Are You Smarter Than a Smart Machine? Why “old smart” is the new stupid
The concept of being smart enters our lives early—as soon as a parent or loved one praises us by saying, “Oh, you’re so smart!” As we proceed through school, smart means getting high test scores, making fewer mistakes, and giving fewer wrong answers than other students. That standard continues in many of our workplaces, in which employees are encouraged to act like machines—to be efficient, mistake free, and more knowledgeable than other employees. How much you know has been the way to succeed in the knowledge economy.
In a world of smart technology, however, that standard of smart is becoming obsolete for humans. Already smart machines can remember and recall information faster and more accurately than we can. As the shelf life of knowledge becomes shorter, smart technology also will be able to generate and process more new knowledge faster and better than we can. A well-known example of technology becoming smarter than us is IBM’s Watson beating two Jeopardy champions in 2011. Another more recent example is when AlphaGo, a computer program created by Google’s Deep Mind artificial intelligence company, beat a South Korean Go master four matches to one in the ancient Chinese strategy game in 2016. Smart machines will always be smarter than us if the quantity and accuracy of knowledge is the standard.
Because of technology advances in artificial intelligence and smart machine learning, leading researchers Frey and Osborne at Oxford University predicted in 2013 that 47% of U.S. jobs have a high probability of being automated over the next 16 years. In 2015 the Bank of England’s chief economist predicted that 80 million U.S. jobs could be lost to automation over that time period. The consulting firm McKinsey has stated that upwards of 45% of job tasks done today already could be automated with current technology. To put that in context: the United States lost about seven million manufacturing jobs to automation and globalization over the last few decades.
We are on the leading-edge of a Smart Machine Age in which humans will only be needed to do those jobs that technology can’t do well. The consensus among experts is that those jobs will require higher-order critical thinking, creativity, innovative thinking, high emotional engagement with other human beings, and with respect to trade jobs: real-time problem solving and manual dexterity. Those higher-order thinking and problem solving jobs will require people to excel at iterative learning—through trial and error. In that environment, what you know will not be as important as how you learn, think, and relate to others and making mistakes will be inevitable. As such we need a new definition “smart” that will help us excel in the Smart Machine Age. We need a NewSmart standard that is measured not by quantity but by the quality of your thinking, listening, relating, and collaborating skills.
How do you become NewSmart?
- Join “Learners Anonymous” by accepting the science that clearly states that we all are suboptimal thinkers, listeners, and collaborators by nature and nurture. We tend to be reflexive in our thinking and seek to confirm what we already believe. We tend to be close-minded and make big generalizations based on little data. We tend to have high levels of confidence that we are right and be emotionally defensive when others challenge our thinking. We seek affirmation from others that we are “smart,” and, thus, we tend to avoid new or challenging situations in which we may make mistakes or look bad. We avoid looking stupid at all costs, which actually impedes excelling at the skills that humans will be needed to do in the Smart Machine Age.
- Work to improve the quality of your thinking, listening, relating, and collaborating skills. To start, you should adopt two mindsets: (1) “I am not my ideas” and (2) “My mental models (my stories of how the world works) are only my stories based on my limited experiences—they are not reality.”
- Accept the science that we can’t overcome our cognitive biases or excel at innovation by ourselves—that we need others to help us. Higher-order thinking is a team sport. That means we have to quit looking at others as competitors and understand that in the Smart Machine Age our biggest competition is ourselves. Our success will depend upon how good we are at taking our thinking, listening, relating, and collaborating skills to a higher level of excellence by overcoming our reflexive thinking and emotional defensiveness.
- Treat everything you believe (not your values) as a hypothesis subject to modification by better information. Actively seek disconfirming information, and ask good thinkers to challenge your thinking. Think like a good scientist—be data driven and constantly stress test your thinking.
- Embrace the magnitude of your ignorance and recast mistakes as learning opportunities. In the Smart Machine Age, the biggest mistake will be the failure to learn from mistakes.
- Slow down to be intentional in your thinking and in listening to and emotionally engaging with others. Embrace daily micro-opportunities to make better choices that enable better thinking, listening, relating, collaborating, and learning.
- Work daily at excelling at these four key NewSmart Behaviors: Having a quiet ego; managing your thinking, emotions and behaviors; reflectively listening (listening to learn not to confirm); and “otherness”—taking the time to connect and emotionally engage with others in a way that builds positive regard and trust. Train yourselves to be NewSmart just like a champion athlete or world-class musician trains—through deliberate practice.
As we all frantically race to stay ahead of technology, adopting NewSmart should enable you to manage your ego and your fears in a manner that will optimize continual learning and self-improvement. Good luck in your race.
Have you read?
Humility Is the New Smart: Rethinking Human Excellence in the Smart Machine Age
About the book: Humility Is the New Smart, a book about human excellence – how human beings can excel at the skills that smart machines and smart robots will not be able to do well in the next few decades.
Authors:
Edward D. Hess, a professor of business administration and Batten Executive-in-Residence at the University of Virginia Darden School of Business.
Katherine Ludwig, a research, editing, and publishing associate at the University of Virginia Darden School of Business.
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