Saturday, June 25, 2011

How To Become A Better Human (P.S. Learning Involved)

Two great post's on Q3D (here and here), reviewing four different books:
"Newspapers today are filled with stories of genes for this and neurons for that. Recent examples range from “The Love-Cheat Gene: One in Four Born to be Unfaithful” to “Scientists Reveal Brain Cells Devoted to Jennifer Aniston”. Partly, the reductionist worldview is gaining in prevalence because many of its claims are true: evolutionary theory is now firmly established, our genome is being deciphered and there are indisputable correlations between consciousness and brain activity. But a problem arises when scientists, policymakers or the media adopt this biological perspective in the search for simple solutions to complex problems, blaming the credit crunch, for example, on short-termism inherited from our primate ancestors. Some thinkers are, therefore, rebelling against the reductionist consensus.

Of course, those with a strongly religious perspective often reject it outright. But even secular thinkers are increasingly resisting its claim to be the whole truth. Although some go too far in their attacks – arguing wrongly, for example, that we have next to nothing to learn about ourselves from our evolutionary history – such critics are, nonetheless, right to point out that in accepting the reductionist view, we risk doing ourselves a dangerous disservice.
All three books, different as they are, point to the same conclusion: that we need not allow ourselves to be reduced by these powerful new disciplines of genetics, neuroscience and computing. Instead, we can learn from them and assimilate them into a broader understanding of ourselves. We can, in fact, use them to become better at being human."
"Nowadays, of course, it’s common sense to distrust our common sense. A number of best-selling books have made us painfully aware of the biases that beset our everyday reasoning — we overrate the importance of recent events and overvalue objects because we happen to possess them, and so on. Watts turns his attention elsewhere: his primary aim is to debunk “methodological individualism,” the notion that “until one has succeeded in explaining some social phenomenon — the popularity of the Mona Lisa or the relation between interest rates and economic growth — exclusively in terms of the thoughts, actions and intentions of individual people, one has not fully succeeded in explaining it at all.

In such a world, can we really use common sense as a guide? No.
We need a kind of uncommon sense, Watts argues. And we’re in luck. If you had asked social scientists even 20 years ago what powers they dreamed of acquiring, they might have cited the capacity to inconspicuously track the behaviors, purchases, movements, interactions and thoughts of whole cities of people, in real time. Of course, this is exactly what is possible now that so many of us — via credit cards, cellphones, online social networks, blogs and so on — leave just such digital breadcrumbs as we move through our lives. Watts provides powerful examples, many taken from his own work in this new field of computational social science. One project tracked patterns of tweets and retweets among 1.6 million Twitter users. Another followed thousands of people as they judged which songs they wanted to download, and found that their individual tastes were easily trumped by small, and random, differences in a song’s perceived popularity among other people."

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