Weekly Web Harvest for 2018-03-18

  • Gobo

    Sign up for Gobo, link it to your other social media profiles, and you can take control of your feed. Want to read news you aren’t otherwise seeing? Use our “Echo Chamber” filter to see what we call “wider” news. Want a better balance of men and women in your feed? Use our “gender” filter to rebalance it. Want to take a lunch break and just see popular funny videos you friends are sharing? Use our “virality” filter to pick only the most shared content. With Gogo you’re in charge of the algorithmic filters that control what you see on social media. We’ve built a bunch of filters like these already, are building more, and have made it possible for other developers to add filters too. Sign up, try it out, and see if it changes how you think about how social media should work.

  • Lunar Conversations – C82: Works of Nicholas Rougeux
  • Watch neural networks see only what they’ve been trained to see / Boing Boing

    confirmation bias meets potentials for art

  • This School Has Been Arming Classrooms With 5-Gallon Buckets Of Rocks In The Event Of A School Shooting

    David Helsel, superintendent of the Blue Mountain School District in Schuylkill County, made the announcement at a state House Education Committee hearing on school safety March 15.

    “If an armed intruder attempts to gain entrance to any of our classrooms, they will face a classroom full of students armed with rocks. And they will be stoned,” Helsel said.

    “We have some people who have some pretty good arms. They can chuck some rocks pretty fast,” he added.

  • Uber’s Self-Driving Cars Were Struggling Before Arizona Crash – The New York Times

    “With autonomy, the edge cases kill you, so you’ve got to build out for all the edge cases,” Mr. Khosrowshahi said at a conference in November.

  • A Quantitative Analysis of the Impact of Arbitrary Blockchain Content on Bitcoin

    Our analysis shows that certain content, e.g., illegal pornography,
    can render the mere possession of a blockchain illegal. Based on
    these insights, we conduct a thorough quantitative and qualitative analysis
    of unintended content on Bitcoin’s blockchain. Although most data
    originates from benign extensions to Bitcoin’s protocol, our analysis reveals
    more than 1600 files on the blockchain, over 99 % of which are texts
    or images. Among these files there is clearly objectionable content such
    as links to child pornography, which is distributed to all Bitcoin participants.
    With our analysis, we thus highlight the importance for future
    blockchain designs to address the possibility of unintended data insertion
    and protect blockchain users accordingly.

    h/t 4 links