Learn Something For Its Learning Potential, Not Its Earning Potential

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Publication date:

July 07, 2021

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Parents often ask me whether their kids should learn computer coding skills. The short answer is that they should. Not that coding will be the only job remaining in a future with ambient intelligence. Rest assured, it will not be. More importantly, consider these two facts. First, computers are already being trained to code themselves and, hence, coding jobs might well go down the same path towards obsolescence we see other jobs take. Second, most future job opportunities are still well below the horizon. Hence, looking at what to learn should not be done through the lens of the appealing jobs that exist today. When facing an uncertain future, you do not bet your own future on the certainty of today. Instead, you invest in your agility.

In line with this, my argument for why kids should acquire coding skills has little to do with any specific job prospects, current or future. In fact, I believe that job prospects are no longer a useful guide in what we should learn. The reason for that is that most, if not all, jobs and careers are becoming increasingly fragile and susceptible to obsolescence or radical restructuring. Letting these jobs define learning needs is looking at the future through the rear view mirror.

Radical innovations, rapid advances in the sciences, and perpetual disruption are making many jobs obsolete and/or ripe for radical restructuring. Just think of a radiologist. With the performance of medical imaging and recognition technologies rapidly approaching – and in some cases already surpassing – human accuracy, do we still need them? We currently need them to label the images that train the neural networks that drive the recognition algorithms and perfect their diagnostic capabilities,  but then what? What about lawyers, judges? On the latter, note that parole boards are already relying on AI systems to decide on whether to let an ex-convict back into society.

As we go down the list of jobs, we (should) quickly realize that few if any are safe in the digital world. The reality is that most of us do jobs that smart algorithms will be able to do better, faster, error-free and, it must be said, with no human drama. All jobs are becoming transient and, because of this, a career or a profession is no longer a good barometer for how to design ones learning path.

Note, furthermore, that no radiologist or judge was trained in any of the technologies that could replace them. That is just another indication that work-based education – which much of higher education has become –  might have run its course and is in need of a major overhaul. Going forward, education should aim for professional agility and not slot students into ever narrowing career paths that might well be dead ends.

Computer coding is a good example of what education should be aiming for. It is a job skill but in the process of acquiring that skill, one develops competencies that are much more versatile. Hence, coding does not necessarily lock you into becoming a coder. Furthermore, as a basic skill of the digital era, coding gives you a peek behind the curtain where many future jobs are still hidden.

Learning to code is acquiring a new language that will enable you to communicate with computers. It also introduces you to algorithms and how they operate. As we are all becoming more dependent on computer algorithms (and increasingly run the risk of being replaced by them), having a basic understanding of how human knowledge and intelligence is programmed into computers is invaluable for all.  On one hand, it is part of becoming digitally literate; on the other, it offers a glimpse into what algorithms are not able to do and, hence, point to areas where human intelligence will be needed to supplant or supplement them. Those are the very areas where the jobs of the future are hidden.

What is important to realize is that In the process of acquiring coding skills, you learn other skills that are relevant well beyond the narrow coder career path. This is the learning potential in learning computer coding. The reason I support coding is the same reason why my generation had to learn algebra in school. When we did slug through the equations, none of us could quite figure out what the use of all that painful stuff was. After all, none of us ever saw any of our parents solve any equations in their jobs!

The point is that algebra, as coding does today, teaches you how to break down complex problems into logical and solvable pieces. In other words, it trains you to think in a structured and an analytic way. That is an invaluable skill to have in a world that is changing rapidly and becoming increasingly more complex.

In a reality where jobs/professions are becoming more fragile, learning agendas should focus on skills and competencies that are versatile. The message is clear: as we gear up for lifelong learning, all learning should focus on, and be motivated by, its learning potential and not just its earning potential.

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