"A lady said, 'What's your solution?'
I said, 'There are no solutions. There are only trade-offs.'
She said, 'The people demand solutions!'
- Thomas Sowell

When the Boston Red Sox won their first World Series title since 1918 last year, the team had some new blood, including key players Curt Schilling, Orlando Cabrera and Doug Mientkiewicz, to mix with the old and help the team achieve the pinnacle of baseball success.

In a paper to be published April 29 in the journal Science, Northwestern University researchers turned to a different type of team -- creative teams in the arts and sciences -- to determine a team's recipe for success. They discovered that the composition of a great team is the same whether you are working on Broadway or in economics.

The researchers studied data on Broadway musicals since 1877 as well as thousands of journal publications in four fields of science and found that successful teams had a diverse membership -- not of race and gender but of old blood and new. New team members clearly added creative spark and critical links to the experience of the entire industry. Unsuccessful teams were isolated from each other whereas the members of successful teams were interconnected, much like the Kevin Bacon game, across a giant cluster of artists or scientists.

Gordon Rugg cracked the 400-year-old mystery of the Voynich manuscript. Next up: everything from Alzheimer's to the origins of the universe.

Two years ago, an Englishman named Gordon Rugg slipped back in time. Night after night he spread his papers on the kitchen table once his children had gone to bed. Working on faux parchment with a steel-nibbed calligraphic pen, he scribbled a strange, unidentifiable, vaguely medieval script. Transliterated into the Roman alphabet, some of the words read: "qopchedy qokedydy qokoloky qokeedy qokedy shedy." As he wrote, he struggled to get inside the mind of the person who had first scrawled this incomprehensible text some 400 years ago.

By day, Rugg, a 48-year-old psychologist, teaches in the computer science department of Keele University, near Manchester, England. By night, as an intellectual exercise, he has been researching one of the world's great oddities: the Voynich manuscript, a hand-lettered book written in an unknown code that has frustrated cryptographers since its discovery in an Italian villa in 1912. How impregnable is the Voynich? During World War II, US Army code breakers - the guys who blew away Nazi ciphers - grappled with the manuscript in their spare time and came up empty. Since then, decoding the book's contents has become an obsession for geeks and puzzle nuts everywhere.

Then came Rugg. In three months, he cooked up the most persuasive explanation yet for the 234-page text: Sorry, folks, there is no code - it's a hoax! Lifelong Voynichologists were impressed with his reasoning and proofs, even if they were a little chagrined. "The Voynich is such a challenge," says Rugg, "such a social activity. But then along comes someone who says 'Oh, it's just a lot of meaningless gibberish.' It's as if we're all surfers, and the sea has dried up."

When the news of Rugg's breakthrough was published last winter, everyone missed the bigger story. Rugg cracked the Voynich not because he was smarter, but because he focused on what everyone else had missed. Then again, this came naturally to Rugg: He has made a career out of studying how experts acquire knowledge yet screw up nevertheless. In 1996, he and his colleagues developed a rigorous method for peering over the shoulders of experts - doctors, software engineers, pilots, physicists - watching how they work and think, testing their logic, and uncovering ways to help them solve problems.

Rugg calls it the verifier approach, and the Voynich was its first major test. If Rugg gets his way, verifiers will revolutionize the scientific method and help solve other seemingly unsolvable mysteries, such as the origins of the universe or the cause of Alzheimer's disease.

Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies, and Nations

In the summer of 2003, analysts at the Department of Defense had an unusual idea. To predict important events in the world, including terrorist attacks, they would create a kind of market in which ordinary people could actually place bets. The proposed Policy Analysis Market would allow each of us to invest in our predictions about such matters as the growth of the Egyptian economy, the death of Yasir Arafat, and the likelihood of terrorist attacks in the United States. Investors would win or lose money on the basis of the accuracy of their predictions. Predictably, the Policy Analysis Market produced a storm of criticism. Ridiculed as "offensive" and "useless," the proposal was abandoned.

Amid the war on terrorism, why was the Defense Department so interested in the Policy Analysis Market? The answer is simple: it wanted to have some help in predicting geopolitical events, including those that would endanger American interests, and it believed that a market would provide that help. It speculated that if a large number of people could be given an incentive to aggregate their private information, in the way that the Policy Analysis Market would do, government officials would learn a great deal.

Does this idea seem ludicrous? Since 1988, the University of Iowa has run the Iowa Electronic Markets, which allow people to bet on the outcome of presidential elections. As a predictor, the Iowa Electronic Markets have produced extraordinarily accurate judgments, often doing better than professional polling organizations. In the week before each of the last four elections, the predictions in the Iowa market have shown an average absolute error of just 1.5 percentage points, a significant improvement over the 2.1 percentage point error in the final Gallup Polls. Or consider the Hollywood Stock Exchange, in which people predict Oscar nominees and winners, as well as opening weekend box-office successes. Here, too, the level of accuracy has been exceptionally impressive, with (for example) correct predictions of thirty-five out of forty Oscar nominees in 2002.

In fact, prediction markets are springing up all over the Internet, allowing people to make bets on the likely outcomes of sports, entertainment, finance, and political events. On tradesports.com, people have been betting on whether Donald Rumsfeld will resign soon (extremely unlikely), whether Osama bin Laden will be captured by June 2004 (extremely unlikely), whether John Edwards will be selected as John Kerry's running mate (a good chance, but probably not), and whether George W. Bush will be re-elected (more likely than not). One can imagine prediction markets on any number of questions: Will gas prices reach $3 per gallon? Will cellular life be found on Mars? Will smallpox return to the United States? Will there be a sequel to Master and Commander? Will the Federal Communications Commission be abolished? (I didn't make these up; they are actual or proposed questions on existing markets.)

James Surowiecki is fascinated by prediction markets. In his opinion, they demonstrate that crowds are often wise. He rejects the widespread view that groups of ordinary people are usually wrong--and that we do better to ignore them and follow experts instead. Even when individuals blunder, he believes, groups can excel: "Under the right circumstances, groups are remarkably intelligent, and are often smarter than the smartest people in them." This is so even when "most of the people within the group are not especially well-informed or rational." What is wonderful, and surprising, is that "when our imperfect judgments are aggregated in the right way, our collective intelligence is often excellent." Instead of chasing experts, we should consult that collective intelligence.

The Model of Hierarchical Complexity presents a framework for scoring reasoning stages in any domain as well as in any cross cultural setting. The scoring is based not upon the content or the subject material, but instead on the mathematical complexity of hierarchical organization of information. The subject’s performance on a task of a given complexity represents the stage of developmental complexity.

(DANNY HILLIS:) I have always envied Alexander the Great, because he had Aristotle as a personal tutor. In those days, Aristotle knew pretty much everything there was to know. Even better, Aristotle understood the mind of Alexander. He understood which topics interested Alexander, what Alexander knew and did not know, and what kinds of explanations Alexander preferred. Aristotle had been a student of Plato, and he was himself a great teacher. We know from his writings that he was full of examples, explanations, arguments, and stories. Through Aristotle, Alexander had the knowledge of the world at his command.

Of course no one today knows all that is known, in the sense that Aristotle did. Now there is far too much knowledge for that to be possible. The scientific revolution, and the technological revolution that followed it, led to a self-reinforcing explosion of knowledge. The explosion continues. Today not even the most highly trained scientist, the most scholarly historian, or the most competent engineer can hope to have more than a general overview of what is known. Only specialists understand most of the new discoveries in science, and even the specialists have trouble keeping up.

This problem isn't new. In 1945, Vannevar Bush wrote an essay for Atlantic Monthly about out the problem of too much knowledge. He wrote,

The significant problems we face cannot be solved at the same level of thinking we were at when we created them.
- Albert Einstein

In the fields of observation, chance favours only the prepared mind.
- Louis Pasteur

Never accept the proposition that just because a solution satisfies a problem, that it must be the only solution.
- Raymond E. Feist

Not all those who wander are lost.
- J.R.R. Tolkien

In all affairs it's a healthy thing now and then to hang a question mark on the things you have long taken for granted.
- Bertrand Russell

No problem can withstand the assault of sustained thinking.
-Voltaire

Shaping the Next One Hundred Years: New Methods for Quantitative, Long-Term Policy Analysis
By Robert J. Lempert, Steven W. Popper, Steven C. Bankes
Copyright 2003