Data Stories 027 | Big Data Skepticism w/ Kate Crawford
Oct 17, 2013
01:05:13
Here we go with another great episode. This time more on the data side. We have Kate Crawford, Principal Researcher at Microsoft Research, on the show talking about the other face of big data. That is, after all the excitement, hype, and buzz, she is the one who is asking the tough questions: Is more data always better? Is there any objective truth in it? Is big data really making us smarter?
Papers and articles from Kate
- Boyd, D. and Crawford, K. 2012 ‘Critical Questions for Big Data‘, Information, Communication and Society, Volume 15, no 5, pp 662-679.
- Crawford, K. and Schultz, J. 2014 ‘Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harms‘, Boston College Law Review, Vol. 55, No. 1.
- “The Hidden Biases in Big Data” (Harvard Business Review)
- “Think Again: Big Data” (Foreign Policy)
Some of Kate’s Talks
- The Raw and the Cooked: The Mythologies of Big Data
- Strata 2013: Kate Crawford, “Algorithmic Illusions: Hidden Biases of Big Data“
Links
- Book: Objectivity by Lorraine J. Daston (How recent is it?)
- Paper: Private traits and attributes are predictable from digital records of human behavior (how big data and algorithms can discriminate).
- Paper: Unique in the Crowd: The privacy bounds of human mobility (only 4 data points are needed to identify a person)
- When Google got flu wrong (Google failing to predict flu)
- The End of Theory: “The Data Deluge Makes the Scientific Method Obsolete” (Chris Anderson on the end of theory, correlation vs. causation, etc.)
- How a Map Is Like an Op-Ed (“Maps are arguments, just like a piece of written journalism is an argument.”)
- Mislove, Alan, et al. “Understanding the Demographics of Twitter Users.” ICWSM. 2011.
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Enjoy it, there’s lots of food for thoughts here!