The future of work in a data-driven world

Are coders the coal miners of the 21st Century?

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In the computer-fueled, innovation-driven, artificially intelligent world we live and work in, you would think computer programmers had it made.

Just last week, “60 Minutes” aired a segment on the gender gap in the tech industry and talked about ways that technology companies are trying to get more girls to learn to code. Breaking the glass ceiling in the technology industry is important — for both women and girls and the industry itself. But in the future world of work, coding is not an end goal; it’s a jumping-off point.

Programming, at its most basic, is a solitary act. Programmers are given objective goals, often not knowing how their piece integrates with others, and often working in environments that are far less collaborative than Hollywood would have us believe. Of course, there are exceptions.

But in a future that may be as little as 10 to 20 years away, those exceptions will need to become the norm. And those coders will need much more expansive skills and operational principles to succeed.

Yes, you can learn the most sought-after programming languages today — ranging from C (with variations C-sharp, Objective-C) to Ruby and SQL. But if you are a geek, you know that the languages computers in the near future speak may bear little or no semblance to their ancestral counterparts.

Self-healing software has been a “thing” for two decades or more. While progress has been made, particularly in areas like network failure and cybersecurity, the full monty has remained the province of science fiction. That may be changing. Artificial intelligence is creating systems with an unimagined future. In this future, we won’t need the army of coders currently required to search millions of lines of code looking for errors. AI-driven software will likely repair itself, identify attacks, and create defenses — similar to the neural networks in the human brain.

While systems do that on their own, what we will need are next-generation, technology-literate thinkers, leaders, and ethicists.

That doesn’t mean we don’t need programming; in fact, we’ll need a lot more. We’ll need everyone to learn programming in the same way children learn the vagaries of their native language. Without that, we can’t communicate. But programming will need to become a bedrock skill, and those who see it as all they need may be left behind.

In a study of skill shifts that could occur by 2030, the McKinsey Global Institute estimated that 1 in 3 workers will need to adapt their skills to a changing world of work in just the next decade. The need for programmers and coders will rise, the study projects, by 55 percent. But the “soft skills” coders do not focus on – cognitive skills, creativity, critical analysis, problem-solving, and a culture of continuous learning – will become significantly more important.

AI systems, networks, and computers will take over more of the mundane tasks that occupy programmers, coders, and systems analysts daily. Where does that leave us? In McKinsey’s view, “The hardest activities to automate with currently available technologies are those that involve managing and developing people (9 percent automation potential) or that apply expertise to decision making, planning, or creative work (18 percent).”

Technology will take over the tasks, but someone still has to set the goals. For a vast number of coders and technologists, understanding how their applications or systems are used is not a big priority. In my tech career, I can count on a few extremities the number of technologists I’ve worked with who ever thought about spending time in other departments of their business, seeing what employees do, seeing what the business makes.

I’m not trying to insult geeks and coders. That’s just the way we’ve rolled for decades. But it won’t be what the future will demand.

Girls should code. Programming should be something we teach in K-12 right alongside algebra, biology, and English. But like those subjects, programming is just a foundational building block of a 21st-century education.

How big is the skills gap?

McKinsey’s survey of 3,031 business leaders in Europe, the U.K., and the U.S. identified areas that would have a significant skills mismatch over the next three years, related to automation and AI adaptation.

Companies that have already adopted some AI and automation say 30 percent of current staff in data analytics, IT, mobile, and web design don’t have the skills that will be needed in the next three years.

Companies that have not moved toward AI see higher rates of skills issues in sales and marketing, production operations, customer service, and supply chain management, among others.

Source: “Skill shift: Automation and the future of the workforce,” McKinsey and Co.


How will organizations resolve the skills gap?

Retraining is favored more by European companies; new hires are preferred in the U.S.

U.S.

Exclusively by hiring                 5 percent

Mainly by hiring                      30 percent

Mix of hiring and retraining      35 percent

Mainly by retraining                 27 percent

Only by retraining                     4 percent

 

Europe and U.K.

Exclusively by hiring                 0

Mainly by hiring                        7 percent

Mix of hiring and retraining       49 percent

Mainly by retraining                  45 percent

Only by retraining                      0

Source: “Skill shift: Automation and the future of the workforce,” McKinsey and Co.

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