If you read here often enough or have scrolled down to the footer of my blog then you are familiar with some of writings and videos of Cathy O’Neil, a former Wall Street Quant and below is a bit of her history as she wrote on the O’Reilly Strata page which has published her latest essay. Interesting to read below on the exposure she had while working at DE Shaw and her opinions. Yes we all hear the political bull horns but when to comes right down to the fact we are really seeing how little some of the people who are trusted to make major decisions know about data mechanics. You don’t have to be a mathematician to understand the concepts, but at least “get the concepts” of how all of this works. We are seeing this big time right now with our HHS secretary stumbling all over the place sadly which is pretty much what I said back in 2009 that Health IT would eat her up and we have the same issues at the SEC so this is not personal, it is what it is and this even manifests itself in even a bigger way with our Congress.
As she states there’s a lot of good stuff out there but there’s always the other side that exists and so goes that with anything in life; however the power of data is something that we have not experienced before like we are seeing it today, and there is good reason to be skeptic when you need to be. It boggles my mind as well when I see the attention not focused to where there’s some good education on hand, “from the folks who create the math models and code”..they are out there so your choice if you want to learn more or continue on with what I call “Algo Duping” to base your opinions and allow further attacks of the “Killer Algorithms” to permeate.
Here’s another blog post she wrote a while back and I share the same thoughts…and so does Larry Ellison for that matter as he talked about in his recent interview when he said banks have over 30 years of your data, worry about private industry and NSA second as far as the use of your data and privacy.
Recommended Reading: “Where’s the Outrage Over Private Snooping?” “The Killer Algorithms Have Teeth & Don’t Care Who They Might Bite
If you look through the table of contents you can see some very important topics discussed, ones that get over looked, like the big addiction to metrics, framing problems incorrectly, the “Smell Test of Big Data”, and more. The smell test is probably the most important as if you are not sniffing when something doesn’t sound right, then you will more than likely miss the boat. Again she stresses this is being a skeptic and not a cynic.
The essay is available for free to download via O’Reilly with registration at the site. I highly recommend it as again a lot of what she states here relates to the Algo Duping and Killer Algorithm discussion I have on this blog which is what I have been calling it for a couple of years and put together a group of videos created by people smarter than me. I have had some very good feedback from the likes of the NISS (national institute of statistical science) and others on the Killer Algorithms topics & videos as well. You can see one of Cathy’s videos at the link above as well as the one the footer here.
"Data is here, it's growing, and it's powerful." Author Cathy O'Neil argues that the right approach to data is skeptical, not cynical––it understands that, while powerful, data science tools often fail. Data is nuanced, and "a really excellent skeptic puts the term 'science' into 'data science.'" The big data revolution shouldn't be dismissed as hype, but current data science tools and models shouldn't be hailed as the end-all-be-all, either.
People come to data science in all sorts of ways. I happen to be someone who came via finance. Trained as a mathematician, I worked first at a hedge fund and then a financial risk software company, each for about two years, starting in June 2007 and ending in February 2011. If you look at those dates again, you’ll realize I had a front row seat for the financial crisis.
I worked on a few projects in algorithmic trading with Larry Summers at the hedge fund and was invited, along with the other quants at Shaw, to see him discuss the impending doom one evening with Alan Greenspan and Robert Rubin. It honestly kind of surprised and shocked me to see how little they seemed to know, or at least admitted to knowing, about the true situation in the markets. These guys were supposed to be the experts, after all.
I left finance pretty disgusted with the whole thing, and because I needed to make money and because I’m a nerd, I pretty quickly realized I could rebrand myself a “data scientist” and get a pretty cool job, and that’s what I did. Once I started working in the field, though, I was kind of shocked by how positive everyone was about the “big data revolution” and the “power of data science.”
Not to underestimate the power of data––it’s clearly powerful! And big data has the potential to really revolutionize the way we live our lives for the better––or sometimes not. It really depends.
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