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Knowledge management trends: cognitive learning technologies

In a recent post “5 knowledge management trends for 2016”  I announced that Cognitive technology and machine learning have demonstrated that they can become leading catalysts for change in knowledge management models as executives begin to embrace them in order to overcome barriers and ensure growth-profitability.  

The field is advancing to such point that machines can integrate knowledge in a very similar way to humans.  “Integrating knowledge, our fourth skill, represents the much more complex ability to pull together information from many sources and reach accurate conclusions” (Diaminis and Klotler, 2015).  As opposed to Intranet-like technologies and other form of repositories, the development of cognitive learning technology is allowing machines to reach new levels of understanding and assist decision making. One current example is Watson, a cognitive computing system that uses natural language processing and machine learning to reveal insights from large amounts of data.

Many researchers have proposed models based on the analogy brain-is-like-a-computer since the late ’60s.  From that point onwards many investigations and scientist have undergone various efforts to replicate human processing and models such as ANNABELL have demonstrated significant advances. The ANNABLE model is a cognitive architecture entirely made up of interconnected artificial neurons, able to learn to communicate using human language starting from a state of ‘tabula rasa’ only through communication with a human interlocutor.

The question is: can such systems help businesses to significantly boost learning, avoid reinventing the wheel moments and foster collaboration?  Companies like Automation anywhere (https://www.automationanywhere.com) are already applying this technology for faster and smarter process automation and specialists are already producing more elaborate solutions like solving China´s smog problems. An IBM team is using complex computer models and machine learning to calculate how pollution will spread across the city. The researchers can now produce pollution forecasts, with a resolution of a kilometer square, up to 10 days in advance. (https://www.technologyreview.com/s/600993/can-machine-learning-help-lift-chinas-smog/).

The last example incorporates Watson and it seems that significant advances are coming from IBM. Anyone who has seen Watson win at jeopardy can guess where the field is moving towards. In another note, PC world reported that Watson is using stores of data from ACS and IBM in order to offer personalized advice to cancer patients and answer questions using a combination of voice recognition and natural language processing (http://www.newsmax.com/TheWire/ibm-watson-cancer/2016/04/13/id/723686/).

IBM has even created a Chef version of Watson and recently a few weeks ago in Spain, people witnessed the first cognitive meal being prepared. Basically over 10,000 recipees were uploaded and “Watson searches for patterns in the existing recipes and combines them with an extensive knowledge of the science behind food pairings to come up with ideas for unexpected combinations” (http://www.bonappetit.com/entertaining-style/trends-news/article/chef-watson-app). If you want to play around with Watson “Chef” to see this technology at work, I recommend you head down to https://www.ibmchefwatson.com/.

The above examples demonstrate that cognitive technology is already proving valuable and it is not only capable of assimilating knowledge but it can provides us with suggestions and possible answers. Both these elements combined will engineer a new method for KM that needs to be investigated further since no examples are being generated from knowledge management teams.  We must bear in mind that the inclusion of this technology will sweep away the old IT fabric which dresses KM in the form of intranets, wikis, forums and web 2.0 elements. From this point onwards we might even suggest that handling tacit knowledge won´t be a problem as artificial intelligence gets smarter. The price for developing this type of systems is also not high since in the case of Watson you can download the necessary API´s required to make your own version.

Technology should not replace human processes, intuition and experience, but rather, find a suitable source of exploitation so that human judgement is multiplied and not just replaced by expert systems. Combining both will open the path towards myriad solutions in multiple fields and help reach a better future. In summary, the cognitive technology  will radically transform the way knowledge management is handled and the future is now.

© Jose Carlos Tenorio Favero

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