Predictive 'E'verything: Is this a Good Thing?


Ever since Amazon started making suggestions as to other things we might like to read, the holy grail of the tech industry has been to give advertisers the ability to guide us to things we did not know we needed until they exposed them to us. The benefit of this type of predictive navigation to us was supposedly to open our eyes to expanded possibilities, and make it easier to find things that might give us personal pleasure or tools to enhance our careers. 

As a result of a host of news services from the likes of Cue, MindMeld, and now Facebook  –  and of course Google, with predictive search and its new In-depth Feature capabilities –  we seem to be approaching advertiser nirvana. With so much about our behavior now in the cloud and therefore accessible for tabulation, extrapolation, correlation and presentation, predicting what we want based on context and content is going mainstream. Unfortunately, that might not be a good thing.

While I understand the desirability of having such predictive capability serve as a filter from all of the online disruptive noise—too many e-mails, alerts, SMS text, voice mails, chats, et al—the reality is a more messy world might be preferable to an algorithmic-based one. 

Years ago I read what is still considered one of the definitive works on the subject of organizational learning, The Fifth Discipline: The art and practice of the learning organization, by Peter Senge, the director of the Center for Organizational Learning at the MIT Sloan School of Management.  The good professor presented a useful construct. He said that the way we and organizations learn is by:

  • Really knowing the things we know
  • Getting educated on the things we know we do not know
  • Exposing ourselves to the things we did not know we do not know

His point was that while you need to have a culture based on all three, real innovation and true learning arises for the most part on the last two. That is where all of the helpful hints based on our digital detritus being posited in the cloud for apps and other third parties to digest and reformulate comes in. What they will be feeding up, with increased precision over time and likely to be embedded in such things as location-based services, along with such mundane things as automatic deletion of things that some computer decides, according to our previous behavior and predilections, is by its very nature a diminution of spontaneity. I would argue it is also a diminution of creativity and hence a possible obstacle to innovation.

There is a disclaimer on recommendations from financial services companies that warns that past performance is not a promise of future results. Human nature being human nature, if predictive searches and the presentation of other things we might be interested in becomes the lazy way out for us to be inquisitive, that would not be a good thing. 

The marketing person in me says “bring it on!” The more I can anticipate your needs, or entice you to need something that had not yet appeared as part of your volition, the better. There is an old categorization of “We are from the government and are here to help” as an oxymoron. Our futures seem to be about, “We are from XYZ and are here to help.” We are even going to have our interactive personal voice assistants abetting the process by whispering sweet nothings in your ears. The next thing you know there will be the accompaniment of what some computer thinks is the type of music that will put us in the shopping mood to help speed along the transactions process.

I will admit that my attitude is likely a generational bias. The digitally immersed younger generations are certainly going to be so comfortable with technology that they might crave what I find disconcerting. 

As with most things, let’s hope that there is a balance. Indeed, let’s hope that that balance is created by humans who respect the need for random exposure to “E”verything, and do not hog our time and virtual space with only what computers think we should be interested in or desire. In particular I hope that Senge’s construct for the way organizations learn and excel does not become a thing of the past.

Edited by Blaise McNamee
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