levels are durable, withstanding sweeping changes in health and wealth. Life changes, it suggests, but you don't. It showed that there is a substantial genetic component to happiness. People have a personal baseline of happiness that is influenced by stable personality traits such as extroversion or neuroticism that are partly heritable The happiness baseline has been likened to the body weight set point, leading some to believe that adding permanent points on the happiness scale is as likely as offloading pounds permanently from the weight scale. You've got a battle on your hands with a formidable opponent: yourself. Short of a biological fix, happiness interventions seemed doomed to formidable recidivism rates.

But the extreme picture of the human happiness baseline as a fixed set point and of adaptation to life events as inevitable and complete is wrong, and it's being revised rapidly While the "average" person's happiness may bounce back to baseline, the happiness of many individuals does not (about 1 in 4 people show a change of 2 or 3 points on a 0-10 scale with 9% showing changes of 3 or more points and even stable people show an average of a 1 point change in a recent study). Personality is much less stable than body weight, and happiness levels are even less stable than personality.

I said "cautiously" optimistic because, so far, for every person who shows a substantial lasting increase in happiness, 2 people show a decrease. Discarding the set point idea for a more malleable happiness baseline means that we will uncover vulnerability as well as hope.

I am also optimistic that we will uncover diverse ways that people can find sustainable happiness. But we'll need to dig beneath the surface and resist "once size fits all" formulas. I'll give one example. Some often-cited research suggests that married people are happier than "singles" (the never married, divorced, widowed, co-habitors). The latter group is large and getting larger. As of 2002 there were 86 million single adults in the United States; more than 40% of adults over 18 are single, up from 28% in 1970. Is this massive demographic shift dooming us to increasing unhappiness? Should we encourage people to marry to increase their happiness?

People marry for many reasons, but here, lets just consider their happiness. The newest research follows large groups of people over long periods of time. It finds that the average person adapts to marriage; after the first year or two, she is not any happier than she was before marriage (an alternate analysis of the data suggests that adaptation is incomplete but that happiness is increased by a tiny amount , .115 on a 0-10 scale). Looking beyond averages to individuals, the data show that some people return to their former happiness levels, some end up much happier and about an equal number end up significantly less happy than they were before they were married.

Although this data will dismay some passionate advocates of marriage, I think it is good news both for the married and for the single. The idea that that marriage should make you permanently happier places a large burden on the already burdened state of marriage and unrealistic expectations on partners. But the fact that it can and it does for some, by a large amount and for very long a time is a thrilling possibility.

The data suggests that the demographic trends we are seeing away from marriage do not portend an increasingly unhappy society. Along with other evidence, it suggests that what is important for happiness is the quality of a relationship and not its civil status.

Finally, forget optimism, I know this for sure: we will always form passionate bonds with others, and through them find joy, solace, comfort, love, amusement, sympathy, and moments of ecstasy, and we will know in them the awe and wonder of being alive.

JOHN MCCARTHY
Computer Scientist; 1st Generation Artificial Intelligence Pioneer, Stanford University

World Peace

I'm optimistic about the sustainability of materil progress, but since I'm known for that, I'll refrain. Instead I want to express optimism about world politics, especially about world peace.

World peace is what we have. There are only minor wars and no present
prospect of a major war threatening western civilization and its present extensions to the actually developing countries. Only Africa and the Arab world are in bad shape.

Contrast this with the time between 1914 and 1989, when there were
serious attempts at world domination accompanied by at least three
genocides.

Admittedly something bad and surprising could happen. 100 years ago,
in 1907, no-one predicted such troubles as happened. Even in April 1914, Bertrand Russell could write:

"To us, to whom safety has become monotony, to whom the primeval savageries of nature are so remote as to become a mere pleasing condiment to our ordered routine, the world of dreams is very different from what it was amid the wars of Guelf and Ghibelline. Hence William James's protest against what he calls the "block universe" of the classical tradition; hence Nietsche's worship of
force; hence the verbal bloodthirstiness of many quiet literary men. The barbaric substratum of human nature, unsatisfied in action, finds an outlet in imagination. In philosophy, as elsewhere, this tendency is visible; and it is this, rather than formal argument, that has thrust aside the classical tradition for a philosophy which fancies itself more virile and more vital."

As for Arab jihadism, I think they'll get over it as soon as a new generation matures to oppose their parents' slogans. If not

Whatever happens we have got
The Maxim Gun, and they have not.

— Hilaire Belloc, 1898, The Modern Traveller, part 6.

It is important that the political causes of the 20th century disasters, virulent and militaristic nationalism accompanied by letting one man take power, do not exist in major countries today. Communism is dead as a motivator of violence. The green movement is accompanied by occasional minor violence, but a green Hitler or Stalin seems unnlikely.

Still, it's hard to predict 100 years ahead. As Stephen Hawking advocates, humanity would be safer if it expanded beyond the earth.

MARVIN MINSKY
Computer Scientist; 1st Generation Artificial Intelligence Pioneer, MIT; Author, The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind

New Prospects of Immortality

Benjamin Franklin: I wish it were possible... to invent a method of embalming drowned persons, in such a manner that they might be recalled to life at any period, however distant; for having a very ardent desire to see and observe the state of America a hundred years hence, I should prefer to an ordinary death, being immersed with a few friends in a cask of Madeira, until that time, then to be recalled to life by the solar warmth of my dear country! But... in all probability, we live in a century too little advanced, and too near the infancy of science, to see such an art brought in our time to its perfection.
—Letter to Jacques Dubourg, April 1773

Eternal life may come within our reach once we understand enough about how our knowledge and mental processes are embodied in our brains. For then we should be able to duplicate that information — and then into more robust machinery. This might be possible late in this century, in view of how much we are learning about how human brains work — and the growth of computer capacities.

However, this could have been possible long ago if the progress of science had not succumbed to the spread of monotheistic religions. For as early as 250 BCE, Archimedes was well on the way toward modern physics and calculus. So in an alternate version of history (in which the pursuit of science did not decline) just a few more centuries could have allowed the likes of Newton, Maxwell, Gauss, and Pasteur to anticipate our present state of knowledge about physics, mathematics, and biology. Thenperhaps by 300 AD we could have learned so much about the mechanics of minds that citizens could decide on the lengths of their lives.

I'm sure that not all scholars would agree that religion retarded the progress of science. However, the above scenario seems to suggest that Pascal was wrong when he concluded that only faith could offer salvation. For if science had not lost those millennia, we might be already be able to transfer our minds into our machines. If so, then you could rightly complain that religions have deprived you of the option of having an afterlife!

Do we really want to lengthen our lives?

Woody Allen: I don't want to achieve immortality through my work. I want to achieve it through not dying.

In discussing this prospect with various groups, I was surprised to find that the idea of extending one's lifetime to thousands of years was often seen as a dismal suggestion. The response to my several informal polls included such objections as these: "Why would anyone want to live for a thousand hundred years? What if you outlived all your friends? What would you do with all that time? Wouldn't one's life become terribly boring?"

What can one conclude from this? Perhaps some of those persons lived with a sense that they did not deserve to live so long. Perhaps others did not regard themselves as having worthy long term goals. In any case, I find it worrisome that so many of our citizens are resigned to die. A planetful of people who feel that they do not have much to lose: surely this could be dangerous. (I neglected to ask the religious ones why perpetual heaven would be less boring.)

However, my scientist friends showed few such concerns: "There are countless things that I want to find out, and so many problems I want to solve, that I could use many centuries." I'll grant that religious beliefs can bring mental relief and emotional peace—but I question whether these, alone, should be seen as commendable long-term goals.

The quality of extended lives

Anatole France: The average man, who does not know what to do with his life, wants another one which will last forever.

Certainly, immortality would seem unattractive if it meant endless infirmity, debility, and dependency upon others—but here we'll assume a state of perfect health. A somewhat sounder concern might be that the old ones should die to make room for young ones with newer ideas. However, this leaves out the likelihood that are many important ideas that no human person could reach in, say, less than a few hundred well focused years. If so, then a limited lifespan might deprive us of great oceans of wisdom that no one can grasp.

In any case, such objections are shortsighted because, once we embody our minds in machines, we'll find ways to expand their capacities. You'll be able to edit your former mind, or merge it with parts of other minds — or develop completely new ways to think. Furthermore, our future technologies will no longer constrain us to think at the crawling pace of "real time." The events in our computers already proceed a millions times faster than those in our brain. To such beings, a minute might seem as long as a human year.

How could we download a human mind?

Today we are only beginning to understand the machinery of our human brains, but we already have many different theories about how those organs embody the processes that we call our minds. We often hear arguments about which of those different theories are right — but those often are the wrong questions to ask, because we know that every brain has hundreds of different specialized regions that work in different ways. I have suggested a dozen different ways in which our brains might represent our skill and memories. It could be many years before we know which structures and functions we'll need to reproduce.

(No such copies can yet be made today, so if you want immortality, your only present option is to have your brain preserved by a Cryonics company. However, improving this field still needs further research — but there is not enough funding for this today — although the same research is also needed for advancing the field of transplanting organs.)

Some writers have even suggested that, to make a working copy of a mind, one might have to include many small details about the connections among all the cells of a brain; if so, it would require an immense amount of machinery to simulate all those cells' chemistry. However, I suspect we'll need far less than that, because our nervous systems must have evolved to be insensitive to lower-level details; otherwise, our brains would rarely work.

Fortunately, we won't need to solve all those problems at once. For long before we are able to make complete "backups" of our personalities, this field of research will produce a great flood of ideas for adding new features and accessories to our existing brains. Then this may lead, through smaller steps, to replacing all parts of our bodies and brains — and thus repairing all the defects and flaws that make presently our lives so brief. And the more we learn about how our brains work, the more ways we will find to provide them with new abilities that never evolved in biology.

GEORGE F. SMOOT
Cosmologist, Lawrence Berkeley National Laboratory; Recipient, The Nobel Prize For Physics 2006; Coauthor, Wrinkles in Time

Correggio Domani e for peggio! — Courage for Tomorrow Will Be Worse! (The Words of a Born Optimist)

A careful assessment and years of experience that show that the long-term future is most bleak: Entropy will continue to increase, and a heat death (actually a misnomer as it means the degredation of usable energy in a dull cooling worthless background of chaos) is the very likely fate of the world. This is the fate that awaits us, if we manage to work our way past the energy crisis that looms as the Sun runs out of fuel and in its death throws expands as red giant star likely to engulf us after boiling away the seas before it collapses back to a slowly cooling cinder eventually to leave the solar system in cold darkness.

This energy crisis will eventually spread to the whole Milky Way Galaxy which will use up its available energy resources in a time scale of roughly ten times the present 14 billion year lifetime of our observed Universe. In that same time the accelerating expansion of the Universe continually reduces what we can observe and potentially access until in the distant future only the cinders of stars in our own galaxy are left. Argument goes on whether a sufficiently advanced intelligent society could manage to live (continue to have experiences and process new information and create new things) indefinitely in such an environment taking on the most carefully constructed and extreme measures that are physically possible. The chances of success look relatively low for even the most optimally managed and intelligent society.

Given this and the history of human society in cooperatively plundering the resources of a meager but beautiful planet with currently abundant resources, who can possibly be optimistic about the long-term future of humanity? How many examples do we have of humans addressing global problems in an efficient way and with enlightened self-interest? Historical experience is that humans have generally been engaged in warfare, exploitation for personal gain and religious strife. Real issues are generally not addressed until they become serious crises and often not even then. We could mention here, various episodes of genocide, large-scale pollution, and ecological devastation, which are often interrelated.

In this background the rise of culture and science is remarkable. That is until we understand their usefulness. In our modern world it is clear that material rewards and political power accrue to those that have the most scientific and technological knowledge and the educated workforce with the cultural background of hard productive work as part of a larger system. Such societies have economic and military success and large tax revenues.

Is it this culture and knowledge that offers us hope to be at least as successful as the dinosaurs which dominated the Earth for nearly 100 times as long as humans have held sway? It is often said that the United States systematically underestimates the stubbornness preventing the peaceful resolution of long-term ethnic and tribal conflicts — perhaps because of being the melting pot of waves of peaceful immigration — less a few Indian wars. However, could humans share the planet with reptiles? Or how about intelligent machines? Could they share with us?

Now leaving cultural and religious value systems aside, let us move to realistic assessment of the title "Courage for Tomorrow will be Worse". Every physical process in the Universe follows the second law of thermodynamics. That is in every process entropy (a measure of disorder which equals loss of information and usefulness) will tend to increase for the Universe as a whole. No process decreases the entropy of the Universe. Only completely reversible processes leave it unchanged. All living things and all man-made machines operate with processes that increase the entropy of the Universe.

One cannot live by the Hippocratic dictum "Do no harm". But the best one can hope for is the weak mantra "Do minimal damage". I was often bothered by this inevitable conclusion and tried to see that if one could write a great work of literature, make art, or most optimally a great science discovery could one objectively leave the world better than one found it? Each time I worked out an example, the impact was negligible however great it was found by human culture compared to the damage done by mere existence. The only discovery that would make a difference called for repealing or avoiding the laws of probability or making a whole new universe. Both of these are quite extreme. Perhaps the discovery of extra dimensions would allow some leeway in what otherwise seems an inescapable doom after a long period of unrighteous degradation of the universe. We face a continuous downward spiral of no return. This is not a moral or ethical statement only an engineering evaluation though it is some indication of original sin. So even living one's life as a vegetarian that only eats fruit dropped into one's hand by a willing plant is only going so far as to be very kind and considerate to other beings that are also worsening the universe for the sake of a little more order in their own self.

With such sure knowledge of one's own impending demise as well as for all humanity, how can one get up and face each day with any hope? Well in science it is a central tenet to be skeptical and to question and as certain as this seems, one could cling to a shred of hope that there is some trap door of escape that will be found and opened either because of the greatness and infinite flexibility of mankind or our incredible ingenuity under extreme pressure. I suspect that the odds of winning the lottery are higher — much higher.

"perchè sai che domani sarà impossibile anche alla tua astuzia." (poet Eugenio Montale)

"because you know that tomorrow it will be impossible no matter how astute you are." (translation by Jody Fitzhardinge & Lorenzo Matteoli)

Instead one might look to the definition of courage and optimism and go forth cheerfully and eagerly even when there isn't the smallest sliver of hope and still do great and glorious deeds, build great civilizations even in the face of their inevitable doom.

It takes real optimism and courage to go forth when the inevitable course for the universe is downhill and knowing that all humanity has done or is likely to do will probably have less impact than a footprint on sand after a few dozen or thousand waves pass over it.

I am from the very beginning an optimist and remain so right to the very end.

I invest time and effort into my work, my health and fund my retirement plan fully.

I even write articles and spend much of my days training and educating the next generation. Why do I do this? Because I think that the future, on my human and longer time scale, can be very bright as long as humans work well and intelligently.

I look forward to the immediate future as a part of the long human slog towards a better culture and society in spite of the constant flux of misguided craziness.

NATHAN MYHRVOLD
CEO, Managing Director, Intellectual Ventures; Former Chief Technology Officer, Microsoft Corporation; Physicist, Paleontologist,Photographer, Chef


The Power of Educated People to Make Important Innovations

It is interesting that pessimism seems to be the conventional wisdom — i.e. that the world is going to hell in a hand basket and things are getting worse. In the short run pessimism is an easy bet. The news media, for example, would be a terrible business if there was only good news — shocking bad news sells more newspapers (or generates more Neilson ratings, or internet clicks). Yet they need not worry about there being a dearth of bad news — its only a matter a time before some more bad news comes in.

However, I think that the focus on pessimism is hugely misleading. The pattern of the last five decades is that by and large the most important factors in human life have improved immensely. By and large there is no better time to be alive than today, and any rational estimate is that we will continue to be in a phase of continued improvement.

Perhaps the biggest reason I am optimistic is that I am a huge believer in the power of educated people to make important innovations. The trends in China and India and elsewhere toward educating literally millions of people with scientific, engineering and technical degrees is tremendously positive. It is trendy in some US-centric circles to bemoan the fact that China and India are graduating more engineers than the US — indeed the developing has the potential to graduate more engineers than the US has people. I view that with tremendous optimism — at least on the whole. There will be negative consequences to be sure, and some naysayer will whine about them. History is clear that the negatives of bringing high levels of education to heretofore under educated people are more than outweighed by the tremendous positives.

ROBERT TRIVERS
Evolutionary Biologist, Rutgers University; Coauthor, Genes In Conflict: The Biology of Selfish Genetic Elements


Long-Term Trends Toward Honesty to Others and Self

What goes up comes down, what goes around comes around, for each action there is a reaction, and so on. Life is intrinsically self-correcting at almost all its levels, including evolutionary, physiological, historical and genetic. This permits a limited optimism. Wickedness and stupidity are ultimately self-destructive and self-limiting, so we need not trouble ourselves that any particular trend in that direction will go on indefinitely.

On the other hand, the principle of self-correction also applies to love, friendship and high intellectual powers. No movement in these directions can proceed long without setting up counter-pressures against their further spread.

In short, we should neither be too despondent nor too elated at the trajectory of current events. Sooner or later — and usually sooner — they will be reversed.

Two questions arise.

Are there long-term trends we could feel optimistic about? Thirty years of work on the evolutionary trajectory of cooperative strategies suggest long-term trends (under a broad range of conditions) toward greater cooperation, contingent on ever more sophisticated discrimination. It seems likely that when similar models are produced for varying degrees of deceit and self-deception, long-term trends toward honesty to others and self will (at least under some conditions) be favored.

Is there any reason to believe that we will survive long enough to enjoy any of these long-term trends?

This is far less certain. Evolution does not plan for contingencies that have not yet occurred and the vast majority of species go extinct. There is no reason to expect humans are exempt from these rules. The good news is that there is presently no chance that we could extinguish all of life — the bacterial "slimosphere" alone extends some ten miles into the earth — and as yet we can only make life truly miserable for the vast majority of people, not extinguish human life entirely. I would expect this state of affairs to continue indefinitely. The feeling that everything may be fine if only we survive the next 50 to 500 years may become a regular part of our psychology.