It is easy for people to think their jobs are safe from automation. For a psychologist, the therapeutic alliance between two people is said to be what makes the treatment work. For lawyers, it is difficult to imagine that the creative thinking often required to help their clients find success in the courtroom could be replicated by a computer system. Politicians, artists, writers, accountants, professors, doctors, and others who need education, skill, or inborn talent to do what they do well may expect that their jobs will continue to exist, even when all others are completed by robots or computers. Some feel that their long-term education, that which is required in their industry, will insulate them from replacement. Others think that the creative talent they have been honing since they were a child is irreplaceable. Yet, what keeps them in a position where they can use their experiences and abilities to earn a living wage is that someone values their work highly. What tends to be overlooked is that there is someone else out there who can do what they do—but for less. In fact, there are hundreds of thousands of people in need of money who will use their skills and talents as a crowd in ways that put those in what are deemed to be ‘stable careers’ out of work. All it takes is for economic actors to decide that workers no longer need such an education, or that inborn talent is not worth a fair and decent wage. What follows next is that these jobs can then be given to individuals who are willing to work for far less. It is this combination of automation and a crowd of willing workers, which may lead to the decimation of white collar work as we know it, unless we confront the future of work head-on.
Of course, this sort of move cannot happen if there is no one to give the work to. There are dozens of platforms that offer large crowds of workers willing to do tasks for pennies a piece, such as Figure Eight, One Space, Clickworker, and Microworker. The oldest and most well known of them all, Amazon Mechanical Turk (mTurk), not only facilitates the work itself through its online labour platform, but has gathered a crowd of more than 100,000 workers willing to do anything and everything for money (Difallah, Filatova, & Ipeirotis, 2018). You can imagine the site to be like a bulletin board you might find at a community job centre, or even in your local coffee shop. In such an offline environment, people in the area could print off a job ad explaining what they would like done, and workers nearby could check to see if there is work they can do. For example, if I wanted to translate an article I had written from English to French, I might stick it up on that board with the price that I am willing to pay and my contact information. Then someone who knows both languages well would take the article home, work on it, and bring it back to me in exchange for the payment promised. It might take a few days or even a few weeks, depending on the complexity and length of the text. I might end up paying a few hundred dollars to ensure the best work was received. Yet, if I am not willing to wait so long or pay so much, I could instead put that article up on mTurk. First, I would cut each sentence out and submit each individually; this is a system of posting work called “microtasking”. Then, once they were all posted on the site, anyone who knows both languages would grab as many sentences as possible and do them in tandem, meaning a 1,000 sentence article could be translated in as little as six minutes. That whole article would likely only cost me $20 to translate. mTurk makes getting work done cheap, easy, and quick. Thus, there is no reason why, as AI learns to do the jobs we need done, companies will not start moving jobs to mTurk or other platforms.
As a worker on mTurk for the last 13 years, I have probably seen it all. From writing titles for porn videos to tagging ISIS video screenshots to categorizing images and videos based on their violations of content moderation policies for Fortune 500 companies, it has not always been enjoyable. Yet, one type of work which has increased in availability on mTurk over the last eight years has been that which clearly powers automation, robotization, and AI. Crowd work platforms, it turns out, are now key to technological innovation in the digital realm. For example, mTurk workers create datasets that are used to train AI algorithms. We are a part of the process of training AI from beginning to end. First, we create gold standard datasets; essentially, we provide the correct answers to questions that are to be posed to AI. For example, we might take 10,000 photos stating whether they include a cat or a dog. These answers are then fed to algorithms to teach them to determine the difference between cats and dogs in images. Next, the algorithm tries to figure it out on its own, and we adjudicate the results of its work, which is then fed back to the algorithm to fix any flaws it may have. Lastly, we often judge the algorithm on its “human nature” – does this seem like a robot completed the work, or a human? Many companies want their AI to appear humanlike, such as a chatbot for customer service, so we are tasked with making it more like us.