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How Machine Learning will Affect Human Learning

Jul 31, 2017
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How Machine Learning will Affect Human Learning

There’s much talk about machine learning. Machine learning refers to machines and robots actually learning and building on their artificial intelligence.  Machine learning goes beyond merely downloading additional data. Rather machines are being designed to process data, learn from it and apply that new knowledge.

This is certainly an exciting time to be a machine.

As we explore the possibilities of machines learning, what are the implications for good old-fashioned human learning? Let’s start with a couple of fundamental questions. How and why do humans learn? Unlike a computer that can upload data, humans learn through their senses.

Sometimes humans learn passively without even attempting to. You might call this empiricism. We observe nature and imbed that learning into our own behaviors unconsciously. But some knowledge requires strenuous activity and discipline. Learning how to read requires discipline and time on task. Learning more advanced mathematics or science require even more concentration, study and continuing effort.

One of the challenges to human learning is our “will”, including our laziness and stubbornness. Sometimes we see facts yet reject those facts. We may find the facts inconvenient because the facts disrupt our beliefs, prejudices, or assumptions, or because they imply some perceived obligation on us. So we humans twist the facts and rationalize theories that turn the facts on their heads. In effect, humans have an ability to actively reject knowledge. It remains to be seen if machines will evolve to develop this human skill.

By contrast, once a machine has been programmed to perform a mathematical equation, it will continue to process the factors in the equation the same way every time with steady reliable repetition. Unlike a human mind, the machine is unlikely to forget what it’s learned, or suffer from stress or other distractions.

As machine learning and artificial intelligence advice, we will be tempted to rely more and more on the technology. If machines can process information for us, why should we even learn how to do math, or engage in scientific inquiry in the first place? As a few gifted humans teach machines to learn, the masses of humans will be tempted to not study at all.

Such intellectual laziness would have consequences in our daily lives. We already live in a society that all too often defers to perceived experts. As machine learning advances, will we defer to machines?

We already Google and go to YouTube to find answers to simple tasks. I recently told my son we were about to have a special bonding moment. Since time immemorial fathers have passed on practical knowledge to their sons. I told him that we are about to have such a moment. There was a simple task that I wanted him to do around the house. But rather than showing him with my own two hands how to do the repair, I taught him how to find the answer. I told him, “Son, go look it up on YouTube.”

We don’t forfeit any of our humanity when fathers tell their sons to look up instructions to simple tasks on YouTube. But will we humans become so complacent that we start to look to robots and machines to give us instructions, directions and tacitly authorize our decisions?

It’s not difficult to imagine a time when this or that government, regulatory body or trade union digitally publishes their guidelines for best practices for nearly every daily activity. When something goes wrong, will we be liable if we failed to consult with the all-knowing machine? That’s unlikely to happen very often before we humans are trained that we must consult with the robots before we proceed with daily tasks.

We already have people in this society who have reified science as if it is a thing. But science, properly understood, is a method of inquiry, not a settled storehouse of human knowledge. Science is an inquiry into nature, causes and effects. The purpose of science is to achieve knowledge, and to test what we know. We have confidence in what we know based on repeating the same test over and over again with the same result. Yet, we derive much of our existential meaning from how we fit into nature around us. If the masses surrender scientific inquiry to machines (and a select few scientists who work with the machines), are we also surrendering our human sense of wonder and quest of understanding? If we look to machines for technical answers, will we humans also let the machines tell us the meaning of things? Taking this to the extreme, will the robots some day be teaching us humans the “meaning of life”?

Science fiction is becoming reality. It is yet to be seen if we are building a utopia or a dystopia. But, if we have any hope for improving the human experience, we have to double down on our humanity. We have to hunger more for knowledge and understanding, not less.

 

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