[more ...]
Good article in Slate on disparities in health care policy
blog for POLS 206 course at CLU
the lived experience of a place. That experience may be news, or it may simply be about that part of our lives that isn't news but creates the texture of our daily lives: our commute, where we eat, conversations with our neighbors, the irritations and delights of living in a particular place among particular people. However, when news happens in a community, placeblogs often cover those events in unique and nontraditional ways, and provide a community watercooler to discuss those events.
Google's tentacles are everywhere. It runs services for blogging, email, instant messaging, shopping and social networking. It offers a suite of word processing, spreadsheet and other tools to rival Microsoft's products in the workplace. It is building a software platform for mobile phones that may challenge Apple's iPhone and others. It has just launched Knol, a peer-reviewed encyclopedia to take on Wikipedia. In America, Google Health enables users to maintain their own medical records. The company is also working on language translation, speech recognition and video search.
They have amassed more information about people in 10 years than all the governments of the world put together. They make the Stasi and the KGB look like the innocent old granny next door. This is of immense significance. If someone evil took them over, they could easily become Big Brother.
It is true that Google doesn't force anyone to reveal anything. But to quote a book currently popular among politicians, its users are 'nudged' towards entering more and more information about themselves in exchange for personalised services. Google can save you time and money, find a restaurant to your taste or a chemist to cure your illness, but only if it knows you well enough. Help it to help you; that is the siren song... The goal is to enable Google users to be able to ask questions such as "What shall I do tomorrow?" and "What job should I take?" This is the most important aspect of Google's expansion.'
What the Net may be doing, I argue, is rewiring the neural circuitry of our brains in a way that diminishes our capacity for concentration, reflection, and contemplation.
Fast communication, powerful media and superficial skimming are all creations of our insatiable demand for information. We don't just want more, we need more. While we complain about the overload, we sign up for faster internet service, in-pocket email, unlimited talk-time and premium cable. In the mist of the flood, we are turning on all the taps.
We are now trying to comprehend the global village with minds that were designed to handle a patch of savanna and a close circle of friends. Our problem is not so much that we are stupider, but rather that the world is demanding that we become smarter.
To be limited to Twitter-sized discourse ultimately means that we will never really understand each other, because all of our minds are complex and in that way “cathedral-like.” It is extremely difficult to understand other people, unless you take a long time to study what they say. If we do not understand each other in our full and deep individual complexity, we will be invisible to each other, and ultimately incapable of real human society.
The idea that our minds should operate as high-speed data-processing machines is not only built into the workings of the Internet, it is the network’s reigning business model as well. The faster we surf across the Web—the more links we click and pages we view—the more opportunities Google and other companies gain to collect information about us and to feed us advertisements. Most of the proprietors of the commercial Internet have a financial stake in collecting the crumbs of data we leave behind as we flit from link to link—the more crumbs, the better. The last thing these companies want is to encourage leisurely reading or slow, concentrated thought. It’s in their economic interest to drive us to distraction.
It may turn out that tremendously large volumes of data are sufficient to skip the theory part in order to make a predicted observation. Google was one of the first to notice this. For instance, take Google's spell checker. When you misspell a word when googling, Google suggests the proper spelling. How does it know this? How does it predict the correctly spelled word? It is not because it has a theory of good spelling, or has mastered spelling rules. In fact Google knows nothing about spelling rules at all.This is no doubt true when it comes to Social Science where we are notoriously dreadful at prediction. It is not so true for explanation, science's other core purpose. Here's Bruce Sterling's amusing rejoinder to Kelly's
Instead Google operates a very large dataset of observations which show that for any given spelling of a word, x number of people say "yes" when asked if they meant to spell word "y. " Google's spelling engine consists entirely of these datapoints, rather than any notion of what correct English spelling is. That is why the same system can correct spelling in any language.
In fact, Google uses the same philosophy of learning via massive data for their translation programs. They can translate from English to French, or German to Chinese by matching up huge datasets of humanly translated material. For instance, Google trained their French/English translation engine by feeding it Canadian documents which are often released in both English and French versions. The Googlers have no theory of language, especially of French, no AI translator. Instead they have zillions of datapoints which in aggregate link "this to that" from one language to another.
Once you have such a translation system tweaked, it can translate from any language to another. And the translation is pretty good. Not expert level, but enough to give you the gist. You can take a Chinese web page and at least get a sense of what it means in English. Yet, as Peter Norvig, head of research at Google, once boasted to me, "Not one person who worked on the Chinese translator spoke Chinese. " There was no theory of Chinese, no understanding. Just data. (If anyone ever wanted a disproof of Searle's riddle of the Chinese Room, here it is. )
Surely there are other low-hanging fruit that petabytes could fruitfully harvest before aspiring to the remote, frail, towering limbs of science. (Another metaphor—I'm rolling here. )
For instance: political ideology. Everyone knows that ideology is closely akin to advertising. So why don't we have zillionics establish our political beliefs, based on some large-scale, statistically verifiable associations with other phenomena, like, say, our skin color or the place of our birth?
The practice of law. Why argue cases logically, attempting to determine the facts, guilt or innocence? Just drop the entire legal load of all known casework into the petabyte hopper, and let algorithms sift out the results of the trial. Then we can "hang all the lawyers, " as Shakespeare said. (Not a metaphor. )
Love and marriage. I can't understand why people still insist on marrying childhood playmates when a swift petabyte search of billions of potential mates worldwide is demonstrably cheaper and more effective.
Investment. Quanting the stock market has got to be job one for petabyte tech. No human being knows how the market moves—it's all "triple witching hour, " it's mere, low, dirty superstition. Yet surely petabyte owners can mechanically out-guess the (only apparent) chaos of the markets, becoming ultra-super-moguls. Then they simply buy all of science and do whatever they like with it. The skeptics won't be laughing then.
There is now a better way. Petabytes allow us to say: "Correlation is enough." We can stop looking for models. We can analyze the data without hypotheses about what it might show. We can throw the numbers into the biggest computing clusters the world has ever seen and let statistical algorithms find patterns where science cannot.
Regradless of how much we let mathematical and staistical modeling dominate the social sciences, they are unlikely to become scientific in the natural sciences sense. This is so because the phenomena modelled are social, and thus "answer back" in ways natural phenomena do not.
We thought people might talk about what happened at some fraternity party last weekend, or to rank sororities. That sort of thing," he insists. "And if you look, you'll definitely find those fun stories. And then there's a bunch more stuff that we didn't realize people would use the site for.
promiscuity, drug abuse, plastic surgery, homosexuality, rape, and eating disorders, along with enough racist, anti-Semitic, and misogynistic invective to make David Duke blanch—that seems to generate the majority of the page views.
Attempts by statistical researchers to 'control for third variables'... ignore the ontological embeddedness of locatedness of entities within actual situation contexts." (Emirbayer 1997, 289).This is true, but then the question remains, how do you validly and reliably study identity in the political process. One interesting approach might be to employ folksonomies to race questions in political science. Rather than asking people to classify themselves according to the controlled vocabulary of the survey researcher, a folksonomy would allow the respondent to use as many self-identifiers they want to describe themselves. You can use social network analysis to group respondents based on the similarity of their self-tagging structures into clusters and then test whether cluster membership is related to a desired political outcome.
he built a Web site that features hundreds of pages of material intended to undermine Obama. "If 20 percent of what's on my Web site is true, this guy is a clear and present danger," Beckwith said. (He later added, "I try very hard to be accurate.") But while
Beckwith speaks with pride about his research -- much of which he credits to an unnamed "colleague" in Europe -- and to his extensive Obama files, he rejects outright the suggestion that he authored the chain e-mail. "I've never been involved with any
e-mailings. Period," he said.
A first group of people published articles that created the basis for the attack. A second group recirculated the claims from those articles without ever having been asked to do so. "No one coordinates the roles," Allen said. Instead the participants swim toward their goal like a school of fish -- moving on their own, but also in unison.What are the implication of this type of "wildfire" politics? it doesn't take much to influence low information voters. Can an uncoordinated response be addressed by a coordinated campaign like the Obama campaign is currently attempting? I'm skeptical that any intentional effort can stop this type of uncoordinated effort. It might be the perfect storm of elements has combined to make Obama president, but this is a curious side battle he has to wage.
Statewide, Michigan is about 78 percent white, 14 percent Black, 4 percent Latino and 2 percent Asian, with most people of color concentrated in a handful of urban areas. For example, while Wayne County, home of Detroit, is less than 50 percent white, a handful of other counties are nearly 98 percent white. Wayne County was one of only three counties where a majority voted against Proposal 2. The other two, Washtenaw and Ingham, include the state’s two largest universities and have among the state’s most diverse communities. In general, across the rest of Michigan, the whiter the county, the higher the support for the ban.Interestingly, support for the anti-Affirmative Action measure was not correlated with county unemployment rates, a proxy for income levels.
It seems clear to me that the Web, in this case Foreign Policy's online poll, taps into the need of a certain subset of a entho-religious group to re-frame the way they are perceived by "the rest" of the world community. Then again, educated, upwardly mobile Muslims might just, on average, be more avid readers of Foreign Policy?No one spread the word as effectively as the man who tops the list. In early May, the Top 100 list was mentioned on the front page of Zaman, a Turkish daily newspaper closely aligned with Islamic scholar Fethullah Gülen. Within hours, votes in his favor began to pour in. His supporters—typically educated, upwardly mobile Muslims—were eager to cast ballots not only for their champion but for other Muslims in the Top 100. Thanks to this groundswell, the top 10 public intellectuals in this year’s reader poll are all Muslim. The ideas for which they are known, particularly concerning Islam, differ significantly. It’s clear that, in this case, identity politics carried the day.