Reinventing Discovery - Michael Nielsen [43]
On the same morning that all this begins, you notice another striking request on your list of top-ranked requests. It comes from a student in Bangalore, India, who wants some help learning about recent research on using computer algorithms to simulate complex quantum systems. They don’t know any local experts, and are learning from online papers, which they find confusing at some points. You’ve received the request because you’re an expert on such algorithms, and can easily answer the student’s questions. Furthermore, you’ve asked your system to alert you to a few student requests for assistance each week, tailored to areas where you have a special expertise. A rapid-fire exchange with the student ensues over the next couple of days, clearing up much of their confusion. Your work with the student is automatically noted in an archive of your scientific activity, along with statistics showing your contribution to public outreach.
A few other requests also show up in your list of top-ranked requests, but you decide you don’t have time to help out. Among these are several more collaboration requests broadly similar to that from the materials scientist, although differing in the details; a request for assistance from a local school; and a request for reading material from a student whose thesis topic overlaps with several of your old papers. All of these requests will be seen by tens or hundreds of other people, most of whom, like you, have a special expertise closely related to the requests. Response is voluntary, and none of the requests are directed only to you.
All this is made possible by a ranking algorithm that prioritizes the millions of requests for assistance made daily so that you see only the requests where you personally are likely to have the greatest interest and the greatest comparative advantage. The ranking algorithm takes into account your areas of expertise, what requests you’ve responded to in the past, the history of the people making the requests, and preferences such as your desire to help students. By judiciously selecting requests, you can maximize the impact of your work.
Around the world, similar patterns are being repeated millions of times over. A cognitive scientist in Ottawa is trying to replicate an experiment showing how a particular optical illusion can be suppressed by changing the color of some parts of the illusion. When she began work, she tried to figure out how to replicate the experiment just from a broad understanding of the original experiment. She made good progress, but occasionally got stuck, whereupon she consulted online videos showing the experiment being done in two other laboratories. That helped, but she’s still having trouble reproducing the results. After several days of being bogged down, last night she sent out a request for help, hoping to find someone with expertise both in optical illusions and in how the nervous system combines the color information coming from the different cones in the eye. This morning, she’s heard from a psychophysicist in Iowa, who’s sent along a modified color scheme, and some instructions on how to recalibrate the color scheme, if necessary. In short order she solves the problem, and the experiment is up and running.
Meanwhile, in a research lab in Shanghai, China, a biologist is working late at night, genetically sequencing a strain of the influenza virus. When he’s done with the sequencing, he queries online databases to compare the virus’s genetic makeup to all known viral strains. He discovers that this is, as he suspected, a new variation of influenza. Over the next