Post-Postmodern Times: Machine is not stealing your job but liberating you from it.
In 1936 film “Modern Times”, Charlie Chaplin comically but acutely criticizes the pursuit of the industrial efficiency sacrificing the humanity. Chaplin portrays himself as a factory worker who works in an assembly line of an ever accelerating pace. He is a diligent worker and even obsessive in keeping up with the demand by a corporate tyranny. The worker eventually loses his mind.
By the end of the last century, the kind of the task the worker was doing in Modern Times became fully automated by machines. Today, machines are becoming so intelligent that the intellectual tasks that were once considered professional and complex are executed by artificial intelligence. Those works include accounting, legal, and investment management.
People think the recent advancement of machine learning and its applications will put many workers out of job. That is probably true. But the tasks the artificial intelligence is replacing the human worker is still simple and repetitive ones: The kind exhausting and driving the factory workers nuts.
Here is an example: A friend of mine in the data science community is applying the deep learning to automatically categorize the fashion items in the catalog. Currently, the workers with sufficient fashion knowledge look at the photography of the merchandise, decide if it is a tank top or camisole, then manually input the information into the database. Now the machine can learn the pattern through the examples and become as good as a human worker. The machine does not get exhausted or become mentally sick by repeating such tedious work all day and night. And it works very fast.
Now fashion experts do not have to waste their time in those trivial tasks. They can be engaged in more high-level and creative activities. Yes, a worker would lose his job if all he wants to do is to perform a well-defined, repetitive, and simple tasks. But shouldn’t we rather be living humanly by learning, creating, expressing, and loving?
Is it too optimistic if I say, “Machines will liberate human from inhuman works.”?
Of course, there are many concerns. The wealth will be highly concentrated in the corporates and the capital who own the sophisticated machines. I also fear the human workers replaced by machines would become hostile to the development of the artificial intelligence. The 21st-century version of Luddite movement may come into reality. The post-World War II system and the way of life must change and the change is never comfortable to most of us. We will face a big change in the social structure in every level before the real golden era of man-machine collaboration flourishes.
But this is a chance that we prepare our future generation to live with the updated definition of what it means to be a human and achieve something we never thought we could.
“Many experts believe that human beings will still be needed to do the jobs that require higher-order critical, creative, and innovative thinking and the jobs that require high emotional engagement to meet the needs of other human beings.”, says Ed Hess in a Harvard Business Review article.
If you are in early in the career, I bet your expertise will be challenged by machine efficiency one day. How much portion of your job requires you to be thinking critically and being creative? Does it require high emotional engagement? In other words, does it make somebody smile and feel loved?
A theoretical neuroscientist Vivienne Ming even goes on to warn us that we will turn from a human capital to a toxic asset if we don’t invest in ourselves today. In a Techonomy article, she writes, “It takes 20 years to a ‘build’ a problem-solver. It takes liberal arts, and exposure to culture, and even learning to deal with repeated failures. Instead, we train people with static skillsets to fill specific jobs. All that misinvestment has turned human capital into a toxic asset.”
Hess continues, “What is needed is a new definition of being smart, one that promotes higher levels of human thinking and emotional engagement. The new smart will be determined not by what or how you know but by the quality of your thinking, listening, relating, collaborating, and learning. Quantity is replaced by quality. And that shift will enable us to focus on the hard work of taking our cognitive and emotional skills to a much higher level.”
This applies even for a job like Data Scientist. Machines are automating data science workflow every day. They are getting smarter. Today’s data science job requires a lot of manual work from data cleansing to the hyper-parameter tuning of machine learning algorithm. That may keep our day full and we may think our j ob is secure that way. But such tedious jobs will be replaced by computer algorithms soon. In fact, as a data scientist, you should be the one who is always thinking how to automate them so you can focus only on what matters.
In the era of the machine getting increasing smarter, I would like to focus on the activities that make human smarter. Machine and human are different in that machines need objectives defined by a human. They cannot envision the future based on the human value system. Acquiring concrete skills to get things done is important, but today’s valuable skills may get obsolete tomorrow and it may be replaced by what machine can do. Polishing our value system within, envisioning the future, thinking critically to achieve our objectives - I think those are increasingly important things to do every day as human.
Daigo Tanaka is the founder and principal data scientist at Anelen, Co, LLC. If your company is interested in using data science towards corporate strategy, please connect me on LinkedIn or send a message.*