5 Common Myths About Artificial Intelligence That Aren’t True

3. Artificial Intelligence Will Evolve And Become Superhuman

The 2014 movie The Machine features a female robot character that went berserk after attaining a high level of emotional intelligence. Sci-fi movies like this tend to shape people’s views about the future of AI. But establishing our beliefs on mere imaginations is impractical.

It’s clear that artificial intelligence now influences decision-making processes in business intelligence, astronomy, medicine, and pharmacy. But the fact remains that no matter how well you train a machine, it can’t think for itself.

This is a limitation that will take ages for AI to override—and probably will never happen. As such, most processes that use artificial intelligence will always depend on a final verdict of people to decide.

Therefore, thinking of the potential of artificial intelligence as overruling us is somewhat ridiculous. It makes more sense to portray AI as modern servants that carry out more daunting tasks more accurately and efficiently than we can—not more intelligently than us.

4. Artificial Intelligence And Machine Learning Are Synonymous

Artificial intelligence and machine learning are sometimes wrongly equated. These terms are not the same, though they are interrelated.

The origin of artificial intelligence and machine learning goes as far back as the 1950s. The term “machine learning” was coined by IBM’s Arthur Samuel in 1952—after he successfully developed a computer program to play checkers that mastered all previous positions.

However, the need for the development of machines with artificial brains came into limelight in the late 1940s. And because it was necessary to have a broader term for everything a machine does, including learning, artificial intelligence became a discipline in 1956.

As a result, using both terms synonymously isn’t quite correct. Machine learning is a process whereby a machine learns by experience, based on the information it has seen before. For more information, we’ve looked at some examples of machine learning algorithms.


Machine learning algorithms are designed to make life easier and improve systems, but they can go awry with bad consequences.

Such information is in the form of data, whether it’s featured or not. Artificial intelligence, on the other hand, involves all processes, including machine learning, that brought about the product we know today.

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