An international CONFERENCE, a scholarly JOURNAL, a BOOK series, and an online KNOWLEDGE COMMUNITY
![[rss]](http://techandsoc.com/wp-content/themes/k2_1.0.3/images/feed.png)
Edited by Phillip Kalantzis-Cope and Karim Gherab-Martin
Analyzing the relationship between digital technologies and society, this book explores a wide range of complex social issues emerging in a new digital space. It examines both the vexing dilemmmas with a critical eye as well as prompting readers to think constructively and strategically about exciting possibilities.
Please join us at the Epelde & Mardaras Gallery to enjoy a traditional Basque Country Dinner. The menu includes Mussels in Basque Sauce, Fish Soup, Tenderloin with Peppers, and Basque Flan. Vegetarian options are available.
For more information please visit our web-site.
From Mad Science
Almost two millennia before the rest of humanity entered the industrial age, the Greek inventor Hero invented the steam engine, wind-powered machinery, and theories of light that couldn’t be improved for centuries. And then he invented some really crazy stuff.
Scientific geniuses have to pull off a tricky balancing act before they’re even born. Great minds like Albert Einstein or Isaac Newton were born at precisely the right time for their ideas to be really revolutionary – just far enough ahead of their time to be trailblazers, but not so far ahead that people had no idea what they were talking about.
Hero of Alexandria
Hero, or Heron, of Alexandria, on the other hand, had the astonishing bad taste to be born around 10 CE, which made his inventions so far ahead of their time that they could be of little practical use and, in time, were forgotten. If he had been born in, say, 1710, his engineering prowess and incredible creativity might have made him the richest person in the world. As it is, he’ll just have to settle for the posthumous reputation of being the greatest inventor in human history. Seriously, unless you invent a warp drive tomorrow, there’s no way you’re catching up to Hero.
We know precious little about where Hero came from, and it’s only in the last century that we actually became certain which century he lived in. The best guess is that he was an ethnic Greek born in Egypt in the early decades of the first century CE, one of the many people whose ancestors had emigrated from Greece after the conquests of Alexander the Great.
From Sam Grobart, The New York Times
Steve Jobs’s announcement on Jan. 17 that he would take his second medical leave from Apple in three years raised questions about how Apple would fare without its chief executive. A look at Apple’s products shows what effect Mr. Jobs has had on the company. Sam Grobart, The Times’s personal technology editor, provides audio commentary.
From Jon Udell in his blog Strategies for Internet Citizens:
Back in 2000, the patterns, principles, and best practices for building web information systems were mostly anecdotal and folkloric. Roy Fielding’s dissertation on the web’s deep architecture provided a formal definition that we’ve been digesting ever since. In his introduction he wrote that the web is “an Internet-scale distributed hypermedia system” that aims to “interconnect information networks across organizational boundaries.” His thesis helped us recognize and apply such principles as universal naming, linking, loose coupling, and disciplined resource design. These are not only engineering concerns. Nowadays they matter to everyone. Why? Because the web is a hybrid information system co-created by people and machines. Sometimes computers publish our data for us, and sometimes we publish it directly. Sometimes machines subscribe to what machines and people publish, sometimes people do.
Given the web’s hybrid nature, how to can we teach people to make best use of this distributed hypermedia system? That’s what I’ve been trying to do, in one way or another, for many years. It’s been a challenge to label and describe the principles I want people to learn and apply. I’ve used the terms computational thinking, Fourth R principles, and most recently Mark Surman’s evocative thinking like the web.
From The Economist
Management gurus are always discovering the next big thing (and source of income). Last year it was emerging markets and “frugal innovation”. This year it is “the internet of things”, or, as it has rapidly become “the internet of everything”.
Over the past decade billions of people have hooked themselves up to the internet via the computer and, more recently, mobile devices. This communication revolution is now extending to objects as well as people. Imagine if all the objects in the world had all the information that they needed to function optimally. Buildings would adjust themselves according to the temperature. Ovens would cook things for exactly the right time. The handles of umbrellas would glow when it was about to rain. We long ago inserted “intelligence” into objects in the form of thermostats and the like; the internet of everything will extend this principle exponentially, giving us unprecedented control over the objects that surround us.
The internet of everything will help solve two of the biggest problems facing the world: energy and health care. Buildings currently waste more energy than they use effectively. We will be able to cut this waste down to almost nothing. Health care is currently delivered in lumps: we visit the doctor a couple of times a year at most, and get our blood pressure checked every now and again. The internet of everything will allow us to monitor our bodily functionings all the time. A few sensors discreetly attached to the body will keep you constantly informed about how your vital functions are doing. It will also help us to keep ourselves healthy. Pill bottles will tell us when to take our medicines; wine glasses will be able to tell us when we have had enough to drink; sugar bowls will warn us about our sugar intake.
From The Economist
The internet’s omniscience is one of its most useful and transformative features [Citation needed]. Whether you want to look up an obscure word or phrase, get a quick briefing on an historical figure or dig into a little-known scientific or political concept [Example needed], help is just a click away. In part this is because of the power and reach of Google’s search engine; but search is only as useful as the information it retrieves, and for many common queries the top match will be an entry in Wikipedia, an online, user-generated encyclopedia which celebrates its tenth birthday this week (see article).
Wikipedia started life as an offshoot of Nupedia, a free, online encyclopedia being written by experts. To speed up the production of articles, two members of the Nupedia team, Larry Sanger and Jimmy Wales [see Wales (disambiguation)], had the idea of allowing anybody to edit entries, using “wiki” technology. The result quickly eclipsed Nupedia.
It is an astonishing success story [Further explanation needed]. On paper, the idea that volunteers could collectively produce the largest and most popular encyclopedia the world has ever seen sounds implausible. Surely reference works need to be compiled by experts [Disputed]? Yet Wikipedia now has over 17m articles, 3.5m of them in English, and its popularity—it is one of the ten biggest sites on the web and is used by around 400m people each month—shows how much people value it. As well as being a useful reference work, Wikipedia is also the most striking example of the idea that volunteers working together online can collectively produce something valuable. Not everyone can contribute to (or even understand) open-source software projects, but anyone can see how Wikipedia’s “crowdsourcing” model works. It showed that the wisdom of the masses could be harnessed, inspiring many other crowdsourced projects—a further reason to celebrate its success [This article reads like an editorial or opinion piece and may require cleanup].
Forthcoming title from Chandos Publishing…
This book addresses the question of how knowledge is currently documented, and may soon be documented in the context of what it calls ‘semantic publishing’. This takes two forms: a more narrowly and technically defined ‘semantic web’; as well as a broader notion of semantic publishing. This book will examine the ways in which knowledge is currently represented in journal articles and books. By contrast, it goes on to explore the potential impacts of semantic publishing on academic research and authorship. It sets this in the context of changing knowledge ecologies: the way research is done; the way knowledge is represented and; the modes of knowledge access used by researchers, students and the general public. More…
Authors: Bill Cope, Mary Kalantzis, University of Illinois, USA and Liam Magee, Royal Melbourne Institute of Technology (RMIT) University, Australia
From Lucas Mearian in Computerworld:
The Computer History Museum this week opens a $19 million, 25,000-square-foot building expansion and a signature exhibition titled “Revolution: The First 2000 Years of Computing.”
In development for more than six years, the new exhibit represents the world’s most comprehensive physical and online exploration of computing history, spanning everything from the abacus and slide rules to robots, Pong and the Internet.
“Many times, people coming to the museum have very basic questions: ‘How did that computer on my desk get there? How did that phone I’ve used for so long get so smart?’ ” said John Hollar, CEO of the museum in Mountain View, Calif. “It’s an exhibition that’s primarily aimed at a nontechnical audience, though there’s a ton of great history and information for the technical audience as well.”
From Jess3
Moritz Stefaner’s Notabilia [notabilia.net] reveals the sentiment within the community discussions that focus on keeping or deleting specific Wikipedia entries. Any Wikipedia editor has the power to nominate an article for deletion and, if this nomination is legitimate, a community discussion takes place where follow editors have the opportunity to make their voices heard.
The online visualization visualizes 100 Article for Deletion (AfD) discussions that took the longest amount of time. A discussion is represented by a thread starting at the bottom center. Each time a user joins an AfD discussion and recommends to ‘keep’, ‘merge’, or ‘redirect’ the article a green segment leaning towards the left is added. Each time a user recommends to ‘delete’ the article a red segment leaning towards the right is added. As the discussion progresses, the length of the segments as well as the angle slowly decay.
Note that the visualized subset might not be representative, as more extensive data suggests that the largest part of these discussions ends after only a few recommendations have been expressed.