Gift cards, serial numbers and hard technology
I bought someone a digital gift card the other day. That’s generally a bad idea, since there’s so much waste and breakage, but it was the right answer to the problem in the moment.
The code the person would have to type in to redeem the card was: X5LMFP478DRYTHQY
I’m sure that the team who worked on creating a secure platform for the transfer of billions of dollars of transactions was proud of the hard work they did.
Except no one wants to type this in, and it’s incredibly impersonal.
It could have been just as secure if there was a list of 1,000 words and the code was five of the words. All the words could be positive and easy to spell and remember. Typing in “happy love birthday celebrate friend walrus” is going to be more memorable, fun and engaging, and the computer is smart enough to ignore the spaces.
The day before, the tech support folks at a different big company wanted me to read off the serial number on the bottom of a device. I’m sure the tech folks were proud of the check digits and other elements that were embedded in the serial number, which was printed in grey type considerably smaller than this blog is written in. It included a 0 and an O as well as a 1 and perhaps an l.
And the serial number for my oven requires lying on the floor to read it.
In all of these cases, the organizations failed because they decided that humanity and technical issues don’t overlap. These minor issues I’m complaining about are nothing compared to the life-changing impacts that technology that avoids the hard problems can create.
In medical school, they spend days teaching people to operate on lungs, and no time at all helping young doctors learn how to get their patients to stop smoking and get vaccinated. The technologists forgot about the human issues.
This is most glaring when we go near the edges of a bell curve. Disabled people or folks who are out of the mean in any way are shunted aside by what the busy but blindered tech people think is important. A captcha that doesn’t work, machine learning that doesn’t learn well, systems that don’t serve the people who need them…
Technology that doesn’t solve a problem for the people using it isn’t finished yet.