In Dissent, Anna-Verena Nosthoff and Felix Maschewski of the Critical Data Lab analyze the failure of the "metaverse" to materialize, despite Mark Zuckerberg’s considerable efforts.
In all likelihood, the metaverse is an expensive PR stunt to help Meta again bask in the light of profitability and glorious innovation following its spate of recent data scandals. However, not all has gone according to plan. … All this paints a picture of a wider disillusionment pointing to the fraying of solutionism itself.
Julia Velkova and Jean-Christophe Plantin introduce a New Media & Society special issue on data centers:
Most Internet content and data today pass through and get stored on these facilities. As we are writing this text, large and small territories on Earth’s five continents, underground, underwater, and in space are being envisioned, planned, and zoned for the construction and operation of new data centers. From Singapore to Iceland, and from Cape Town through Chile to Northern Ireland, data centers have become critical to large-scale industrial projects that render climate, energy, and the planet “knowable” and exploitable through data. … The timely operation of platform services, computation on demand, streaming video, and social media are thus critically dependent not just on software or data capture but also upon organizing and managing their timely provision from within data centers.
Other contributors to the issue include Devika Narayan, Steven Gonzalez Monserrate, Tonia Sutherland, Mél Hogan, Vicki Mayer, A.R.E. Taylor, and Patrick Bresnihan.
In the NORRAG Blog, Kean Birch asks what material limits the EdTech sector is likely to come up against in its pursuit of data as a value-creating asset:
There’s a lot going on in EdTech, once you start looking; not all of it is going to be good for teaching or learning, and not all of it is going to be good for universities and faculty. In fact, there are a range of unintended or unexpected consequences from this expansion of EdTech that we simply can’t predict.
An important issue that has come up during our fieldwork are the attempts by EdTech companies to find a use for all the personal and user data they are collecting, whether deliberately or accidentally. Most EdTech products and services end up producing data in one form or another, and many assume that there is "gold in data," as one informant told us.
The Internet Archive’s Brewster Kahle summarizes some challenges to preserving digital heritage:
Ever try to read a physical book passed down in your family from 100 years ago? Probably worked well. Ever try reading an ebook you paid for 10 years ago? Probably a different experience. From the leasing business model of mega publishers to physical device evolution to format obsolescence, digital books are fragile and threatened. For those of us tending libraries of digitized and born-digital books, we know that they need constant maintenance—reprocessing, reformatting, re-invigorating or they will not be readable or read.
Wired has published an excerpt from Sarah Lamdan’s Data Cartels: The Companies That Control and Monopolize Our Information:
You might not be familiar with RELX, but it knows all about you. Reed Elsevier LexisNexis (RELX) is a Frankensteinian amalgam of publishers and data brokers, stitched together into a single information giant. There is one other company that compares to RELX—Thomson Reuters, which is also an amalgamation of hundreds of smaller publishers and data services. Together, the two companies have amassed thousands of academic publications and business profiles, millions of data dossiers containing our personal information, and the entire corpus of US law. These companies are a culmination of the kind of information market consolidation that’s happening across media industries, from music and newspapers to book publishing. However, RELX and Thomson Reuters are uniquely creepy as media companies that don’t just publish content but also sell our personal data.
In Hyperallergic, Marco Donnarumma reflects on the ethical — and artistic — shortcomings of AI image generators:
As an artist and scholar working with open source technology since 2004 and with machine learning and AI since 2012, I’m as fascinated as I am weary of the creative potentials and cultural implications of machine learning. Deep learning and, by extension, AI generators are particularly problematic because their efficiency depends on the exclusive assets of a few extraordinarily wealthy agents in the industry.
Jonne Arjoranta built a tool to explore why there aren’t more women in computing. The answers may surprise you!
Why aren’t there more women in computer science? Why haven’t there been more women working as programmers? These questions often evoke speculation about biological differences, but answers often leave out the historical and cultural context.
This design project by Silvio Lorusso captures the explosion of small tasks that eat up many workers’ days.
The paperwork explosion of the ’60s, which computers were supposed to end, has become a collision of digital microinteractions – a microwork explosion. In this CV of microwork, the life experience of the traditional résumé coincides with user experience.
A Tactical Tech-curated collection of technologies "developed, marketed and implemented to mitigate the pandemic and to help societies ‘get back to normal.’"
The project creates a snapshot in time and an archive of rapid shifts in the uptake of ambient, behavioural and bio-metric data and intelligence worldwide. Some of these technologies bring hope and some play into our fears. Ultimately the project asks — what kinds of societies are we building? what trade-offs are we willing to make? and do these techno-solutions help us succeed in controlling the virus, or only in controlling the hosts?