Bryan Beverly

When Good Algorithms, Tech Stop Being Good

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bkbeverly
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Re: Losing data to time
bkbeverly   3/21/2017 12:27:05 PM
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@Kq4ym - agreed. If data retention is mandated by law or litigation, or can be written off as a tax loss, then you know ahead of time. But otherwise - who knows?

kq4ym
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Re: Losing data to time
kq4ym   3/20/2017 8:49:51 AM
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Yes, keeping old data and then making good use of it may very well be beneficial, but trying to figure out ahead of time which datat to keep and then testing to see if the return on investment is worth it can be a tricky piece of business.

bkbeverly
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Re: Losing data to time
bkbeverly   3/17/2017 11:33:45 PM
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@Lyndon_H - The thalidomide crisis - yes - perfect example. That makes me remember the problems caused by DDT. I believe that economists and lawyers call those 'negative externalities' (as in The Tragedy of the Commons). I know of someone whose fingers were deformed because her mom took thalidomide.

Lyndon_Henry
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Re: Losing data to time
Lyndon_Henry   3/17/2017 4:59:50 PM
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..

Kq4 writes

Doing no harm may be the goal, but when big chunks of money are involved, things often go astray. While "a cure that is worse than the disease," is nothing we intentionally plan, those plans get a bit out of hand when unbridled curiosity or the promise of great profits seem to be ahead. Perhaps social scientists should be involved along with data scientists in planning and program design?



 

My own thoughts go in a somewhat similar direction. When it comes down to it, just about any new technological development can be applied to harmful purposes – it all depends on whether individuals or agencies with maleficent intentions can get their hands on it and deploy it to those purposes. The airplane was a revolutionary invention that speeded passenger travel and mail delivery – but it also became one of the most formidable and horrific weapons ever devised. Likewise, lasers can be deployed as excellent surgical tools or fearsome weapons.

In my mind, a more clear-cut case of "technological iatrogenesis" would be something like a new anti-cancer vaccine that turns out to engender a different serious disease (say, ALS or Huntington's) in recipients. The thalidomide disaster might also fit in this category.

..

bkbeverly
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Re: Losing data to time
bkbeverly   3/17/2017 4:44:09 PM
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@SethBL - So noted! To use a culinary metaphor - borrow the receipe but season to taste. Great 'cautionary tale' - thanks!

SethBreedlove
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Re: Losing data to time
SethBreedlove   3/17/2017 2:19:54 PM
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I think every industry borrows technology from other industries and that includes algorithms.  When I do an industry analysis I'm always borrowing from other analyes but with the knowlege that it will have to be re-crafted over and over to fit it's new purpose.  This type of behavior should be encouraged because that is one of the ways research and technology grows.  However, it should only be done knowing that it is a new starting point and may not be as effective or have a desirable outcome.

bkbeverly
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Re: Losing data to time
bkbeverly   3/14/2017 10:27:38 AM
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@kq4ym - Interesting suggestion! Certaintly having an interdisciplinary team brings multiple perspectives to the table and reduces the risk of TI. The challenge is to find the right number of people - too few and you don't have enough perspectives. But too many and you never get any work done. And to your point, when the leadership has tunnel vision on revenue, then wanting to see any other view is a hard selling point. But yes, I think your suggestion is great.

kq4ym
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Re: Losing data to time
kq4ym   3/14/2017 8:36:59 AM
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Doing no harm may be the goal, but when big chunks of money are involved, things often go astray. While "a cure that is worse than the disease," is nothing we intentionally plan, those plans get a bit out of hand when unbridled curiosity or the promise of great profits seem to be ahead. Perhaps social scientists should be involved along with data scientists in planning and program design?

bkbeverly
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Re: Losing data to time
bkbeverly   3/13/2017 1:25:19 PM
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@Jim,  Excellent point.  The complex system architectures of today (and associated multiple vendors who promise perfect system integration – but that is for another topic ...) are designed for high output, low costs, ease of use, and easy maintenance of the components. Hence DR is less of a concern, more so in the private sector.  As it relates to the feds, those agencies whose output/products are critical (akin to only essential personnel should come to work on snow days – which suggests that most people are not essential – but that is for another topic ... ) to the nation's welfare, do have DR plans in place. Actually the Labor Department has annual mandatory risk and security awareness training for federal and contract employees. So to your point, I am guessing that the degree of risk exposure, costs outweighing the benefits or the arrogance of thinking that nothing could go wrong is what is behind a decrease in the attention paid to DR in general.

Actually, your statements just raised an interesting question: There is so much talk about the dollar value in data, but if there is no DR plan in place, then are those valuation statements true?  Seems to me that if data is the goose that lays the golden eggs, then you might to store a DNA sample so that you could clone it. But please note that my career period in business development makes me suspicious of marketing language of the data evangelists. I am wondering if the lack of DR means that data assets are overvalued or that it won't be a concern unless a big problem occurs. Yeah – if your think of DR as data insurance, and if there is a decline in the implementation of DR, then then have to wonder if DR is overpriced or if the data assets are undervalued?

Thanks Jim – I think I smell a future post cooking.

James Connolly
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Re: Losing data to time
James Connolly   3/13/2017 12:02:55 PM
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@Bryan. I haven't seen any data about it recently but I recall that a few years back research showed that the percentage of companies that actually ran true disaster recovery tests is low, like well below half. At one time when computing was centralized and you could have all of your key function backed up by a hot site I think the number of organizations that could run a true DR test probably was higher.

Imaging doing a companywide DR test today? While you probably could do it on a single application or function, doing so companywide would require testing recovery with many different services -- data feeds, SaaS apps, remote access systems etc. -- and so many different stakeholders and department level IT teams. It would seem that just planning would take so long that half the configurations and people would change before it was time to test.

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