August 30, 2015
Briefly
- Three posts about algorithmic transparency and discrimination, via mathbabe.org:
- in order not to discriminate on, say, race, you need to explicitly use race in your algorithm selection: Cynthia Dwork, at NYT
- How Big Data is Unfair, by Moritz Hardt
- Fairness, Accountability, and Transparency, by Hanna Wallach
- “If you get the software a little bit wrong, you will break the law thousands of times” A different sort of big data story from Matt Levine
- The number of ‘moderate’ voters is seriously overestimated, from Vox
- A pointy-clicky way to make fairly sophisticated graphs, from Jeroen Ooms.
- You can do randomised controlled trials of natural products, as in the trial of kānuka honey for acne, covered by Jamie Morton at the Herald. The trial doesn’t show the product is better than ordinary honey or that it’s better than other acne treatments, but it does show it’s better than just soap and water.
Thomas Lumley (@tslumley) is Professor of Biostatistics at the University of Auckland. His research interests include semiparametric models, survey sampling, statistical computing, foundations of statistics, and whatever methodological problems his medical collaborators come up with. He also blogs at Biased and Inefficient See all posts by Thomas Lumley »