Why AI won’t replace Humans

Instead they will be a complementarity, to us.

The debate of the century...In the future we foresee Artificial Intelligence replacing Humans and their jobs.Will the future tech actually displace humans and their jobs?

It’s easy to say and conclude that Artificial Intelligence could somehow replace us humans in the near future. Due to conventional wisdom. But If you think it that way then you don’t understand enough how computers actually work. If you’re pessimist about the future taking over us I think you watch too much Hollywood Sci-fi movies.

Don’t be delusional, don’t try to escape the reality we’re in. Because the reality we’re in is way far different than the one you see in the movies, maybe. The future we’ll see tomorrow is in our hands and it entirely depends on us.


Credit: https://www.outbrain.com/blog/wp-content/uploads/2017/01/OB-Blog-Artwork-Artificial-Intelligence-1-v1.jpg

Let me highlight you the keyword of this story:

Complementarity

noun [U] UK
the state of working usefully together
ex. London’s time zone position offers a natural complementarity with New York and Tokyo for tradingof securities.


Let me tell you what i believe in. A more advanced AI technology that you often see in the movies (Terminator for ex) or a replacement by computers is a thing of the 22nd and even 23rd century.

We humans of today are the ones that gonna create the future we want or we vision and that will only happen if we have a definite plan to achieve it. We can’t be just the Europe of today, just hoping the future will be okay without actually having no idea in which way it could be “okay”.

Technology Means Complementarity

Take this article from a book of Peter Thiel, Zero to One which elaborates the idea of complmentarity.

Now think about the prospect of competition from computers instead of competition from human workers. On the supply side, computers are far more different from people than any two people are different from each other: men and machines are good at fundamentally different things. People have intentionality — we form plans and make decisions in complicated situations. We’re less good at making sense of enormous amounts of data. Computers are exactly the opposite: they excel at efficient data processing, but they struggle to make basic judgments that would be simple for any human.
To understand the scale of this variance, consider another of Google’s computer-for-human substitution projects. In 2012, one of their supercomputers made headlines when, after scanning 10 million thumbnails of YouTube videos, it learned to identify a cat with 75% accuracy. That seems impressive — until you remember that an average four-year-old can do it flawlessly. When a cheap laptop beats the smartest mathematicians at some tasks but even a supercomputer with 16,000 CPUs can’t beat a child at others, you can tell that humans and computers are not just more or less powerful than each other — they’re categorically different.
The stark differences between man and machine mean that gains from working with computers are much higher than gains from trade with other people. We don’t trade with computers any more than we trade with livestock or lamps. And that’s the point: computers are tools, not rivals.
Credit: https://unsplash.com/photos/0E_vhMVqL9g

The Ideology of Computer Science

Why do so many people miss the power of complementarity? It starts in school. Software engineers tend to work on projects that replace human efforts because that’s what they’re trained to do. Academics make their reputations through specialized research; their primary goal is to publish papers, and publication means respecting the limits of a particular discipline. For computer scientists, that means reducing human capabilities into specialized tasks that computers can be trained to conquer one by one.

For the Startups of todays and the future, take note of this.

We have let ourselves become enchanted by big data only because we exoticize technology. We’re impressed with small feats accomplished by computers alone, but we ignore big achievements from complementarity because the human contribution makes them less uncanny. Watson, Deep Blue, and ever-better machine learning algorithms are cool. But the most valuable companies in the future won’t ask what problems can be solved with computers alone. Instead, they’ll ask: How can computers help humans solve hard problems?

So the real challenge is: Create a company that will build new things (innovation) and help humans solve more complex problems.

Summing it all up…

As computers become more and more powerful, they won’t be substitutes for humans: they’ll be complements.

This way our future will definitely be better and sustainable.

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My inspiration for this story is Peter Thiel and his award-winning book.

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