Learning About EQ by Training an Artificial Intelligence: Three key lessons about growth

by Tom Procicchiani from 6Seconds

Millions of people use Siri to solve challenges every day. Could that kind of computing tell us something about emotional intelligence that we otherwise wouldn’t be able to see? Can artificial intelligence be applied to this field? What could we do with it?

In seeking answers to these questions, we accidentally learned three powerful lessons about emotional intelligence (EQ)… and how people can best learn to put their EQ into action. Can these same principles help us improve all learning and development?

The artificial intelligence creates a new perspective on emotional intelligence

What can data tell us about emotions?

If you have taken Six Seconds EQ test, the SEI, you know it creates a report that includes analysis and descriptions of strengths and weaknesses that can be turned into actionable items.

What if all the data we have collected through the SEI assessment could be used in a whole different way to help us improve our EQ? Enter the EQ Neural Network, a predictive, rather than descriptive, data tool that can help guide future actions. Think Siri for EQ.

In 20 years of activity we gathered a pretty impressive amount of data from the SEI and we always used it to improve the reliability and the efficacy of the tool and to create solutions and ways to actually practice EQ, go into action. This year we started to play around with the idea of branching out from the descriptive statistics to explore the possibilities of predictive statistics

What does THAT mean?? Check out this 2 minute video:

We decided to explore if the data could evaluate a specific person’s Emotional Intelligence profile and identify the best course of actions to improve it, to do so, we used a technology called Neural Network. The results are incredibly powerful. But in addition to developing a tool that makes it easier to utilize emotional intelligence, we found three insights that may be even more important.

Surprising Lessons from the AI

As we worked on the Neural Net, we’ve had a number of surprises. It seems that training our new “Siri for EQ” taught us something beyond our expectations.

Here are three lessons that we can all use to improve learning.

When does the most effective learning take place?

There’s a lot of discussion of the importance of focusing on strengths instead of weaknesses. At Six Seconds, we’ve had an orientation that tapping strengths will create the most benefit.

So when it comes to learning to apply EQ… Does it work best when we choose to focus on our weaknesses or when we leverage our strengths? There are good reasons for both approaches but the literature is not in full agreement about what the perfect recipe is.


The answer is… both.


Actually, in the EQ Neural Net analysis we found that in 3 out of 10 cases, a strength will provide the most benefit. In another 3/10 cases, focusing on a weakness is the key.

More of the time, in 4 out of 10 cases, it’s something in the middle that needs our attention.

We found this concept fascinating, it challenges us to break our patterns, as machine learning can do a lot of times. We need to shift from this “strengths/weakness” dichotomy to a broader, more comprehensive approach. Looking at our full range of capabilities can change the way we plan our learning pathway… and most likely this will change how we feel about the learning process as well.

What’s the “streamlined” system for developing people?

In the past, when we’ve looked at EQ profiles, we’ve seen reports from two people that are fairly similar… and made an assumption that they would both need a similar solution. Take a look at these two graphs:

“Ali’s” EQ scores

“Scooter’s” EQ scores

As you can see, both have very similar high and low scores. From years of experience, one of our certified SEI Assessors can easily make recommendations for these two clients. Both have strengths in self awareness, they evaluate carefully, and they have a strong purpose… and may be challenged when it comes to Navigating Emotions.

So, if we were coaching them both about, let’s say, Effectiveness, we might consider very similar recommendations for each one (such as using that strong emotional literacy to notice emotional cues about staying focused on what’s important). But when we put these two results into the EQ Neural Net, the AI doesn’t see them as all that similar. Here’s what the AI offers each one as an optimal path to use emotional intelligence for Effectiveness:

“Ali’s” Neural Net recommendations for Effectiveness

“Scooter’s” Neural Net recommendations for Effectiveness


In other words, even the tiniest differences in the shape of the profile matters. A slight change in the EQ competencies scores and gaps makes a big difference for the AI.

While a generalized approach will reduce complexity… and it may work well for some people… optimal learning is personal. When it comes to a single person, we’re all different, unique human beings, and whatever worked for you might not work for me.

Perhaps this is evidence for Six Seconds’ principle: No Way is The Way. The most powerful growth comes from an approach that’s uniquely you.

We’ve all heard that there’s no such thing as multi-tasking, so does it mean we should just focus on one thing at a time? When it comes to utilizing emotional intelligence, it turns out that narrow focus may not be the best solution.

Looking at the data from the EQ Neural Net, we noticed that the impact of focusing on just one skill at the time is far weaker that the value of developing three together.

To a certain extent it’s common sense that there is a benefit to working on multiple skills to make a difference, however it’s intriguing to see that targeting a wider range of competencies together is preferable to selecting a single one. It tells us that, at least as far as working on Emotional Intelligence, there is merit to having a systemic approach.

In other words, don’t consider one competency as a stand-alone area to develop. Instead, think about all your skills as intertwined. Look for the links, all the pieces of the puzzle that can come together to make learning effective.

Artificial intelligence is spreading more and more and in several different contexts. It still remains a controversial topic because it brings up the inevitable dispute of machines versus human mind. Will mathematical algorithms that are able to learn from data and improve themselves, exceed the accuracy of our insights and expertise?  It may turn out that a tool like the Neural Network actually helps us be more present and effective in face to face interactions, but that depends on how it is used.


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April 27, 2017

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