In 2005 an online chess-playing website set up a special freestyle chess tournament. Teams could consist of all human players, or humans plus computers. Gary Kasparov, who a few years earlier had defeated IBM’s Deep Blue supercomputer at the game, wrote about the tournament. He expressed surprise that the winner was “not a grandmaster with a state-of-the-art PC but a pair of amateur American chess players using three computers at the same time.” The pair’s skill in “coaching” their machines to assist them “effectively counteracted the superior chess understanding of their grandmaster opponents and the greater computational power of other participants.”

While we might place our money on machines alone for a game of chess today, Kasparov’s tournament story is a good example of how humans can partner with automation technology (an umbrella term for robotics and AI/machine learning) to achieve better outcomes. But in 2018 we’re more likely to hear about how automation is detrimental to the ways people live and work.

Public conversations tend to focus on forecasted job loss and negative societal impacts, even though the scale of these effects remains a point of contention among economists and research groups. Furthermore, in contrast to previous waves of automation, this new wave is “blind to the [color] of your collar” in that its use ostensibly threatens blue-collar work as well as traditionally white-collar tasks such as data analytics and actuarial work.

Despite these concerns, Kasparov’s insights remain relevant. The disruption wrought by automation may be the lede in our newsfeeds, but these technologies work best when they augment human capabilities rather than simply replacing them.

While automation will reduce the number of human workers needed in the aggregate, it can also give people more time for socially demanding aspects of work, such as building strong relationships with customers and offering high-touch, white-glove service. Here are a few examples of people working side-by-side with automated technologies to good effect:

  • Quality Monitors. Zume Pizza’s in-store robot production line has human workers place toppings and check for overall quality (two tasks that robots can’t yet perform). They also pioneered the use of computer-operated ovens in delivery trucks so that pizzas arrive freshly baked at the customer’s door. Human workers are critical here as well. In each truck, two people – a driver and a quality monitor – ensure that Zume Pizza delivers a high-quality customer experience every time.
  • Pathfinders. People are better than AI at navigating complex driving conditions such as extreme weather or high-density urban environments, which requires quick thinking and a series of judgement calls. Phantom Auto, a teleoperation service for autonomous vehicles, can “pass off” vehicle control to a remote human driver if road conditions deteriorate due to inclement weather.
  • Remote Operators. Soft Robotics pioneered a robotic gripper that brings farmers one step closer to autonomous harvesting. A person operates the robots remotely, which lets other staff focus on work that requires agricultural expertise such as determining when produce is ready for harvest. Automation is also strengthening the business case for environmentally friendly animal husbandry. Vence offers virtual fencing hardware and software that reduces overhead costs by letting people remotely herd and monitor the health of livestock.
  • HR Administrators. HireVue claims that its candidate screening platform can counteract the unconscious biases of people involved in the recruitment process. TARA Intelligence automates software development project scoping and contractor hiring. These tools claim to level the playing field for candidates by reducing human bias to focus on the right things for their companies and products.
  • Healthcare workers. DoseMe takes in patient data and calculates more precise and individualized medication dosages. This enables doctors to focus on more holistic care for patients.

These examples show that there will continue to be a place for human workers in our increasingly automated world. As with past technological revolutions, our cultural and political expectations about work—what it looks like, how it’s valued, how necessary skills are taught—will need to evolve. As we rethink people’s place in the economy, we will need insights from a broad spectrum of human experts, including economists, ethicists, technologists, business and policy analysts, and even chess grandmasters.