Four Ways Jobs Will Respond to Automation, Automation is changing the nature of work. The robots are coming but according to popular belief, it’s not just low-paying jobs that are at risk of automation.
Automation will affect jobs by separately assessing the degree of threat to each profession’s core skill set and value form.

A review of the academic literature and public discourse on automation revealed limited consideration of risks by profession. So we did our own comparison, coding 50 professions (including many from our literature survey) according to the type of value jobholders delivered and the skills they used to deliver it, to create a framework that helps workers assess what kind of threat automation poses for them. We identified four paths of evolution — jobs will be disrupted, displaced, deconstructed, or durable — and found that value is more predictive of change than wages, education, efficiency, cost, or other factors.

Counter to popular belief, it’s not necessarily blue-collar or non-college-educated workers who will be most threatened by automation in the coming decades. Our analysis suggests that a plumber may see less disruption than a legal professional. Simply instructing everyone to engage in continuous education and skill development is remiss. Workers must understand the four paths of job evolution — and the factors behind each path — if they hope to adapt.

Understanding the Four Paths

A jobholder uses a core set of skills to deliver value in some form to a recipient — either externally to a customer or within an organization. Jobs evolve as those consumers’ perceptions of value fluctuate along two dimensions: core skills and delivery mechanism, or what we call value form.

For some jobs, core skill sets include a specific knowledge base or craft. Others involve people skills and the ability to build relationships rather than technical expertise. Skills that can easily be standardized, codified, or routinized are most likely to be automated. Those that involve hands-on or real-time problem-solving are less so, because developing tools sophisticated enough to handle such ambiguity is either too cost- and labor-intensive or technologically out of reach. For example, while an electrician’s skills may seem vulnerable to automation, the application of those skills varies widely according to the unique circumstances of every client. This degree of customization would be difficult to automate.

A skill set provides value only when it is delivered to a recipient, however, and the delivery mechanism may be transformed. Here’s an example: A professor’s core skill set is expertise in a certain domain. Such expertise has traditionally been delivered to consumers (students) through in-person classes. However, online platforms and massive open online courses, or MOOCs, offer new vehicles through which learning can occur. The core skill remains the same, but technology is shifting the value form as adaptive software and virtual tutors offer highly personalized instruction and support to growing numbers of students with diverse needs. And computer-directed learning will continue to improve with the increasing sophistication of automation and AI.

We identified the four ways automation will affect jobs by separately assessing the degree of threat to each profession’s core skill set and value form. (See “Which Professions Are Most Vulnerable to Automation?”) Here, we’ll describe those paths to evolution and suggest strategies for navigating each one.

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