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Index of Titles Filed Under 'Data Mining'
Das Kapital bin ich: Schluss mit der Digitalen Leibeigenschaft.
Das Manifest für alle Internet-Zweifler und Gegner der virtuellen Manipulation. Für alle, deren Fingerspitzen nur noch Touchscreens berühren, die in YouTube verloren gehen und sich Facebook ausgenommen fühlen. Für alle, die sich den AGBs von Google & Co nicht mehr fügen wollen. Es ist Zeit, sich aus der selbstverschuldeten “Digitalen Leibeigenschaft” zu befreien! Der Ökonom Hannes Grassegger zeigt auf, wie wir zu einem neuen Selbstbewusstsein im Umgang mit unseren Daten finden und auch noch Geld daran verdienen. “Holen wir uns, was uns gehört. Wir sind das Internet.”
There is no doubt that we live in exciting times: Ours is the age of many ‘silent revolutions’ triggered by startups and research labs of big IT companies; revolutions that quietly and profoundly alter the world we live in. Another ten or five years, and self-tracking will be as normal and inevitable as having a Facebook account or a mobile phone. Our bodies, hooked to wearable devices sitting directly at or beneath the skin, will constantly transmit data to the big aggregation in the cloud. Permanent recording and automatic sharing will provide unabridged memory, both shareable and analyzable. The digitization ...
Instagram photos, public transport information, streamed music and Netflix movies seem to appear out of thin air on your phone, don’t they? Well, getting them onto that screen isn’t as light and easy as it feels. There is, in fact, an immense and decidedly heavy infrastructure powering the cloud. More and more architecture is being designed and built to house server space and internet connection hubs. Since these buildings typically use as much energy as a medium-sized city, our digital lives have a direct environmental toll. Minimising this footprint is one of the data centre industry’s main issues.
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A super-computational grid overlaying the earth’s surface, an all-seeing, oating ecosystem, an Uber-planet, an internet of things in which the things are us, is recording and storing our every movement. We subscribe to it—willingly providing it with our data. By the same token, our immersion in the permanence of the informational mayhem is flooding us with fictions. On the one hand, theoretically, the permanent input channel of billions of facts per second—GPS coordinates, heartbeats, selfies, currency fluctuations, etc.— into the super-computational megastructure, is always pushing for a transparent world. In that world “truth” would cease to be a word because there would be ...
Making available massive amounts of data that are generated, distributed, and modeled, digital media provide us with the possibility of abundant information and knowledge. This possibility has been attracting various scenarios in which technology either eliminates non-knowledge or plants it deep within contemporary cultures through the universal power and opacity of algorithms. This volume comprises contributions from media studies, literary studies, sociology, ethnography, anthropology, and philosophy to discuss non-knowledge as an important concept for understanding contemporary digital cultures.
The Wages for Facebook manifesto appeared anonymously online in 2014. Its website consists of a single page with the manifesto written in bold letters scrolling automatically, denying visitors the ability to use the patented swipe gesture or the scrollbar.
Wages for Facebook refers to a 1975 text “Wages against Housework” by Silvia Federici, the feminist author and activist, which addressed the invisible role played by women’s affective labor as mothers, wives, and housewives (although not exclusively) in sustaining capitalism. In the same vein, Wages for Facebook demands that our time spent online, on social media platforms be recognized for what it is: ...
Sitting somewhere between Minority Report and the OurRevolution PAC, White Collar Crime Risk Zones is a website and app that use “machine learning to predict where financial crimes will happen across the U.S.” The app’s system was trained on financial malfeasance reports going back to 1964, and by referencing events with geotagged cartography it can predict financial crimes at the city-block-level with an accuracy of 90.12%. Typically, the logic of predictive policing is applied to ‘street’ level crime (drugs, assault, etc), and has rarely (if ever) been applied to the financial crimes of white collar criminals. Turning the technology on the ...
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