As Donald Rumsfeld reminded us in 2002, human knowledge may be divided into known-knowns, known-unknowns, unknown-knowns and unknown-unknowns:
Learning can be thought of as the migration of items from the two quadrants on the left to that on the top-right.
All four quadrants are fascinating - the ingestion and assimilation of countless sensory data (Known-Knowns), its encoding and storage (Unknown-Knowns) and our insatiable, life-long thirst for knowledge (Known-Unknowns) - are all rich subject areas in their own right. They are also all limited in some way by the human brain. Unknown-Unknowns are not limited.
If we could convert the right unknown-unknowns into known-knowns, we’d enhance the capability of individual, company, our entire species. But how? In life and business we occasionally stumble upon exquisitely apposite information. Such serendipity is delightful largely because it is rare. But it’s not efficient.
The problem of mining the unknown-unknowns will be solved by AI-powered recommendation systems. With just a little information about a user, extensive information about a given domain and a feedback mechanism, AIs now make useful, shrewd, personalized recommendations in many fields. Spotify’s Discover Weekly algorithm generates a personalized playlist which strikes the balance between fresh and familiar for over 100m people. Amazon, Facebook, LinkedIn, Tinder, Twitter, Skyscanner and eBay do the same in their respective domains. Machine-learning recommender systems are now supporting medical decisions.
What if the hundreds of millions of knowledge workers in the world were able to systematically and scalably acquire the right information, data, hard skills, soft skills and knowledge for them? It will happen in the next 10 years. In this way, artificial intelligence will bring an imminent step-change in human intelligence and potential.
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