My Faults My Own

Any human’s death diminishes me,

because I am involved in humankind.

IN  WHICH Ross Rheingans-Yoo—a sometime economist, artist, trader, expat, poet, EA, and programmer—writes on things of int­erest.

Reading Feed (last update: July 5)

A collection of things that I was glad I read. Views expressed by linked authors are chosen because I think they’re interesting, not because I think they’re correct, unless indicated otherwise.


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Blog: Don't Worry About the Vase | Spoiler-Free Review: Witcher 3: Wild Hunt (plus a Spoilerific section)

Blog: Popehat | The Fourth of July [rerun]

Blog: Tyler Cowen @ Bloomberg View | The NBA’s Reopening Is a Warning Sign for the U.S. Economy — "If so many NBA players are pondering non-participation, how keen do you think those workers — none of whom are millionaire professional athletes — are about returning to the office?"

Comic: SMBC | Saturday Morning Breakfast Cereal - Holism


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Blog: Market Design | Job market technology is diffusing slowly through the armed forces

Blog: Marginal Revolution | Tales from Trinidad barter

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January 16 Links: Technologies, Games, and Play

Yes, the Friday linkwrap is, in fact, going out on Friday. We're living in the future!

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The Harvard Political Review reports that a Chicago nonprofit is scraping Twitter to pass on complaints about food poisoning in restaurants to the Chicago Department of Public Health:

Foodborne Chicago depends on human judgment in addition to computerized predictions. First, the algorithm "surfaces tweets that are related to foodborne illnesses." Next, "a human classifier goes through those complaints that the machine classifies, [...determining] what is really about food poisoning and what may be other noise." The Foodborne team then tweets back at the likely cases, providing a link for users to file an official complaint. In short, computers deal with the massive quantity of Twitter data, and humans ensure the quality of the result. According to its website, between its launch on March 23, 2013 and November 10, 2014, the Foodborne algorithm flagged 3,594 tweets as potential food poisoning cases. Of these tweets, human coders have identified 419,

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