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Forget Machine Learning:
Humans Still Have a Lot to Learn About Themselves, Part I

By February 4, 2019 No Comments
Forget Machine Learning: Humans Still Have a Lot to Learn About Themselves

Fear has played an integral role in the course of human evolution. It helped to keep early humans safe from predators, hostile environments, and other humans. Fear (or, the amygdala, rather) continues to contribute to decisions modern humans make in their daily lives, lives that are unrecognizable in nearly every way from humans’ ancestors’. Still, the amygdala reacts to modern threats like compromised familial safety, access to food, water and shelter, access to medicine, rough turbulence in an airplane, or walking down a dark alley at night—and even job security and economic stability.

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While most modern humans no longer need to fear packs of animals storming their caves and living areas, humans do still fear what lies over the horizon, what they can’t see—only what they can imagine. And it’s that uncertainty that still stokes fear in many humans; fear of the unknown is arguably the greatest fear of all. Whether it’s fear of miles of unexplored terrain, or wondering if one’s job will still be there five years down the road, the amygdala still fires fear, bypassing parts of the brain responsible for more tempered emotion and thinking. For humans in 2019 and beyond, this fear of their job (or entire sector) being destroyed by Artificial Intelligence (AI) and machine learning is a top fear.

The Difference Between AI and Machine Learning

Artificial Intelligence is a machine’s trait, meaning it exhibits “intelligent” behavior that allows it to successfully perform a task under different environments. These behaviors are most often generated by preset algorithms that have been programmed into the machine, rather than “learned” by observing humans. Most AI systems are created and brought to artificial life by engineers.

Machine learning, however, goes a step beyond. When a machine learns, it does so through intelligent behavior that was not originally programmed in its AI system. This means that it feeds its AI system with autonomously learned data, allowing it to change its behavior on its own—no human hand required.

The Creators and Their Creation: Humans Control AI, Machine Learning’s Future—For Now

For all of the fear of AI and machine learning taking the reins of entire industries, much of that fear remains unfounded; there is currently no universal agreement on how many jobs AI will take, and how many it will create. For some, this uncertainty is worse than knowing their job may soon be on the chopping block. But before advanced technologies are capable of completely performing even a minute portion of current jobs, AI must become much, much more advanced; its learning capabilities are currently nowhere near the level needed to execute the types of tasks that, currently, only humans can.

It’s often forgotten that AI and machine learning did not spring into existence on their own; humans created AI, and they still control how it will shape the world in the coming years. While it’s all but certain that many jobs will be either supplanted or massively modified by AI, it is nowhere close to being able to reproduce human traits like problem solving, creative thinking, and leadership. The interim between AI’s early stages and its seemingly destined ubiquity in daily life will likely see dangerous, dirty, and tedious jobs go the way of pagers and payphones—jobs that few enjoy, and put many at risk.

Humans Don’t Know What They Don’t Know

But as AI’s presence grows, it will be crucial that humans learn from the mistakes made by AI applications, and the shortcomings of machines’ ability to learn. Even Amazon’s sophisticated AI recruiting tool was developed with a massive flaw: it showed bias against women, downgrading their resumes in favor of men’s—a trait it learned from sorting through thousands of resumes. Catching these and other flaws then allows humans to make better-informed decisions about how these applications should evolve or, in Amazon’s case, to be scrapped.

AI isn’t yet sophisticated enough to take on broader, less-defined questions; current AI cannot produce the types of complex answers humans will want (and need) to ask when faced with equally complex problems. This leaps in AI and machines’ ability to learn will take time, and it will do so with increasing speed. However, humans must continue to learn from not only their machines, but from the unforeseen flaws that are inevitably in the path towards an AI-centered future.

AI and Machine Learning Bring Lots of Uncertainty. Work with a Partner that Can Help You Navigate that Uncertainty.

Artificial Intelligence knows no borders; as businesses continue to expand globally, so too will the applications used to help fuel those organizations—and will continue to change the way global businesses operate. If you’re considering a global expansion, but are unsure about which market best suits your need, Velocity Global’s International PEO (Professional Employer Organization) solution can have you in your test market in as few as 48 hours—and out quickly if it’s not the market for you. Ready to make moves? Let’s talk.

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