“I am not staring at you. I am a cyborg photographer. Just act natural. This is a candid shot.”
While this line from the cartoon Rick and Morty may be silly, what if cyborg photographers were real? What if you lost your job to a machine?
Last week, Macleans magazine cited an Oxford study which concluded 47 per cent of jobs are at risk being automated. This study is from 2013, but the threat of automation has only grown since then.
What is automation? A basic definition would be to take a repetitive human task and teach a machine to do it. Greg Jamieson, associate professor of Mechanical & Industrial Engineering at the University of Toronto, says it goes further than that.
“In my field, sometimes people say it’s any task that a person used to do that’s now done by a machine. But now we are having machines do tasks that people never did, so that definition of automation doesn’t seem very descriptive anymore.”
It is Jamieson’s expectation that automation will have a massive impact on the transportation industry, and this shift may come sooner than expected.
“Google cars and that type of technology is not where we will see automated vehicles first. I think where we’re going to see it first is in (commercial) transportation.”
This might be bad news for someone hoping to pursue a career in that field, according to Jamieson.
“Long-haul trucking, that job will go away. If I had a child who was finishing high school and wanted to think about their career, there’s no way I would encourage them to do anything related to long-haul trucking. It’s tons of hours, low stimulation, reasonably high risk, and a machine can do that much better.”
The world of medicine is changing drastically as well.
Diagnosis of a patient requires the correlation of individual characteristics, symptoms and settings. The skill required for a medical professional to diagnose a patient is acquired through extensive training and practice.
A machine, on the other hand, can pick it up on the fly.
According to Jamieson, “machines can do that correlation very readily,” but their capability is a blessing and a curse.
“If a medical professional is expected to use a diagnostic machine to help them diagnose a patient, then that expertise is offloaded into the algorithm. A mediocre doctor would have more expertise at their fingertips. But they also lose the practice and become de-skilled at doing those things.”
Automation does not only help with diagnosis, but can work preventatively in ways that humans cannot alone.
“If a machine is scraping medical records for information about patients and diseases you can foresee things like outbreaks. You can see when flu season is coming on. You can see if there is a particularly virulent strain of a virus going around,” says Jamieson.
When these automated tools are at our disposal or when these tools dispose of us, we are faced with two challenges.
The first challenge we face, according to Jamieson, is to learn enough about how automation works in our chosen disciplines so that we can use it to extend rather than replace our capabilities.
“Employers are going to want people who can be skeptical about these automation tools,” says Jamieson. “They’re going to want employees to use them because the potential benefits are huge.
“But these employers are also going to learn that what they still have people for is to understand the context, to understand the nuance. Machines are the ultimate idiot-savants. They are incredibly powerful, but utterly ignorant of context.”
Michelle Zhou, a student of Humber’s Interior Design program, sees both sides of this coin.
“A lot of my job is based on drawing, so if a machine can do that I’m out of luck,” Zhou says. “But I would still be the one being creative. It might actually help me out.”
Achal Raveendran, a student of Humber’s Electrical Engineering program, is also cautiously optimistic.
“If robots can install lights, they lack creativity in doing so,” says Raveendran. “Maybe in the future my job will be to tell a robot where to install lights.”
While some jobs may be more or less safe from extinction by automation, there are many that are not. This poses a distant second challenge whose solution may involve a total restructuring of our society.
“If we have so many fewer jobs, universal basic income comes up as an economic and ethical issue,” says Jamieson.
“When we industrialized, we moved huge swaths of population from the country into cities because the jobs were there and it radically changed our societies. But how are going to move people to where the jobs are if the jobs are nowhere?”