Artificial Intelligence is a too-often mischaracterized nomenclature used by many business development and marketing organizations in claims their company is operating in that space. Most AI-claimed products actually provide historical reports of activities that already occurred, rather than real analysis of the environment to predict future business and mission impacts, and their AI analysis is too often just the same report with more sources.

A number of leading edge analytic tools are capable of doing much more than report generation by looking at outlier data points to discern changes or previously unknown information that could affect business decisions. Their secret sauce is in providing intelligent systems driven by thousands and millions of small insignificant pieces of information on their own that put together create a broader, deeper picture from which better decisions can be made.

As technology experts talk today about future intelligent decision systems, they use the term Artificial Intelligence (AI). I prefer the term Intuitive Intelligence (or I2). This implies that intuition must be a part of that intelligent system. There is some science that indicates men and women often arrive at decisions differently. Men are inclined to stick with the facts and make a decision based on what the black and white data tells them. Women are often able to incorporate intuitive (gray area) feelings in the decision process versus a data-driven only perspective. Intuition is an ability to understand something based on a feeling, but in reality that feeling is driven by a multitude of many, many (many) small pieces of often insignificant information that are assimilated in a way to make a better risk assessment. (Your mom told you she just had a feeling about going out with those friends, but really meant she was processing a whole life’s worth of experiences in that assessment. Dad might have been sold on the car they were driving and that they talked to him pretty nicely.)

These are neither universal truths, hard absolutes, nor intended as misogynous musings. It is not to say that men can’t or don’t leverage that same intuition-based process or that women only make decisions based on a gut feeling. Rather it is the difference between leveraging better those small unknowns in the background in a way that produces a better perspective around the ultimate outcome. Intuitive intelligence brings far more to the table because of the millions of small and often unknown pieces of information, often related directly to better interpreting the risks involved that must affect the decision outcome. And this raises the question of whether intelligent systems should be more intuitive-driven or data-driven decision systems.

Christine Legarde, the current head of the European Central Bank, has stated on numerous occasions that perhaps if Lehman Brothers were Lehman Sisters, with more women as part of the decision process, much of the financial crisis in the 2008 – 2009 might have been avoided. The reasoning is that more intuitive risk-taking mechanisms would have kicked in and perhaps the discussion at the financial board-level would have minimized much of the risk associated with actions the financial organization was taking.

So do we want our future intelligent systems – deep analytics, data-driven, artificial intelligence, intuitive intelligence – to be more like our mothers or more like our fathers. It is a great IT discussion, but in the end, the real question is should future intelligent systems be more inclined toward intuitive-risk-assessment than just-the-facts decision driven systems. Artificial intelligence is decision-tree algorithms based on (and learning from) solid facts. Intuitive Intelligence goes a step beyond and derives from many more subtle inputs about risk assessment and potential outcomes. Does it matter whether AI is more male driven than I2? Many AI projects are dominated by male-thought models and tend to be black and white (on-off coding). Intuitive Intelligence (I2) must reinvent the algorithms to better assess the gray (risk) areas and related outcomes.

Sorry, dad. I’m going with mom on this.