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How Do You Decide When Can Doesn't Mean Should?


An old proverb states, “Fire is a good servant but a bad master.”  Put simply, it means that when controlled, fire is a life-sustaining element.  We need it for warmth, to cook food, to make tools, to clean and sanitize our living areas.  We cannot live well – or long – without it.

However, when a fire spreads beyond our control, we all know what a destructive force it can be.  One has only to look at Australia or Yosemite, San Diego or Ventura to see the loss of lives and homes involved.

As technology professionals, we constantly develop (or evaluate) new ways of delivering value to our end users. I remember the dawn of the internet and what a miracle it was.  Yes, I recall the pain of dial-up.  Of being thisclose to loading a web page, only to have someone in your family pick up the phone to make a call while you hollered “NOOOOoooooooooooooo!” in the background, knowing it was too late, and you would have to start all over again.  It was slow, especially by today’s standards. Still, an inconceivably large world had been placed at our fingertips, and we were hooked.  There was no going back.

Then came the advent of social media.  We were able to keep up with our families, no matter where they were in the world.  One of my brothers went on deployment to Iraq many years ago. Not only could I keep up with him, I met a medical professional online who worked at the hospital that served his unit and received updates from her.  I thought of my grandpa, who fought in WWII, and how my grandma was lucky to get a letter at all.  I was so grateful that I didn’t have those awful waits.  I enjoyed social media and loved meeting people through it.  Some of them have become friends that I have stayed in touch with for over twenty years.

Over time, though, we have seen great advances in technology used for purposes that we might not have intended.  We have become increasingly conscious of how our data is accessed – and used – and by whom.  Not long ago, an app online purporting to show what you would look like as an old person went viral.  Not long after that, it was reported that under the pretext of playing a fun game, data was being collected and stored by some people whose intentions were less than honest.  As my old network security professor would have pointed out, “If you don’t pay for the service – you are the service.”

More recently, the New York Times wrote a very interesting article on one way facial recognition technology is being leveraged.   It brought to the forefront of my mind something that I had subconsciously thought about for years.  As data professionals, we want to provide the maximum value to our employers.  But has the time come to consider the warning of the fire proverb?  Should we try to consider the long-term implications of our recommendations before making them?  Should we advocate for measures to keep the fire from getting out of control? Do you think it is too late?  If these issues concern you and you would like to put guardrails around some of this, how would you propose to go about it? 

I’m sending this out as a “message in a bottle” blog to ask you whether this is something that you consider, or whether you think it is a potential problem at all, and to discuss it here.  I’d love to hear all of your thoughts.

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