Your perspective about vertical learning reminds me a lot of the models of culture introduced by…
Henry Kim

I like your insights about culture and Big Data.

When you describe the oversimplified mental model of “left-right” political ideology and the reluctance to revise it and make it more accurate, that’s exactly what vertical learning is designed to overcome. In many ways, I see vertical learning as a self-correcting process—faulty mental models trigger cognitive dissonance and revision.

The reason why people are satisfied with a mental model which can predict 90% of actual voter behavior, and then are offended and get defensive when questioned about revising the model to increase its predictive power, is because they don’t feel confident about their ability to revise the model. And if they do successfully revise the model, they predict it will take a lot of time and effort and only increase its accuracy to 91%. They get offended because a fight or flight response is triggered. Experiencing cognitive dissonance and ignoring it is a serious integrity violation.

When I work with learners, I help them learn how to revise how they revise their mental models. As they practice and get better at revising their mental models, they feel more capable and confident—and the thought of revising a mental model is no longer scary. Once that happens, it’s a no-brainer to revise a model to bump its predictive accuracy from 90% to 91%. In fact, even if there were no actual gain in increasing the model’s predictive power from 90% to 91%, someone who is good at revising mental models would be tempted to do it anyways out of curiosity.

Figuring out how to work with reluctant learners so they eventually become vertical learners is what I’ve been doing for 20+ years.

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