Web Picks (week of 28 November 2016)

Every two weeks, we find the most interesting data science links from around the web and collect them in Data Science Briefings, the DataMiningApps newsletter. Subscribe now for free if you want to be the first to get up to speed on interesting resources.

  • Trust in Data Science
    “Whether it’s a result generated by a team member, our team as a whole, or a system we’ve designed — all of our data consumers, from executive leaders, nurse practitioners and wellness managers, to our call center agents and provider services reps — need to trust in the output. If they don’t, they won’t use it.”
  • Turning Data Around
    How can we build new data systems that start as two-way streets, and consider the individuals from whom the data comes as first-class citizens?
  • Image-to-Image Translation with Conditional Adversarial Nets
    “These networks not only learn the mapping from input image to output image, but also learn a loss function to train this mapping. This makes it possible to apply the same generic approach to problems that traditionally would require very different loss formulations.” Impressive work!
  • Media in the Age of Algorithms
    Since Tuesday’s election, there’s been a lot of finger pointing, and many of those fingers are pointing at Facebook, arguing that their newsfeed algorithms played a major role in spreading misinformation and magnifying polarization.
  • Google’s AI translation tool seems to have invented its own secret internal language
    “All right, don’t panic, but computers have created their own secret language and are probably talking about us right now. Well, that’s kind of an oversimplification, and the last part is just plain untrue. But there is a fascinating and existentially challenging development that Google’s AI researchers recently happened across.”