Saturday, September 26, 2009

Machine Learning Protest at G20

I have returned to the blogosphere to report on our successful voicing of machine learning concerns at the G20 People's March yesterday.

















(Top: "Support Vector Machines," "Repeal Power Laws," "End Duality Gap," "MapReduce, MapReuse, MapRecycle: Green Data Processing." Bottom: "Bayesians Against Discrimination"," "Free Variables," "Ban Genetic Algorithms")


Several CMU SCS grad students and postdocs gathered at CMU and walked to Oakland where the march was to begin. As we carried our signs the LOL:Puzzlement ratio decreased (but by no means disappeared) as the distance from CMU increased. Then we marched with the crowd towards dahntahn.
















John Oliver of the Daily Show showed up.















At some point we realized we were walking in front of the United Steelworkers team, who were all wearing the same hard hats as me (my friend having snagged mine from the USW booth at Netroots Nation last month). Here I am with a USW comparing causes.












All in all it was a success. For full set of pictures, go HERE.

For publications related to machine learning activism, see "Data Mining Disasters: A Report" [pdf], from SIGBOVIK 2008; and "MapReuse and MapRecycle: Two More Frameworks for Eco-Friendly Data Processing" [pdf], of SIGBOVIK 2009.

25 comments:

Misseswaffles if you please said...

Excellent!
That made my day!

Anonymous said...

You guys are all kinds of awesome!!!!

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invierta en franquicias said...

I look forward to reading more on the topic in the future. Keep up the good work! This blog is going to be great resource. Love reading it.

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Benjamin said...

Awesome :)

I'm a data mining student, just about to finish my course, and damn I love the field. And I never thought statistics could be fun. But combined with AI, algorithm, logic and probability theory things just get fun in a very nerdy manner.

I love your signs. Especially the SVM and genetic algorithm ones. We used SVM's mainly, and I very much like them. I do however find myself drawn to genetic algorithms, but I've had a few presentations by industry professionals, as well as my professors, and the message is "they are good, but in very, very limited problem domains, and is generally a no-no".

We'll see how my master thesis goes :) I promise, if I do genetic algorithms, I'll base it on real consideration and not just "WOW, nature does it, and therefore it must rule!"

Also, I'll read your blog. I promise. (Just more fun to do while having lectures - not all of them are as interesting as the one I had in this field)

Sincerely,
Benjamin Fedder Jensen :)