Alex Gray, a Senior Writer at Formative Content, notes “By 2020, the Fourth Industrial Revolution will have brought us advanced robotics and autonomous transport, artificial intelligence and machine learning, advanced materials, biotechnology, and genomics.” Gray continues, “Five years from now, over one-third of skills (35%) that are considered important in today’s workforce will have changed.”
Becoming An Expert Has Put You At A Disadvantage
If your skills are no longer important, how will you make a living? What will be your life’s purpose? Could Gray be wrong in her assessment, perhaps it’s just an opinion?
Then panic begins to snake its way into your brain, and you discover, “I haven’t had to learn anything new in decades.” While the questions you have asked are an attempt to rationalize the facts, the actual problem is you.
Professionally you have become an expert. You have made the decision that you have learned all that you need to learn to do your job well. You have grown comfortable in the knowing mindset, which makes you less open to new ideas, other possibilities and even questioning your world view.
You have habitualized the application of your expertise. Neurologist Robert Burton calls this phenomenon the certainty epidemic. Burton explains, “Your resulting sense of certainty feels like the only logical and justifiable conclusion to a conscious and deliberate line of reasoning.”
Unfortunately, you have limited your conclusions based solely on a finite subset of available data. The single source of truth has served you well the World is evolving, because of the fusion of technologies. While this blurring of technologies speaks to a number advances between the physical, digital, and biological spheres, they also give birth to a series of complex problems that will require new levels of critical thinking and creativity.
Charlie Munger Says You Are Unwise
The long-term treatment for the epidemic is constant learning, specifically building a latticework of mental models. What is a mental model? It’s an explanation of how something works. Your mental model is a theory, a belief, a worldview that guides your decisions making; helping you understand the relationships between events.
I first learned about the importance of mental models from Charlie Munger, vice chairman of Berkshire Hathaway. In a 1944 speech at USC Business School titled “A Lesson on Elementary Worldly Wisdom,” Munger details the importance mental models.
What are the models? Well, the first rule is that you've got to have multiple models because if you just have one or two that you're using, the nature of human psychology is such that you'll torture reality so that it fits your models, or at least you'll think it does.
It's like the old saying, “To the man with only a hammer, every problem looks like a nail.” And of course, that's the way the chiropractor goes about practicing medicine. But that's a perfectly disastrous way to think and a perfectly disastrous way to operate in the world. So you've got to have multiple models.
And the models have to come from multiple disciplines because all the wisdom of the world is not to be found in one little academic department. That's why poetry professors, by and large, are so unwise in a worldly sense. They don't have enough models in their heads. So you've got to have models across a fair array of disciplines.
Remixing Of Ideas Is Your Only Solution
So what are the multiple disciplines that you must focus on? Microsoft founder Bill Gates suggests he would place his focus on:
- Artificial Intelligence
Where do you being learning about these topics? The most straightforward solution is to read, but you have to read wide then deep. No, blog posts won’t do, the coverage is shallow. I am referring to books, for example:
- Artificial Intelligence — “The Master Algorithm,” by Pedro Domingos
- Energy — “Energy and Civilization: A History,” by Vaclav Smil
- Bioscience — “The Vital Question,” by Nick Lane
As you begin assimilating information questions should start popping into your head:
- Why does artificial intelligence need neural networks?
- Why can’t we optimize our resources by creating regional electricity grids?
- Why couldn’t we replace all of the tissues in the human body through engineering?
Once you have healthy list of Why questions now have some fun by asking What if:
- What if we could build learners that build neural networks?
- What if we could build self-replicating electricity grids?
- What if nanobots could repair the damaged tissue?
Now we are being to build interest in learning more about the Why and What if scenarios, but the How is what fuels the latticework of mental models:
- How do we build an advanced algorithm that builds neural networks?
- How will self-replicating electricity grids be funded?
- How will we program that nanobots to only repair damaged tissue and leave the healthy tissue, alone?
The exercise is designed to help you see past the conventional answers and seek out the speculative ideas. Ideas that might not even, at least on the surface, have a natural connection. Author Warren Berger notes, “What If questions — often involves the ability to combine ideas and influences, to mix and remix things that might not ordinarily go together.”
The 10,000-Hour Rule No Longer Works
I know this is a lot of work, but that is how you build new mental models. That is how you inoculate yourself against, your skills being unimportant in five years. Specifically, that is how you build valuable skills. The World Economic Forum explains that in 2020 these will be the most sought-after skills:
- Complex Problem Solving
- Critical Thinking
- People Management
- Coordinating with others
- Emotional Intelligence
- Judgement and Decision Making
- Service Orientation
- Cognitive Flexibility
Do you currently have any of these skills? Do you have mastery over that skill? When I say mastery I am not referring to expertise or the 10,000-hour rule which was popularized by Malcolm Gladwell, I am referring to having the competence of a skill so you can help solve someone’s problem.
Being able to solve someone’s problem is always an in-demand tool. If you have the rich latticework of mental models, you can summon that knowledge to, “combine ideas and influences, to mix and remix things that might not ordinarily go together.” You might come up with a solution to a complex AI that has its roots in bioscience or solves a complex energy problem that has roots in AI.
You must take ownership and build your understanding of not just how one thing works but how lots of things work. You must fight the natural tendency that dictates, “to the man with only a hammer, every problem looks like a nail.”