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The Rise of the Algorithmic Medium
Algorithms are the new medium between people and people, people and data, data and data.
Curated by Pierre Levy
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Rescooped by Pierre Levy from e-Xploration
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#Algorithmic culture. “Culture now has two audiences: people and machines" | #cyberculture

#Algorithmic culture. “Culture now has two audiences: people and machines" | #cyberculture | The Rise of the Algorithmic Medium | Scoop.it

“ A conversation with Ted Striphas”


Via Jessica Parland, nicolasthely, luiy
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luiy's curator insight, May 21, 6:37 AM

How will you define the “Culture of Algorithms”?


My preferred phrase is “algorithmic culture,” which I use in the first instance to refer to the the ways in which computers, running complex mathematical formulae, engage in what’s often considered to be the traditional work of culture: the sorting, classifying, and hierarchizing of people, places, objects, and ideas. The Google example from above illustrates the point, although it’s also the case elsewhere on the internet. Facebook engages in much the same work in determining which of your friends, and which of their posts, will appear prominently in your news feed. The same goes for shopping sites and video or music streaming services, when they offer you products based on the ones you (or someone purportedly like you) have already consumed.

 

What’s important to note, though, is the way in which algorithmic culture then feeds back to produce new habits of thought, conduct, and expression that likely wouldn’t exist in its absence—a culture of algorithms, as it were. The worry here, pointed out by Eli Pariser and others, is that this culture tends to reinforce more than it challenges one’s existing preferences or ways of doing things. This is what is often called “personalization,” though Pariser calls it a “you loop” instead. By the same token, it is possible for algorithmic systems to introduce you to cultural goods that you might not have encountered otherwise. Today, culture may only be as good as its algorithms.

Rescooped by Pierre Levy from e-Xploration
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#Facial Recognition #Analytics - When #Algorithms Grow Accustomed to Your Face

#Facial Recognition #Analytics - When #Algorithms Grow Accustomed to Your Face | The Rise of the Algorithmic Medium | Scoop.it
Companies are developing software to analyze our fleeting facial expressions and to get at the emotions behind them.

Via AnalyticsInnovations, luiy
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luiy's curator insight, December 1, 2013 9:30 AM

Ever since Darwin, scientists have systematically analyzed facial expressions, finding that many of them are universal. Humans are remarkably consistent in the way their noses wrinkle, say, or their eyebrows move as they experience certain emotions. People can be trained to note tiny changes in facial muscles, learning to distinguish common expressions by studying photographs and video. Now computers can be programmed to make those distinctions, too.

 

Companies in this field include Affectiva, based in Waltham, Mass., and Emotient, based in San Diego. Affectiva used webcams over two and a half years to accumulate and classify about 1.5 billion emotional reactions from people who gave permission to be recorded as they watched streaming video, said Rana el-Kaliouby, the company’s co-founder and chief science officer. These recordings served as a database to create the company’s face-reading software, which it will offer to mobile software developers starting in mid-January.

Robert McKenzie's curator insight, December 1, 2013 6:08 PM

This is an emerging field and complements some of the post GFC analytics . e.g. people who take less than 3 weeks leave in 1 stint are more likely to have breached policies...add to that facial and voice recognition. A UK university was looking at IR camera's in immigration based upon the hypothesis that 'untruth' caused greater brain activity that could be picked up on an IR camera as a trigger for deeper enquiry. Sentiment++

Ali Anani's curator insight, December 3, 2013 9:33 AM

Information from faces ans how to turn information into knowledge

Rescooped by Pierre Levy from Cyborgs_Transhumanism
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A Wikipedia for #robots allowing them to #share knowledge and experience worldwide | #algorithms

A Wikipedia for #robots allowing them to #share knowledge and experience worldwide | #algorithms | The Rise of the Algorithmic Medium | Scoop.it

European scientists from six institutes and two universities have developed an online platform where robots can learn new skills from each other worldwide — a kind of “Wikipedia for robots.” The objective is to help develop robots better at helping elders with caring and household tasks. “The problem right now is that robots are often developed specifically for one task”, says René van de Molengraft, TU/e researcher and RoboEarth project leader.

 

“RoboEarth simply lets robots learn new tasks and situations from each other. All their knowledge and experience are shared worldwide on a central, online database.” In addition, some computing and “thinking” tasks can be carried out by the system’s “cloud engine,” he said, “so the robot doesn’t need to have as much computing or battery power on‑board.”

 

For example, a robot can image a hospital room and upload the resulting map to RoboEarth. Another robot, which doesn’t know the room, can use that map on RoboEarth to locate a glass of water immediately, without having to search for it endlessly. In the same way a task like opening a box of pills can be shared on RoboEarth, so other robots can also do it without having to be programmed for that specific type of box.

 

RoboEarth is based on four years of research by a team of scientists from six European research institutes (TU/e, Philips, ETH Zürich, TU München and the universities of Zaragoza and Stuttgart).

 

 

Robots learn from each other on 'Wiki for robots'


Via Dr. Stefan Gruenwald, luiy
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