Posted by Paul Roma, on October 10, 2016
Cognitive computing is already huge, and it’s likely only going to get bigger. And so far I’ve already observed a few seriously risky views on cognitive computing. Why are they risky? Because if they take hold, they’re likely to lead many to say “I wish I would have” in the not-so-distant future. In this case, the implications of getting it wrong, or simply not getting on board fast enough, are serious. Don’t let yourself get caught saying these things a year from now.
“I wish I would have known cognitive wasn’t ten years away”
Cognitive computing is here now. Let me repeat: It has arrived. It’s not ten years away. It’s not even ten days away. It’s now. Maybe you’re not doing anything with it today–and maybe that’s okay. But at the same time, you should account for its presence.
“I wish I would have known cognitive wasn’t an ‘edge’ technology”
What do you do when a new technology appears on the scene quickly? You deploy it in the margins–give it a test run in some pesky part of the business, see how it works, expand, move to another area, and so on. That’s the definition of “edge” technology. Unfortunately, an edge mindset can be wrong in this environment. Cognitive computing is no more of an edge technology than mobility or cloud computing–it is (or should be) a pervasive technology embedded at the core of the business
“I wish I would have known how to start–and when to scale”
Train and learn, or build and develop? Specific purpose or general purpose? These are the types of getting-started questions that can ultimately shape an organization’s entire approach to cognitive. They should not be taken lightly–which is why many feel a sort of paralysis at the moment it’s time to get underway.
“I wish I would have known what cognitive can really do”
What if you realized too late that cognitive can enable the quantification of historically qualified domains? Or that it could amplify your analysis of existing problems? You’d likely miss out on a ton of potential.
“I wish we would have planned for future changes”
Cognitive capabilities are delivered in the form of flexible technologies that can adapt and learn. But still, they can tend to learn in “straight lines” following the example of the humans that guide them. In a cognitive environment, it’s possible to break this paradigm by combining adjacent data domains to give your models perspective, in much the same way that you might guide a child learning about the world.
Are these the only questions we may wish we had better answers for in the future? Almost certainly not. Expect more twists and turns in the road to cognitive ahead. But at the same time, these are all legitimate, known issues–already. It’s just that they’re clearer to some leaders than to others–a fact that can become painfully obvious as cognitive continues down its restless, surprising, high-stakes path.