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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.

Some people just want to watch the world learn. Therefore, Nicky Case has some great advice on how to explain things:

1. Show what made you care
2. Show, then tell
3. Therefore & But, not And Then
4. Write a draft, then cut 10%
5. Do real tests, early & often

But, you should really watch this great talk for yourself.

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?

In THE Campus, computer scientist Andy Farnell takes up the cudgel for plain-text teaching tools.

We don’t need more complex and insular proprietary teaching tools; we need to make more intelligent use of the powerful, standardised, interoperable foundations we already have in computing.

On the Platform Cooperativism Consortium blog, T. O. Molefe introduces the concept of digital coloniality to bring into view the extractive and oppressive relations that fuel tech — and to consider what sorts of relations could be built instead.

Like the charter companies that served as tools of colonial conquest, digital multinationals like Meta, Uber and Airbnb have amplified the extractive, exploitative relationship that global elites have established with everyone else, and have also co-opted governments into their plans. The actions of these companies’ controlling shareholders are defining, and some would say corrupting, what it means to be human in a digital world and who can be human.

Karen Hao follows the workings of AI colonialism to a remote New Zealand town for MIT Technology Review.

In turning to AI to help revive te reo, the Māori language, Mahelona and Jones, who is Māori, wanted to do things differently. They overcame resource limitations to develop their own language AI tools, and created mechanisms to collect, manage, and protect the flow of Māori data so it won’t be used without the community’s consent, or worse, in ways that harm its people.

At Elephant in the Lab, Jefferson Pooley details the metrics and surveillance systems at the heart of academic infrastructures.

Scholarly publishing is its own, emerging surveillance economy. We can call a company a surveillance publisher if it derives a substantial proportion of its revenue from prediction products, fueled by data extracted from researcher behavior. On that definition, we already have surveillance publishers in our midst.