It used to be that it didn’t matter how grueling the work was, so long as it was safe enough that a worker could get through the day uninjured by being careful. If the boss paid cash at the end of the day and didn’t ask too many questions, there’d be someone waiting to jump in the back of his pickup truck when he went out early in the morning to collect workers. The pay wasn’t great, of course, but it was better than what the workers could expect for equivalent work back where they’d come from, and if they were frugal they could save a bit and send some home or eventually bring their families to the U.S. Moreover, there really weren’t any serious consequences for employers who hired undocumented workers.
This post is part of Robohub’s Jobs Focus.
One who’d made a nuisance of himself and had come to the attention of the authorities might be picked up from the worksite (usually a farm) now and then, but there would be another to take his place the next morning. Sure, knowingly hiring illegal workers was itself technically illegal, but violations of these laws were routinely overlooked, and political rhetoric demanding their enforcement was largely insincere. This was the situation in the orchards of the Northwest, throughout the Central Valley of California, east from Texas across the southern United States, and anywhere else hard manual labor was common. In the Midwest and the Great Plains, where crops like wheat, corn (maize), soya, and others easily handled in bulk predominate, most farm labor had already been replaced by mechanization.
Then new, tougher US immigration laws came into effect after 9/11, and everything began to change. Not all at once, of course, but the rhetoric immediately became more serious and more convincing, and the border with Mexico gradually became more of a barrier. Laws regarding the hiring of undocumented workers were strengthened and began to be enforced. Migrant workers without visas and work permits found themselves being squeezed out, as well as drawn to better opportunities back home, and farmers were faced with an increasingly serious shortage of workers, to the point that, in 2012, many crops were left unharvested, and in some cases even perennial crops, like asparagus, were plowed under, because not enough workers could be found to harvest them.
Congress is now considering a range of options to soften the blow, but there’s no chance of things going back to the way they were before, and, despite high unemployment in this country, Americans aren’t stepping up to take the place of the migrant laborers.
This is the situation into which companies like Harvest Automation hope to introduce robots as a replacement for workers already gone missing. With the introduction of robots, remaining human workers are converted from manual laborers to robot tenders, a task American workers are more willing to perform. Ostensibly, this is the wave of the future, with machines taking over more and more of the dull, dirty, and/or dangerous work, while humans move into maintaining, repairing, complementing, and managing the machines. How significant this wave turns out to be will depend in no small part on improvements in education. Here I refer not only to robotics and computing (nor even only to computing, science, technology, engineering, and mathematics), but also to the many aspects which have yet to be implemented in hardware or reduced to computer code of the various types of work robots might eventually be trusted to do.
To begin with, for as long as the machines remain relatively crude, their senses will need human augmentation. Humans will be needed to help distinguish objects the machines cannot distinguish for themselves, such as larger rocks from hunched rabbits (without IR vision) or smaller rocks from mushrooms (without radar). Humans will also be needed to perform operations the machines are unable to perform, for example binding branches split by wind, snow, lightning, or in danger of being split by being heavily laden with fruit. For the moment the list of operations which can’t yet be performed by machines remains long, but in almost every case this is only because the engineering hasn’t yet been done; there are few, if any, gardening operations that cannot, in principle, be performed by machines. However, even once these gaps in their abilities have all been filled, the machines will still need human assistance with making sense of patterns found in the data they collect and with making decisions about how the operational system might be improved, and human guidance with regard to aesthetic considerations – the art of gardening.
Initially there will be a need for technicians who work alongside the machines, but before long there will be a need for people who are thoroughly familiar with the context of the work to be performed (gardening), domain experts, whose task will be to evaluate the net result of the operational system directing the machines and to suggest improvements. These domain experts will fit in a triangular relationship with the technicians (who will still be needed, gradually moving from working alongside the machines to supervising more and more machines) and the engineers who design the machines and the operational system. In the ideal case, many of the technicians would also be domain experts.
So as new types of machines find their way into the fields, rest assured that they are not, for the most part, displacing workers who would otherwise be in those fields, but rather, in some cases, moving them into more technical work as robot tenders, and in other cases taking over work that fewer and fewer people are willing to do for the money it pays, and that, for those few who are displaced, there will be other farmers nearby anxious to hire them. Meanwhile, a new industry will be germinating.