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Speaking AI (artifical intelligence)


You're talking but I can't hear you.  Everyone can certainly understand this condition; the "Peanuts" parents who sounded exactly like your own, your significant other while you watch your favorite game on TV, or most importantly a work colleague or partner which you are attempting to communicate a thought or vision.  All of these, and many other examples, have plagued our organizations long past the childhood game of telephone (passing your words to another, and on to another, etc.). 



So what?  What has changed?  Besides the velocity of products hitting the market, the requirements that we have for our business now needs to be interpreted by data scientists, yet another abstraction layer from the field conditions.  Think about this example;

  • TODAY:  we often think in binary terms, if "x" happens do "y" …  take a sales person seeking potential leads by searching a system for the last time we made contact
  • TOMMORROW:  consider variables that you may have discounted due to the complexity of obtaining and correlating the information.. In contrast to our sales scenario above, proactively feed leads to a sales person in real time using algorithms designed to increase the odds of closing a sale, looking at email sentiment, appointments, breaking news or social trends.



After several opportunities to work with data scientists on projects over the last few years, I believe that one of the most effective forms of communicating thoughts is via "storytelling".  Consider this approach and put down, on one page, your thoughts related to what a machine learning algorithm can and should do for you.  Sections may include a goal, impact, before, driving the point, conclusion, after.  Dare to dream, think about all of the factors which impact intelligent decisions.  If you were to replicate your thought process and reflect on what you would do different given "x" results in the future, you are on your way to "speaking AI"



The time is now to start building strong AI capabilities as these take time to perfect and farm useful data (to be used for predictive and prescriptive modeling) in the future. 



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Next post:  in the "people" business can you really measure performance?

Questions?  feel free to leave replies or direct message me

See all of the "last mile worker" posts here:  http://lastmileworker.com

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