Long before Covid-19 upended our daily lives, the “future of work” discussion was already well underway. In fact, the National Science Foundation had identified research surrounding the Future of Work as one of its 10 Big Ideas for Future NSF Investments. With the landscape drastically altered since March 2020, we’re now forced to come to terms with these changes, and their potential fallout, sooner than expected.
The pandemic has expediated disruption and we’re now seeing increased automation in several sectors. For instance, Pew’s Stateline recently highlighted jobs shifting to automation due to Covid-19, including robotic burger fryers, chicken butchers and hotel cleaning staffs. And, earlier this summer, I told readers about “Tommy,” a robotic nurse in Italy monitoring patients’ vitals and communicating with doctors.
As an engineering professor who studies the design of autonomous systems, this change both fascinates me and gives me pause. As we continue to discern what the future of work will look like and the role automation will play, here are three important considerations:
A mindful pace of adoption
A June survey from PricewaterhouseCoopers found that 44% of corporate financial officers are considering adopting more automation due to Covid-19. With the pandemic accelerating one of the biggest challenges posed by increased automation — widespread job loss — we have less time to identify and implement solutions to prevent or counteract layoffs.
Since it will be very difficult to reverse course once new automated systems are implemented, we cannot ignore the negative ramifications of adopting new automated technologies too quickly. We must balance the present needs with a broader outlook on what a post-pandemic life will mean for all of those impacted. In other words, let’s not just rush to automate simply to automate, but do so mindfully and with purpose.
We should leverage those situations or sectors where the pandemic has created an urgency for automation, to better understand how the automation is affecting the people touched by it. New policies can help to prioritize what industries need to adopt automation sooner, versus those that could wait.
Rethink our training practices
In August, I discussed that humans’ advantage over automation is our ability to handle unexpected, out-of-the-ordinary situations, compared to a machine’s standardized programming for a specific task. For example, a Wisconsin welding company began deploying robots for “easier, more repetitive” jobs, freeing up its employees to work on more complicated projects.
“It allows them to go off and do some of those more complex welds,” the company’s HR manager told a local news station. “That makes a happier employee and a happier company.”
But, in order for humans to have the expertise for these more complex tasks, they must be proficient in “the basics” of the profession, which comes from exposure to the routine work. If automation becomes the default method for accomplishing elementary tasks, humans may have less opportunity to master the preliminary skills that lead to the experience and expertise needed when the unexpected happens. While automation can’t replace humans’ problem-solving abilities and nimbleness, it can be an impediment to the early stages of skill development. If humans will be expected to tackle nonroutine, complex problems sooner, we must rethink how we train our workforces to gain that expertise without the same amount of real-world experience.
Educators must rise to the moment
When a student protests that a problem on their midterm exam wasn’t exactly like an example in their homework, I use it as an opportunity to impart an important lesson. If all they learn to do is repeat exactly what they are taught, they will likely be out of a job before they graduate. That’s because we’ll— eventually —teach a robot to do almost anything that is repetitive. This also puts the onus on me as an educator to make sure that I’m effectively doing my job in developing students’ skills to meet the changing needs of the job market. Educators are key stakeholders in the “future of work” conversation because it’s very much dependent on the future of education.
With schools serving as the pipelines for tomorrow’s workers, education needs to prepare students for a future that is not just already highly automated but increasingly so. Automation, machine learning and artificial intelligence are only getting better and smarter, so designing curricula that challenges students’ ingenuity and problem-solving capabilities in the classroom is vital.
But education will only be effective in preparing students if we have a clear understanding of where industries, and the economy, are heading. Without hearing from employers, professors might design coursework in a way that is not preparing our students for the future they will face beyond graduation. While collaboration between academia and employers currently takes place, it needs to happen more — only 37% of companies believe partnering with educational institutions is important in preparing for a workforce for the future — as the workplace evolves at an accelerating rate due to automation.
Overall, as we’re forced to confront these questions of automation with more urgency and under unusual circumstances, considering and collaborating with all stakeholders will be crucial. Whether life returns to normal in a matter of months or years, we can still make decisions now that are best for society as a whole in order to set ourselves up for the best possible outcome for the future of work.