There is a nice article on Slate today about the demise of the bookseller Borders. The overall point is that, while the rise of Internet retailing created challenging circumstances for bricks and mortar bookstores, the real cause of Border’s demise was its own poor strategy. The article echoes one of the themes of the System Dynamics class that I taught at Sloan the past few years: there’s no such thing as side effects, there’s just effects. What we mean by this is that when a company (or a person, or any orgaization) takes an action, and something unintended or unforeseen happens, we tend to call these outcomes “side effects” as though we were somehow not responsible for them. But in the end, these so called side effects are still the consequences of our own actions. The only thing that distinguishes them is that we didn’t plan for them to happen. Recognizing and taking responsibility for these effects is a first step towards anticipating and preventing them.
Today and tomorrow I’m at the Interdisciplinary Workshop on Information and Decision in Social Networks at the MIT Laboratory for Information and Decision Systems (WIDS@LIDS). Nicholas Christakis gave a thought provoking talk this morning drawing on a lot of material from his book, Connected, written with James Fowler. One of the first ideas he raised is that humans are unique in having a social pressure on our evolution. Humans and other species also face environmental and other species evolutionary pressures. But, he argued that humans are unique in this social pressure because we live in close proximity and other human groups are one of the biggest threats that we face. He went on to say that possibly this unique social pressure is responsible for humans evolving intelligence, because in order to navigate the complexities of social interactions, we need substantial intelligence. I’m not sure that I buy this argument though. What about ants, bees, wolf packs, … ? All of these species work in groups, cooperate, and face competitive pressure from other groups, but none of them have evolved intelligence on a human scale.
Christakis ended his talk asking about why certain ideas are “sticky.” I think this is a super interesting and super difficult question. I’ve been talking with Adam Berinsky in the Political Science Department at MIT about this question in relation to political rumors. Why does the rumor that Obama was born in another country stick around, but other rumors die out? Christakis suggested that this might somehow be a tractable question, but I think it is much more subtle. First of all, there are no natural metrics for judging ideas. Second of all, we can’t just look at which ideas have actually taken off and which haven’t, because so many other chance factors come into play. Because of the big positive feedbacks involved in the spread of ideas, this process is highly susceptible to chance tipping (see the work by Salganik, Dodds, and Watts). It’s very east to fall into the trap that Duncan Watts sums up in the title of his recent book, Everything is Obvious Once You Know the Answer. Once an idea does “go viral,” like the Birther rumor, it is tempting to make up a narrative that says, well of course that rumor spread because it has attributes x, y, and z. But, if the rumor had died we could just as easily construct a different narrative explaining its failure. Paul Lazarsfeld’s paper on The American Soldier gives a fantastic example of how we can trick ourselves into believing this kind of after the fact rationalization.
Ars Technica has an article today about a crowdsourced clinical trial to evaluate the effectiveness of using lithium for treating ALS (Lou Gehrig’s Disease). Over 3500 patients participated in tracking their disease symptoms online and 150 of them were treated with the drug. The results showed no significant impact of the drug on ALS symptoms. The company that ran the study, PatientsLikeMe, was founded by three MIT engineers, and they published an article describing the trial in Nature Biotechnology.
From the press release:
“This is the first time a social network has been used to evaluate a treatment in a patient population in real time,” says ALS pioneer and PatientsLikeMe Co-Founder Jamie Heywood. “While not a replacement for the gold standard double blind clinical trial, our platform can provide supplementary data to support effective decision-making in medicine and discovery. Patients win when reliable data is made available, sooner.”