Welcome to Digitally Literate, issue #331.
This week I’ve been working on some things behind the scenes. More to come soon. 🙂
I received a really intriguing request from Kay Oddone that I think all of my readers here at DL should consider. Oddone is investigating academics’ experience of professional learning through Personal Learning Networks. If you participate, this would have you create a simple mindmap or sketch of your learning network…and then join for a brief discussion via Zoom to explain your connections. I’m definitely going to participate, and if you’d like to join me, here’s how to join.
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The Danger of Ignoring Julian Assange
Johnny Harris with an intriguing overview of Julian Assange’s story, and why we should pay attention.
For more on this story, Harris suggests reviewing the indictment against Assange, as well as Risk (2016) by Laura Poitras and We Steal Secrets (2013) by Alex Gibney.
We’re Publishing the Facebook Papers. Here’s What They Say About the Ranking Algorithms That Control Your News Feed.
Dear DL readers, we’ve moved on from the Facebook Files (investigative journalism from the Wall Street Journal) to the Facebook Papers. Frances Haugen, a former member of the Civic Integrity team at Meta, released a tranche of 1,300 documents during her testimony to Congress. Not soon after, Gizmodo partnered with a group of independent experts to review, redact, and publish these documents to “facilitate the responsible disclosure of the greatest number of documents in the public interest possible”.
This post shares some documents and adds context to show that Facebook has spent years assigning emotional value to every swipe and click in its app.
What these documents show us is that, for all of Facebook’s hand-wringing over what it thinks is “meaningful” to users, or “worthy of their time,” internally, employees view ranking as far too complex, too incomprehensible, to ever get the job done right. They also know it’s a system on which Facebook’s future depends.
Tracking Exposed: Demanding That the Gods Explain Themselves
Cory Doctorow with a review of algospeak, is a new English dialect that emerged from the desperate attempts of social media users to “please the algorithm”: that is, to avoid words and phrases that cause social media platforms’ algorithms to suppress or block their communication. As an example, Vietnamese AOL users were unable to talk about friends named “Phuc” in the company’s chat-rooms.
Doctorow shares tools from Tracking Exposed that serve as creative workarounds for content creators.
The post also suggests that digital platforms, networks, and tools should make their policies legible to audiences and creators, adopting The Santa Clara Principles. The Santa Clara Principles are a set of standards developed by the Electronic Frontier Foundation (EFF) and a coalition of civil society organizations and academics directed at government and state actors to beef up due process and expand guidelines for reporting on and notifying users about takedowns.
The ‘digital town square’? What does it mean when billionaires own the online spaces where we gather?
Jean Burgess on the challenges when Musk buys Twitter and whether we should get rid of the idea of a digital town square.
Are the days of the “digital town square” over? “A free-speech free-for-all, a nightmarish town square where everyone is shouting all the time and anyone who doesn’t like it just stays home.”
Does the idea of the town square moving digital ultimately reinforce existing divisions and hierarchies?
How Kendrick Lamar’s “The Heart Part 5” Video Subverts Deepfake Technology
We’ve talked quite a bit about deepfakes here in DL. We’ve also talked about Kendrick Lamar in this newsletter as well. Lamar just released his fifth studio album this week, and I’ll spend the remainder of the summer listening on repeat. As an aside…check out Lamar’s website. It’s brilliant.
Most times when we’re discussing deepfakes we’re focusing on the negatives, but Lamar uses the technology in a video for The Heart Part 5 to destabilize our concepts of identity.
AI’s first philosopher
Alan Turing was a pioneer of machine learning, whose work continues to shape the crucial question: can machines think?
This long-form piece shares the growth of Turing from “a schoolboy whose work in mathematics was judged promising yet untidy, and whose ideas were considered ‘vague’ and ‘grandiose’ by his teachers, to being one of the most innovative minds of the 20th century.”
The whole thinking process is still rather mysterious to us, but I believe that the attempt to make a thinking machine will help us greatly in finding out how we think ourselves.
Taking & Making Notes
I’ve been taking time behind the scenes to revise my information processing systems, techniques, and tools. Part of that involves reading How to Take Smart Notes by Sönke Ahrens.
This post by Evan Tobias shares guidance on how to take notes as you research. I’ll share more guidance in the future as I revise my workflow.
The wiser mind mourns less for what age takes away than what it leaves behind.
Pessimism sounds smart because optimism often requires believing in unknown, unspecified future breakthroughs—which seems fanciful and naive. If you very soberly, wisely, and prudently stick to the known and the proven, you will necessarily be pessimistic.
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