Alex Soojung-Kim Pang, Ph.D.

I study people, technology, and the worlds they make

Tag: science (page 1 of 2)

Chocolate and “likes” activate the same parts of the teenage brain

The same brain circuits that are activated by eating chocolate and winning money are activated when teenagers see large numbers of “likes” on their own photos or the photos of peers in a social network, according to a first-of-its-kind UCLA study that scanned teens’ brains while using social media.

The 32 teenagers, ages 13-18, were told they were participating in a small social network similar to the popular photo-sharing app, Instagram. In an experiment at UCLA’s Ahmanson-Lovelace Brain Mapping Center, the researchers showed them 148 photographs on a computer screen for 12 minutes, including 40 photos that each teenager submitted, and analyzed their brain activity using functional magnetic resonance imaging, or fMRI. Each photo also displayed the number of likes it had supposedly received from other teenage participants — in reality, the number of likes was assigned by the researchers. (At the end of the procedure, the participants were told that the researchers decided on the number of likes a photo received.)

“When the teens saw their own photos with a large number of likes, we saw activity across a wide variety of regions in the brain,” said lead author Lauren Sherman, a researcher in the brain mapping center and the UCLA branch of the Children’s Digital Media Center, Los Angeles.

Source: Teenage brain on social media: Study sheds light on influence of peers and much more — ScienceDaily

Amateur astronomer discovers four exoplanets

An English gas worker, who downloaded astronomical data from the Exoplanet Orbit Database and combed through it in his free time, has been recognized as the discoverer of four exoplanets:

Peter Jalowiczor has just helped discover a planet around which it [extraterrestrial life] may exist.

Quite a claim for a Rotherham gas worker who has never owned a telescope in his life – but a claim which has been confirmed by a team of astronomical experts from the University of California.

For Peter, of Masbrough, has been named by the centre’s Lick-Carnegie Planet Search Team as a co-discoverer of four planets known as HD 31253b, HD 218566b, HD177830c and HD 99492c.

It was the hours he spent analysing thousands of figures of space data – all in his spare time, all on his two home PCs – which provided the clues for scientists to establish the existence of the huge gaseous orbs….

[I]n 2005, astronomers at the university released millions of space measurements collected over several decades and asked enthusiasts to make of them what they would.

Quirks in the data could signify the existence of exoplanets – that is, planets in other solar systems which cannot be seen with even the most powerful telescope because they are so far away. From March 2007 Peter, 45, spent entire nights reading the data, working the figures, creating graphs…. “Essentially you’re looking for measurements which show a star, which is millions of miles across and light years away, to be oscillating by about 50 metres or less…. The measurements are so tiny, it puts many people off looking – even professional astronomers – but I find it fascinating.”

Rack up another discovery for citizen science!

Busy week

This has turned into a rather busy week: in addition to scheduling several interviews for a new project, I’ve been dealing with the last edits to my long-developing piece on cubesats, which appears headed for the February issue of Scientific American. Incredible.

Edits to the cubesats article
working on the edits, via flickr

I’ve had a great time working with my co-author (I need to collaborate on more articles– it really is a good experience), but still it’ll be really nice to have that piece out. I suspect there could be an interesting short book in here.

I recently had an epiphany about writing. My academic training hammered into me the idea that ideas need time to mature, that more time in the tumbler of your mind would only improve the brilliance your argument, and that books should be long and take years and years to write. In order to guarantee that your work is well-regarded and stands the test of time, you need to write carefully and deliberately.

But what if that’s backward in an important respect? What if importance and timelessness– that elusive quality that gives ideas a life far beyond the author’s– aren’t things that authors can really control, but are constructed almost entirely after the fact, but readers and reviewers and respondents?

This morning's coffee
coffee at Cafe Zoë, via flickr

That suggests that you should write a lot, in order to give your ideas a better chance of surviving the Darwinian competition between ideas: like salmon, only a few will make it to adulthood, so your strategy should be one of fruitfulness rather than intentional profundity. You should get books out quickly while the ideas are still timely– and thus, ironically, make them more likely to be regarded by readers and critics as timeless. Put out the best work possible in Prolific Mode rather than Thorough Mode, and just accept that only some of it will survive.

I don’t know if I can actually pull that off, and I know lots of writers will consider this completely pedestrian an insight, but I think it’s worth a try.

[To the tune of Tzimon Barto, “Preludes: Prelude No. 8 in F sharp minor (Molto agitato),” from the album Chopin: Preludes & Nocturnes (a ^r-star song, imo).]

Review of Steven Johnson, “Where Good Ideas Comes From”

My review of Steven Johnson's new book, Where Good Ideas Come From: The Natural History of Innovation, is now available on the Los Angeles Times Web site. (Interestingly they publish some of the reviews online first, then publish them in the newspaper.)

More at Contemplative Computing.

Update 9 December 2011: Here's the full text of the review:

The author explores the history of innovation, which is firmly rooted in collective efforts and learning things the hard way.

Steven Johnson's "Where Good Ideas Come From: The Natural History of Innovation" is misnamed. Natural history was pioneered by 18th century naturalist Gilbert White, and its blend of scientific fieldwork, travel writing, physical geography and anthropology was meant to convey the majesty and intricate interdependency of God's creation. The time-traveling Johnson overshot his mark by a couple of centuries. "Where Good Ideas Come From" reveals hidden relationships between disparate realms, decodes ancient mysteries, argues that we all have untapped powers and shows how to turn everyday materials into valuable ones. In short, it's a Renaissance alchemical guide.

Granted, the everyday materials Johnson writes about in his fluid, accessible book are not lead or dross, but people, places and very tiny animals. But today's alchemist wouldn't be interested in materials. Recently, Facebook was estimated to be worth about $33 billion, and gold was selling for nearly $1,400 an ounce; that means the social networking company was worth more than 700 tons of gold. We live in a world in which Farmville is worth a lot more than Sutter's Mill.

So what's the philosopher's stone for creativity, the elixir for making innovative places?

A "series of shared properties and patterns recur again and again in unusually fertile environments," Johnson argues, be they companies, cities or coral reefs. Good ideas, whether expressed as patents or paintings or DNA, flourish in liquid networks stocked with old ideas and physical resources that can be cannibalized, recycled and repurposed. Liquid networks give creative groups the chance to explore the "adjacent possible," the new functions or capabilities opened up by incremental innovations; discover new uses for old ideas; and explore potentially fruitful errors.

Finally, they serve as a proving ground for ideas, making it easier to experiment, fail quickly and cheaply and iterate faster. (Maddeningly, though, it's not clear how liquid networks select good ideas. In nature, species thrive when they fit their environments; but good ideas aren't inherently good — they can be counterintuitive and perverse — and "Where Good Ideas Come From" never quite explains whether markets are better than patrons, or tastemakers better than crowds, at identifying them.)

What emerges is a vision of innovation and ideas that is resolutely social, dynamic and material. Despite its trendiness, Johnson's perspective is at times wonderfully, subtly contrarian. Ideas don't spring from the minds of solitary, Galtian geniuses: They may start with smart people, but they're refined, extended and finished by creative cultures that are shaped by their physical environments.

But good ideas also don't emerge magically from crowdsourcing and promiscuous networking; they're slow hunches that "fade into view" during years of reflection, tinkering and exploring dead ends. Creative ferment may be accelerated by the Internet, but place still matters. And innovation is driven much less by competition than by obvious and subtle forms of cooperation: Even the most radical- looking invention builds on old ideas and recycled parts.

Like all of Johnson's books, "Where Good Ideas Comes From" is fluidly written, entertaining and smart without being arcane. But is it any more successful than Renaissance recipes for turning lead into gold? "The more we embrace these patterns" in innovative spaces, Johnson says, "the better we will be at tapping our extraordinary capacity for innovative thinking."

I'm not sure it's that easy. Fish might not mind artificial reefs, but humans sure seem to. Efforts to create innovative spaces still yield results that feel like computer animations: bright, sharp and unreal. For example, Frank Gehry designed the Stata Center at MIT to encourage serendipitous connection and intellectual cross-fertilization among computer scientists.

But people are most innovative when they make their own creative spaces and connections, not inhabit someone else's. It's hard to do the kind of appropriation and reinvention of space that supports real innovation when you're working in a building that reflects a creative vision as distinctive as Gehry's.

The surrounding Cambridge neighborhood, on the other hand, is a bricolage of old houses, small factories and warehouses set on streets blazed by cows in the 1600s. It's flexible and can be repurposed endlessly — and it works brilliantly.

In other words, Cambridge (like Hollywood or Silicon Valley) is itself a good idea, the product of serendipitous connections, slow hunches and rich trial and error. If this is so, then creative environments can only be described, not designed. For all its promise to reveal the elixir of innovation, maybe "Where Good Ideas Come From" is a natural history after all.

If evolution is outlawed only outlaws will evolve

Love it!


(h/t to Heather)

[To the tune of Foo Fighters, “Alone+Easy Target,” from the album Foo Fighters (a 1-star song, imo).]

California deploys its own greenhouse gas monitoring network

I wish Signtific were still around, so I could say about this there, but… The California Report has a piece today (here’s the audio) about the state’s deployment of a network of greenhouse gas monitoring instruments that will provide high-resolution maps of GHG sources.

Similar equipment has been in place for years as part of a continental network established by the National Oceanic & Atmospheric Administration (NOAA). But officials at the California Air Resources Board (CARB) say this new system will be the first of its kind.

“The unique thing about this is that we’re actually looking at the local emissions, rather than the global average, says Jorn Herner, who heads the Greenhouse Gas Technology & Field Testing Section of CARB’s research arm. “Nobody has done that before.”

As the New York Times explains, while this is mainly a science project at the present, the virtually same technologies and networks would be useful in “the kind of system that may be needed in many places as countries develop plans to limit their emissions of greenhouse gases.” Right now, such markets rely largely on either proxy data (i.e., measurements of things that indirectly indicate a rise or fall in GHG emissions) or self-reported data, which depend entirely on the accuracy and honesty of the reporter.

Indeed, Picarro, the Silicon Valley company making the instruments that CARB is putting in the field, says that a national GHG sensing network with 10 km resolution would cost about $300 million– not a huge amount of money given the potential size of the cap and trade market, and the potential for fraud in the absence of a robust data-gathering system. (Picarro itself is an interesting example of a Silicon Valley company that’s reinventing itself as cleantech: according to Green Beat, “a spinout from a Stanford University lab, Picarro initially developed lasers for the telecom industry,” but recently “has redefined itself to ride the climate change momentum.”)

[To the tune of They Might Be Giants, “Meet The Elements,” from the album Here Comes Science (a 2-star song, imo).]

Op-ed on citizen science

Darlene Cavalier (aka the Science Cheerleader) and I have a short op-ed on citizen science in the latest (Autumn 2009) issue of the New York Academy of Sciences Magazine.

Yale University astrophysics professor Kevin Schawinski studies how galaxies form. But his most valuable tool isn’t a telescope or arcane theory. It’s Galaxy Zoo, a project that has enlisted the help of more than 150,000 “citizen scientists” to classify a million galaxies.

Why use people rather than computers for such an undertaking? At least for now, humans with a little training are more accurate than expensive software. And when you have a million galaxies to classify, you want all the help you can get.

Not so long ago, “citizen scientist” would have seemed to be a contradiction in terms. Science is traditionally something done by people in lab coats who hold PhDs. As with classical music or acting, amateurs might be able to appreciate science, but they could not contribute to it. Today, however, enabled by technology and empowered by social change, science-interested laypeople are transforming the way science gets done.

[To the tune of Dixie Chicks, “If I Fall You’re Going Down With Me,” from the album Top of the World Tour- Live (I give it 3 stars).]

Scientific databases as tacit knowledge

I'm supposed to be taking some of the summer off, finishing the book and a couple articles, but like Michael Corleone in The Godfather, every time I think I'm out they pull me back in. I was at the first day of SciBarCamp today, playing local host / fixer / keeping an eye on the furniture. Sean Mooney (who in addition to being a former professor at Indiana University, was a World Wrestling Federation announcer) gave a very interesting talk about current challenges in bioinformatics.

A fair amount of Sean's talk dealt with the technical challenges of creating federated databases, the differing demands of bench scientists and funders– the former want tools for managing and analyzing data in today's problems, while the latter want to attack Big Questions– and the issues involved in getting people to share their data. The issues aren't so much philosophical or competitive, but practical: people believe in sharing data, and once they're done with it are generally willing to share so long as it doesn't put a burden on them.

But as Sean was talking about how different labs used different procedures for similar experiments, and how those differences manifested themselves in the ways they produced and consumed data (at least, this is what I took away from his talk– he might have meant something complete different), a thought came to me. Projects intended to let scientists assume that data can be converted into something like the reagents or instruments labs buy from suppliers– a commodity that you don't have to think about, you just use. But what if data can't be black-boxed this way? Or, more specifically, what if only really uninteresting data– the kind that everyone understands very well, the kind that's solidly in the realm of normal science– can be cleaned up, repackaged, commodified and standardized, and put online into generally-usable databases?

On one hand, this idea might seem stupid. After all, science is science: data is data, and facts about nature are true no matter where they're created. That makes them scientific. On the other hand, if you buy the argument of people like Harry Collins, scientific research is as much a craft as a– well, a science. Databases tend to reflect the specific, local interests of researchers, working on particular problems. This tends to work against the generalizability of data: the more it's a product of craft, and an object tailored to a particular job, the harder it'll be to make it useful to other people.

So depending on how much databases are expressions of craftwork and problem-solving and bricolage, and how much they reflect a timeless, placeless crystallization of nature's order, they're going to be less or more easily poured into big projects to reuse data.

It’s not just for dinner any more

From the New Scientist:

A cloned beagle named Ruppy – short for Ruby Puppy – is the world’s first transgenic dog. She and four other beagles all produce a fluorescent protein that glows red under ultraviolet light.

A team led by Byeong-Chun Lee of Seoul National University in South Korea created the dogs by cloning fibroblast cells that express a red fluorescent gene produced by sea anemones.

This new proof-of-principle experiment should open the door for transgenic dog models of human disease, says team member CheMyong Ko of the University of Kentucky in Lexington. “The next step for us is to generate a true disease model,” he says.

And I know the title’s completely tasteless. Without a good garlic sauce, anyway.

Post-scientific society

I’ve been in Malaysia and Singapore this week, conducting workshops on the future of science and innovation. It’s been a very interesting week, talking to scientists in Penang and Kuala Lumpur about the future of science, and what role they see Malaysia playing in that future. The people I’ve been talking to are pretty convinced that Malaysia, which has a respectable but not world-class scientific community, can evolve into a global player in science in the next couple decades. They don’t want to emulate American and European institutions: you won’t see multi-billion dollar particle accelerators here any time soon. But they’re pretty aware that cloud computing, cheap genomics, and other inexpensive research tools will lower the economic bars to develop world-class competence in some important fields.

So I was especially struck by Gregg Zachary’s latest column in the New York Times, which asks, “might cheap science from low-wage countries help keep American innovators humming?” At least a few policy analysts and scholars studying global trends in science think that the United States can profit from the growth of scientific excellence in the developing world.

Americans have long profited from low-cost manufactured goods, especially from Asia. The cost of those material “inputs” is now rising. But because of growing numbers of scientists in China, India and other lower-wage countries, “the cost of producing a new scientific discovery is dropping around the world,” says Christopher T. Hill, a professor of public policy and technology at George Mason University.

American innovators — with their world-class strengths in product design, marketing and finance — may have a historic opportunity to convert the scientific know-how from abroad into market gains and profits. Mr. Hill views the transition to “the postscientific society” as an unrecognized bonus for American creators of new products and services.

Mr. Hill’s insight, which he first described in a National Academy of Sciences journal article last fall, runs counter to the notion that the United States fails to educate enough of its own scientists and that “shortages” of them hamper American competitiveness.

The opposite may actually be true. By tapping relatively low-cost scientists around the world, American innovators may actually strengthen their market positions….

Precisely because the gap between basic science and commercial innovations is large, Mr. Hill’s postscientific society makes sense to innovators on the front lines. One implication for the future is that the United States “won’t have to import so many scientists,” says Stephen D. Nelson, associate director of policy programs at the American Association for the Advancement of Science.

The association, which for decades has generally favored policies to expand the ranks of American scientists, is devoting a portion of its annual policy seminar next month to talk about the “postscience” situation.

Industry, meanwhile, is adapting to a world where scientific goods can come from anywhere — and fewer scientists work on abstract problems unrelated to the market. “It is no accident that many corporate labs have fallen apart,” Sean M. Maloney, executive vice president of Intel, says. “They were science farms looking for problems.”

What is this post-scientific society that Hill writes about? As he explains it,

A post-scientific society will have several key characteristics, the most important of which is that innovation leading to wealth generation and productivity growth will be based principally not on world leadership in fundamental research in the natural sciences and engineering, but on world-leading mastery of the creative powers of, and the basic sciences of, individual human beings, their societies, and their cultures.

Just as the post-industrial society continues to require the products of agriculture and manufacturing for its effective functioning, so too will the post-scientific society continue to require the results of advanced scientific and engineering research. Nevertheless, the leading edge of innovation in the post-scientific society, whether for business, industrial, consumer, or public purposes, will move from the workshop, the laboratory, and the office to the studio, the think tank, the atelier, and cyberspace.

There are growing indications that new innovation-based wealth in the United States is arising from something other than organized research in science and engineering. Companies based on radical innovations, exemplified by network firms such as Google, YouTube, eBay, and Yahoo, create billions in new wealth with only modest contributions from industrial research as it has traditionally been understood. Huge and successful firms like Wal-Mart, FedEx, Dell, Amazon.com, and Cisco have grown to be among the largest in the world, not as much by mastering the intricacies of physics, chemistry, or molecular biology as by structuring human work and organizational practices in radical new ways. The new ideas and concepts that support these post-scientific society companies are every bit as subtle and important as the fundamental natural science and engineering research findings that supported the growth of firms such as General Motors, DuPont, and General Electric in the past half century. But innovation in these two generations of firms is fundamentally different.

The piece is well worth reading, as it has a number of provocative implications for science policy, innovation policy, and education. Essentially, Hill is arguing that a decline in America’s monopoly on science– even if that does happen– is not to be lamented any more than the shrinking of the agricultural workforce: it doesn’t reflect a weakness, but a more fundamental shift to a different kind of economy, in which the sources of value aren’t facts, but what you do with them.

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