Digitally Literate #231

WELCOME
Machine Learning Delay
Digitally Lit #231 – 2/1/2020

Hi all, welcome to issue #231 of Digitally Literate.

Last week I posted this piece about talking to youth about privacy, security, & digital spaces. These materials and the related interview were used by Meghan Herbst in a piece for Wired on How to Raise Media-Savvy Kids in the Digital Age.

If you haven’t already, please subscribe if you would like this newsletter to show up in your inbox. Feel free to reach out and let me know what you think of this work at hello@digitallyliterate.net.

Watch

How Machine Learning Is Generating Strange, New Sounds (11:18)

Project Magenta is a Google Research project that uses machine learning to create new tools for artists and musicians. One of these tools is NSynth, a neural synthesizer that generates strange, new sounds like “cat flutes,” “beast guitars,” and “screaming 3D printers.”

In this video, from Nat and Friends, they explore how NSynth works, and talk with Andrew Huang about his process creating a song entirely out of NSynth generated sounds.

Read

How to Change Your Off-Facebook Activity Settings

Facebook’s long-awaited Off-Facebook Activity tool started rolling out this week.

While it’s not a perfect measure, and we still need stronger data privacy laws, this tool is a first step toward greater transparency and user control regarding third-party tracking. Hopefully other companies follow suit, and allow users to take advantage of it.

This tutorial shows you have to clear your account of off-Facebook activity, and prevent it from being collected in the future. Go do this now.

Teenage sleep and technology engagement across the week

Amy Orben and Andrew Przybylski with research that analyses data from 11,884 adolescents included in the UK Millennium Cohort Study to examine the association between digital engagement and adolescent sleep. They compare the relative effects of retrospective self-report vs. time-use diary measures of technology use.

Results suggest that the negative associations in evidence are mainly driven by retrospective technology use measures and measures of total time spent on digital devices during the day.

This work provides an empirical lens to understand the effects of digital engagement both throughout the day and before bedtime and adds nuance to a research area primarily relying on retrospective self-report.

Why We Should Ban Facial Recognition Technology

There has been a lot of news about Clearview AI, a shadowy facial-recognition-software company providing users access to a database of 3 billion photographs scraped from social media and video streaming sites.

Max Read takes issue with a quote from one of Clearview’s investors in which he says:

I’ve come to the conclusion that because information constantly increases, there’s never going to be privacy…Laws have to determine what’s legal, but you can’t ban technology. Sure, that might lead to a dystopian future or something, but you can’t ban it.

This post by Read pushes back on this narrative that the creep of new technologies is inevitable, and attempts to stop or control it is foolish.

A De-escalation Exercise for Upset Students

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A simple technique that takes just a few minutes can help an agitated student regain the state of mind needed for learning.

  • Give the student time to regain their calm
  • Direct the student to be aware of their thoughts and feelings
  • Have the student redirect their thoughts
  • Give the student positive feedback on becoming calm
  • Give the student a little more time to refocus
  • Have the student reflect for the future

Google’s College Readiness Collection

The College Readiness Collection from the Google Applied Digital Skills Team. These lessons will help you plan and prepare for college and other education opportunities.

Organize College Applications in Google Sheets: Create a spreadsheet to track and organize college applications using Google Sheets.
Draft an Application Essay: Write a college application essay using Google Docs to jump-start the application process.
Search for Colleges Online: Gather data about college choices by conducting an online search and recording the data in a spreadsheet in Google Sheets.
Prepare for a College Interview: Collaborate with a partner in a document to prepare for potential interviews.
Prepare for the FAFSA: Organize documents and other important information in a spreadsheet for the Free Application for Federal Student Aid (FAFSA).
Ask Someone to Be a Reference: Use Google Sheets to compile a list of potential references, then write an email to each asking for their recommendation.

Make

Reducing friction in the development of your OER

I blog a lot…and share materials openly online. As I build and share materials, I’m always trying to find ways to allow people to respond and critique to my materials in a friction-free manner.

In this post from David Wiley, he indicates that at Lumen Learning they are adding a button to the bottom of all webpages that links to a Google Doc version of the content. This is shared publicly, and has Track Changes turned on to allow feedback.

I may add this to my blogging, and publishing repertoire.
Consider

consider

I’m reflective only in the sense that I learn to move forward. I reflect with a purpose.

Kobe Bryant

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Digitally Literate is a weekly review of the news, notes, tips, and tricks from the week that resonated with me. I leave a trail of digital breadcrumbs as I read online. Some of this I share on my social networks…much more I do not. At the end of the week, I review my notes and write up this newsletter.

If you have some time, watch six decade-long disinformation operations unfold in six minutes.

Feel free to connect at hello@digitallyliterate.net or on the social network of your choice.

2 comments

  1. Aaron Davis
    February 12, 2020 at 6:17 am

    Ian, I am intrigued by the idea of banning the use of facial recognition software by police.

    One city banning its law enforcement from making use of facial recognition won’t necessarily stop a sheriff’s department from creating a surveillance dragnet — nor would it necessarily stop a private institution within a city from enacting its own facial-recognition program. For now, the bans don’t touch on third-party companies whose data is used by facial-recognition algorithms.

    My wondering is what this means for third-party applications in schools? In the community? It still feels like the cat might be out of the bag? I fear that some vendors will continue to cash in and work as mercenaries. I hope I am wrong.
    I am also taking by the argument that we need to focus on surveillance, not just facial recognition.

    • wiobyrne
      February 17, 2020 at 10:03 am

      Hey Aaron, thanks for the feedback.

      I agree that we need to think more about data, data-privacy, surveillance, and tying all of these loose threads together. I agree that facial recognition is a problem, but I agree with your assessment that the “cat may be out of the bag.”

      I think about students using digital texts, tools, and spaces in early learning environments…and have concerns about where that data goes. As an example, my daughter is no longer at one of her first early childhood centers. Who controls the photos and messages the teachers sent us over the years using SeeSaw of her playing outside? Where does that data go? What happens in 15 years (or sooner) when SeeSaw sells out, is hacked, or shuts down. Where does all of that content go?

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