jm + datamining   6

IBM's creepy AI cyberstalking plans
'let's say that you tweet that you've gotten a job offer to move to San Francisco. Using IBM's linguistic analysis technologies, your bank would analyze your Twitter feed and not only tailor services it could offer you ahead of the move--for example, helping you move your account to another branch, or offering you a loan for a new house -- but also judge your psychological profile based upon the tone of your messages about the move, giving advice to your bank's representatives about the best way to contact you.'

Ugh. Here's hoping they've patented this shit so we don't actually have to suffer through it. Creeeepy. (via Adam Shostack)
datamining  ai  ibm  stupid-ideas  creepy  stalking  twitter  via:adamshostack 
february 2014 by jm
How Kaggle Is Changing How We Work - Thomas Goetz - The Atlantic

Founded in 2010, Kaggle is an online platform for data-mining and predictive-modeling competitions. A company arranges with Kaggle to post a dump of data with a proposed problem, and the site's community of computer scientists and mathematicians -- known these days as data scientists -- take on the task, posting proposed solutions.

[...] On one level, of course, Kaggle is just another spin on crowdsourcing, tapping the global brain to solve a big problem. That stuff has been around for a decade or more, at least back to Wikipedia (or farther back, Linux, etc). And companies like TaskRabbit and oDesk have thrown jobs to the crowd for several years. But I think Kaggle, and other online labor markets, represent more than that, and I'll offer two arguments. First, Kaggle doesn't incorporate work from all levels of proficiency, professionals to amateurs. Participants are experts, and they aren't working for benevolent reasons alone: they want to win, and they want to get better to improve their chances of winning next time. Second, Kaggle doesn't just create the incidental work product, it creates a new marketplace for work, a deeper disruption in a professional field. Unlike traditional temp labor, these aren't bottom of the totem pole jobs. Kagglers are on top. And that disruption is what will kill Joy's Law.

Because here's the thing: the Kaggle ranking has become an essential metric in the world of data science. Employers like American Express and the New York Times have begun listing a Kaggle rank as an essential qualification in their help wanted ads for data scientists. It's not just a merit badge for the coders; it's a more significant, more valuable, indicator of capability than our traditional benchmarks for proficiency or expertise. In other words, your Ivy League diploma and IBM resume don't matter so much as my Kaggle score. It's flipping the resume, where your work is measurable and metricized and your value in the marketplace is more valuable than the place you work.
academia  datamining  economics  data  kaggle  data-science  ranking  work  competition  crowdsourcing  contracting 
april 2013 by jm
The Secrets of Building Realtime Big Data Systems
great slides, via HN. recommends a canonical Hadoop long-term store and a quick, realtime, separate datastore for "not yet processed by Hadoop" data
hadoop  big-data  data  scalability  datamining  realtime  slides  presentations 
may 2011 by jm
PeteSearch: How to split up the US
wow. fascinating results from social-network cluster analysis of Facebook, splitting up the entire USA into 7 clusters
clusters  facebook  data  statistics  maps  culture  analytics  datamining  demographics  socialnetworking  graph  dataviz  from delicious
february 2010 by jm
why "anonymized" data really isn't
'Ohm notes, this illustrates a central reality of data collection: "data can either be useful or perfectly anonymous but never both."'
security  internet  politics  privacy  medicine  anonymity  datamining  anonymous  data  from delicious
september 2009 by jm

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