The Relevance of Algorithms // Culture Digitally

I’m really excited to share my new essay, “The Relevance of Algorithms,” with those of you who are interested in such things. It’s been a treat to get to think through the issues surrounding algorithms and their place in public culture and knowledge, with some of the  participants in Culture Digitally (here’s the full litany: Braun, Gillespie, Striphas, Thomas, the third CD podcast, and Anderson‘s post just last week), as well as with panelists and attendees at the recent 4S and AoIR conferences, with colleagues at Microsoft Research, and with all of you who are gravitating towards these issues in their scholarship right now.

The motivation of the essay was two-fold: first, in my research on online platforms and their efforts to manage what they deem to be “bad content,” I’m finding an emerging array of algorithmic techniques being deployed: for either locating and removing sex, violence, and other offenses, or (more troublingly) for quietly choreographing some users away from questionable materials while keeping it available for others. Second, I’ve been helping to shepherd along this anthology, and wanted my contribution to be in the spirit of the its aims: to take one step back from my research to articulate an emerging issue of concern or theoretical insight that (I hope) will be of value to my colleagues in communication, sociology, science & technology studies, and information science.

The anthology will ideally be out in Fall 2013. And we’re still finalizing the subtitle. So here’s the best citation I have.

Read the full essay by ,  Cornell University Department of Communication

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“We especially need imagination in science. It is not all mathematics, nor all logic, but is somewhat beauty and poetry.”

Astronomer Maria Mitchell (1818-1889), the first woman elected to the American Academy of Arts and Sciences.

Also see Robert Sapolsky on science and wonder and Richard Feynman on the cultural role of science.

(↬ It’s Okay To Be Smart)

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Mining of Raw Data May Bring New Productivity, a Study Says - NYTimes.com

Math majors, rejoice. Businesses are going to need tens of thousands of you in the coming years as companies grapple with a growing mountain of data.

Data is a vital raw material of the information economy, much as coal and iron ore were in the Industrial Revolution. But the business world is just beginning to learn how to process it all.

The current data surge is coming from sophisticated computer tracking of shipments, sales, suppliers and customers, as well as e-mail, Web traffic and social network comments. The quantity of business data doubles every 1.2 years, by one estimate.

Mining and analyzing these big new data sets can open the door to a new wave of innovation, accelerating productivity and economic growth. Some economists, academics and business executives see an opportunity to move beyond the payoff of the first stage of the Internet, which combined computing and low-cost communications to automate all kinds of commercial transactions.

The next stage, they say, will exploit Internet-scale data sets to discover new businesses and predict consumer behavior and market shifts.

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NJIT professor uses math analytics to project 2011 Major League Baseball winners

Philadelphia Phillies, St. Louis Cardinals and San Francisco Giants should win their divisions, while the Atlanta Braves will take the wild card slot in the National League (NL), according to NJIT’s baseball guru Bruce Bukiet. For over a decade, Bukiet, an associate professor and associate dean, has applied mathematical analysis to compute winning games for each Major League Baseball Team.

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future of technology: Future of analytics

futureoftech:

IOD Keynote: Computational Mathematics and Freakonomics

I attended the keynote this morning, on the theme of looking forward: first we heard from Mike Rhodin, an exec in the IBM Software group, then Brenda Dietrich, a mathematician (and VP – finally, a female IBM exec on stage) from the…

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downtowncreator: via upload.wikimedia.org Clouds are not spheres, mountains are not cones, coastlines are not circles, and bark is not smooth, nor does lightning travel in a straight line.   —Benoît Mandelbrot, (1924-2010) in his introduction to The Fractal Geometry of Nature.

downtowncreator:

via upload.wikimedia.org

Clouds are not spheres, mountains are not cones, coastlines are not circles, and bark is not smooth, nor does lightning travel in a straight line.
  —Benoît Mandelbrot, (1924-2010) in his introduction to The Fractal Geometry of Nature.

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First Habitable Exoplanet Could Be Discovered by May |  Wired.com A new mathematical analysis predicts the first truly habitable exoplanet will show itself by early May 2011. Well, more or less. “There is some wiggle room,” said Samuel Arbesman of the Harvard Institute for Quantitative Social Science, lead author of a new paper posted online and to be published in PLoS ONE October 4. His calculations predict a 50 percent probability that the first habitable exoplanet will be discovered in May 2011, a 66 percent chance by the end of 2013 and 75 percent chance by 2020.

First Habitable Exoplanet Could Be Discovered by May |  Wired.com

A new mathematical analysis predicts the first truly habitable exoplanet will show itself by early May 2011.

Well, more or less. “There is some wiggle room,” said Samuel Arbesman of the Harvard Institute for Quantitative Social Science, lead author of a new paper posted online and to be published in PLoS ONE October 4. His calculations predict a 50 percent probability that the first habitable exoplanet will be discovered in May 2011, a 66 percent chance by the end of 2013 and 75 percent chance by 2020.


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TOKYO - 08 Jul 2009: IBM today announced the launch of its Tokyo-based IBM Analytics Solution center which is part of a recently announced global network of analytics focused centers. Through these centers, IBM is addressing the growing demand for advanced analytics capabilities need to help clients build smarter business systems and drive improved decision-making.

The new center is co-located at IBM’s Marunouchi office in Tokyo as well as at IBM’s Yamato Lab in Kanagawa Prefecture. It will draw on a wealth of global IBM expertise, including more than 150 mathematicians and software engineers at IBM Research - Tokyo and Yamato Software Development Laboratory to help companies turn data into predictive intelligence.

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IBM Launches Advanced Analytics Center in Tokyo

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“Our focus on algorithms is in the following topics: data stream algorithms, nearest-neighbor seach and embeddings of metric spaces, peer-to-peer networks, aggregation algorithms, and approximation algorithms.”

IBM Research | Almaden Research Center | Computer Science

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