Knocking on Heaven's Door - Lisa Randall [100]
With the ear of a well-known scientist, an unknown might even be listened to right away. That is how Einstein could present a theory that shook scientific foundations almost immediately. The German physicist Max Planck understood the implications of Einstein’s relativistic insights and was fortuitously in charge of the most important physics journal at the time.
Today we benefit from the rapid spread of ideas over the Internet. Any physicist can write a paper and have it sent out through the physics archive the next day. When Luboš Motl was an undergraduate in the Czech Republic, he solved a scientific problem that a prominent scientist at Rutgers was working on. Tom Banks paid attention to good ideas, even if they came from an institution he had never heard of before. Not everyone is so receptive. But so long as a few people pay attention, an idea, if good and correct, will ultimately enter scientific discourse.
LHC engineers and physicists sacrificed time and money for safety. They wanted to economize as much as possible, but not at the expense of danger or inaccuracy. Everyone’s interests were aligned. No one benefits from a result that doesn’t stand the test of time.
The currency in science is reputation. There are no golden parachutes.
FORECASTING
I hope we all now agree that we shouldn‘t be worrying about black holes—though we do have much else to worry about. In the case of the LHC, we are and should be thinking about all the good things it can do. The particles created there will help us answer deep and fundamental questions about the underlying structure of matter.
To briefly return to my conversation with Nate Silver, I realized how special our situation is. In particle physics, we can restrict ourselves to simple enough systems to exploit the methodical manner in which new results build on old ones. Our predictions sometimes originate in models we know to be correct based on existing evidence. In other cases, we make predictions based on models we have reasons to believe might exist and use experiments to winnow down the possibilities. Even then—without yet knowing if these models will prove correct—we can anticipate what the experimental evidence would be, should the idea turn out to be realized in the world.
Particle physicists exploit our ability to separate according to scale. We know small-scale interactions can be very different from those that occur on large scales, but they nonetheless feed into large-scale interactions in a well-defined way, giving consistency with what we already know.
Forecasting is very different in almost all other cases. For complex systems, we often have to simultaneously address a range of scales. That can be true not only for social organizations, such as a bank in which an irresponsible trader could destabilize AIG and the economy, but even in other sciences. Predictions in those cases can have a great deal of variability.
For example, the goals of biology include predicting biological patterns and even animal and human behavior. But we don’t yet fully understand all the basic functional units or the higher-level organization by which elementary elements produce complex effects. We also don’t know all the feedback loops that threaten to make separating interactions by scale impossible. Scientists can make models, but without better understanding the critical underlying elements or how they contribute to emergent behavior, modelers face a quagmire of data and competing possibilities.
A further