Yes, and… [W.P. McNeill/Corner Cases]. Living by the “yes, and” ethos of improvisational comedy. Always build on what the other person said–stay open to their insight and direction. Be a pliable weed not a concrete pylon. Don’t get mired in dogma. I’m thinking this would work equally well in interactions with coworkers as with kids.
College has been oversold [Alex Tabarrok/Marginal Revolution]. The total number of students graduating from college is way up, but the numbers graduating with STEM degrees haven’t increased. That’s bad for individuals and bad for the economy. “An argument can be made for subsidizing students in fields with potentially large spillovers, such as microbiology, chemical engineering, nuclear physics and computer science. There is little justification for subsidizing sociology, dance and English majors.”
You have to break connections to get your ideas to spread [Tim Kastelle/Innovation Leadership Network. Innovation requires disruption. “When you come up with a great new idea, you need to think about this economic network in two ways. The first is: how can I connect to all of the complementary parts of the economy that are needed to get my idea to work? The second is: if I’m going to get my idea to spread, which of these existing connections need to be broken?”
The second economy [W. Brian Arthur/McKinsey Quarterly]. We are in the process of building out the economy’s neural system, what Arthur calls “the second economy” growing up alongside the first economy, the industrial economy. Downside: loss of jobs as computers take over.
Selecting amongst large classes of models [Brian D. Ripley] (pdf). We have the data and the computational resources to “trawl through literally thousands of models (and in some cases many more).” How to pick among them? A subject I intend to learn a lot more about in 2012.
Curing the big data storage fetish [Dan Woods/Forbes]. “One popular way to express lust for big data for its own sake is to create a gargantuan Hadoop cluster.” Not enough to just store the data, need to build a data-driven culture. “But how do you create a company culture like CapitalOne or Google or eBay or Zynga or LinkedIn, where data is essentially part of the management team? At all of these companies there are data scientists, the elite professionals, but there are also swarms of data enthusiasts, people who are eager to use data to help do their jobs better.”