Per the dictionary, a skill is the ability to do something well; expertise. The skills acquired through post-secondary education and at-work training are what drive our career success. We are recognized and rewarded based on our skills. The skills that got us to the present, however, won’t take us to the future. Automation and artificial intelligence are increasingly taking over not just routine, repetitive and low-end tasks, but also highly skilled white-collar work, making many people’s skills and capabilities irrelevant and raising questions about humans participating in the future of work. And now, the pandemic is propelling a new wave of automation. Jobs lost to COVID-19 are not necessarily coming back, as machines move in to take up the slack. Even with the most impressive skill set, there is a sudden realization that our human skills are not sufficient for success in the automated world.
We have been following a narrow definition of skills for decades: technical skills, soft skills, project management skills, business skills, the list goes on. In a time when machines do (almost) everything, we have to break this hardwired mindset. It is no longer just a question of which skills are essential. It is about understanding the social and cultural context of work to stay ahead of machines. For instance, if we are looking for technology experts, we consider programmers, developers, and engineers. What we also need is people who can also understand how those at the bottom of the pyramid are using technology to change their lives. By understanding people’s relationship with technology, developers can develop a solution that changes people’s lives. Embracing diverse perspectives and blending them with existing skills is how we stay employed in the future. To quote Steve Jobs, “Technology alone is not enough—it’s technology married with liberal arts, married with humanities, that yield the results that make our hearts sing.” In short: your skill + social and cultural context = hard-to-automate skill.
Consider the following examples:
- A teacher teaching from a student standpoint as well as a knowledge expert
- A car designer with long-haul truck driving experience who knows how it feels to spend hours behind the wheel
- An engineer building an algorithm from a human standpoint, rather than purely to achieve a business objective
Every skill should be considered within the human context. Through this change in focus, people can start to see their skills in the broader context of the work that matters, instead of just performing their assigned tasks. Without a fundamental recasting of how we think about skills, many individuals and communities will be left behind as machines continue to become smarter and take over more of our work.
Future jobs will require a combination of human and technological capabilities, as will the systems preparing future workforces for these roles. In the not too distant future, job descriptions will carry skill requirements such as: The ability to apply data science expertise in the social context of customers. When you are asked where you see yourself in five years during your next job interview, a reply such as, “Making a positive impact on our society by keeping humans in the loop,” will, if the recruiter is human, give you a great chance at being hired!