Welcome back! Here’s Digitally Literate, issue #341.
I’m stepping away from this newsletter and social media for the month of August. As the summer wraps up, and I prepare for the new academic year, I find it helpful to take a digital detox of sorts. I started this process several years ago when I watched good friend Doug Belshaw take a break during the year. I honestly didn’t see the need when he did it the first time, and I took a two week break to see what it would feel like. During the first summer of COVID, I took the month of August as our family was trying to adapt to unsure circumstances.
I find it helpful to step away and take time to reflect on personal and professional goals and the work that I do. I hope that you also find time to reflect on the what, why, and how of your actions. ˗ˋˏ ♡ ˎˊ˗
This week I helped facilitate sessions at CSPD Week 2022 for the state of South Carolina. The session I helped run focused on bringing educators brand new to computer science and computational thinking into the community.
This video from the Domain of Science YouTube channel includes a great visual that I wish I found for this session.
Last week, Meta announced that the Facebook newsfeed would be shifting towards an algorithmic, recommendation-based model of content distribution. What this means is that Facebook, the world’s largest social network will increasingly rely on recommended media for you based on decisions made by algorithmic models.
In plain English, this means that most, if not all of the content in your feed will be dictated by what Meta thinks “people like you” like, or would be interested in seeing more about.
Whereas in social media, people see content from their friends regardless of the quality of the content, in recommendation media, content distribution is optimized for engagement.
This holds big implications for users of the social network as many individuals use Facebook as their sole resource for info and news. As this silo of the Internet becomes less transparent, we won’t be able to understand the implications for some time. We’ll keep an eye on this in DL.
While teaching others about computational thinking this week, we wrapped up our exploration looking at algorithms. I indicate that an algorithm is just a set up steps put in place to achieve an outcome, or solve a problem. These algorithms are rarely perfect, and decisions need to be made to review and improve the algorithm over time. Given stories about how our networks, platforms, and tools are increasingly moving to algorithms to dictate interactions between humans and devices, understanding the algorithm, or the decisions made behind the scenes is difficult…if not impossible.
The result is three types of individuals. The first is individuals that blindly trust anything that the algorithm provides them. The second is the individual that strives to reach outside of the feed to diversify what they’re consuming. The third is the individual that trusts nothing and walks away from these spaces, places, and tools.
Peter’s dilemma brought to my mind a term that has been used, in recent years, to describe the modern Internet user’s feeling that she must constantly contend with machine estimations of her desires: algorithmic anxiety. Besieged by automated recommendations, we are left to guess exactly how they are influencing us, feeling in some moments misperceived or misled and in other moments clocked with eerie precision. At times, the computer sometimes seems more in control of our choices than we are.
This week in the People vs Algorithms newsletter, the discussion around content creation and the next social network indicates that media is a game of intent and attention. The most valuable platforms dominate one or the other. Few win at both. On the internet, our intent is funneled into commercial action.”
Troy Young suggests that the next iteration of these spaces will focus on content creators and influencers.
People like the influencer family are the fuel that make these engines run. The next generation of social platforms could care less if your personal network is signed up and more about the vibrancy of a indentured creator class that that can be endlessly funneled into the video feed. Like media, social platforms are generational. Social is shifting from connections to entertainment. The next gen wants their MTV.
I think this take is interesting, it also reminds me of what I (and many others) hoped we’d see a little over a decade ago when the Internet started to impact most aspects of society. I also think this take is carving out space for Web 3.0 and NFT discussions.
The term “meme” was coined by Richard Dawkins, who used it to describe an idea, style, or behavior that shares from one person to another in a culture. The term now encompasses an amusing or interesting item (such as a captioned picture or video) or genre of items that is spread widely online especially through social media.
This post from Christopher Ferguson discusses the challenges of memes as a form of misinformation, and how they flatten discourse into a false dichotomy of good and evil.
Here in DL, I often ask whether it is okay for folks to change their mind online, or admit that they got something wrong. I mean…we’re all human. We make mistakes. I’d rather someone try, and admit that they’re learning, and growing every day.
This post alerted me to the latest controversy surrounding purity culture, and what happens after you get married. Purity culture is a term often used for the evangelical movement that attempts to promote a biblical view of purity by discouraging dating and promoting virginity before marriage, often through the use of tools such as purity pledges, symbols such as purity rings, and events such as purity balls.
Followers (and critics) of purity culture are both very vocal as influencers in the community are getting married, and talking a lot more about sex in their feeds.
Jesse Anderson indicating the problem with glorifying personal productivity. Many of these systems are designed to make you look busy…as opposed to getting things done. For people that are not neurotypical, this is often a recipe for disaster.
Anderson suggests a different model focused on four components. Captivate. Create. Compete. Complete.