How Close We Are to Fully Self-Sufficient Artificial Intelligence

If you followed the world of pop-culture or tech for some time now, then you know that advances in artificial intelligence are heating up. In reality, AI has been the talk of mainstream pop-culture and sci-fi since the first Terminator movie came out in 1984. These movies present an example of something called “Artificial General Intelligence.” So how close are we to that?

No, not how close are we to when the terminators take over, but how close are we to having an AI capable of navigating nearly any problem it’s presented with.

Technically defined, artificial general intelligence or AGI is a machine that has the capacity to understand or learn intellectual tasks to the aptitude that humans can. Most AIs today are highly specialized. 

Computer programmers and scientists utilize machine learning algorithms to develop specialized AIs. Those are artificially intelligent algorithms that are as good if not better than humans at one specific task. For example, playing chess or picking which square in a segmented picture has a street sign in it, i.e. Captchas.

Recent advances in AI and machine learning, while not technically close to real AGI, have created a sense that AGI is close, as in a matter of years or decades. It also doesn’t help that you have some fo the world’s top minds like Elon Musk calling out AI as one of the biggest existential threats to human existence of all time. 

Some of the biggest advancements in AI today have been artificial neural networks, which are technologists’ way of mimicking the way that human brains work with code. That said, defining what exactly makes something intelligent is hard…

Humans have multiple forms of intelligence, and we likely need to take a closer look at just what it means to be “intelligent” if we want to determine how close artificial general intelligence is to reality.

Humans both have intelligence when it comes to problem-solving as well as emotions. Emotional intelligence is arguably a trait that makes something more human, whereas the ability to solve problems and understand things is something computers have been mimicking since the beginning of their existence. 

Machine AIs are around about the same level as a four-year-old toddler when it comes to taking IQ tests, so they’re not quite to human level of deduction yet, either.

Emotional intelligence, however, is going to be the harder task for artificial general intelligence to conquer. Emotions are fluid and inexact, not something that works well with the hard-coded nature of machines. The other facet to emotional intelligence is understanding the tone and meaning behind objects. Like, if someone waves a white flag in battle, a computer might recognize it as what it is, a white flag waving. However, our emotional intelligence gives us context and understanding that the waving of the white flag is likely a call for surrender. 

So, true intelligence incorporates the ability to problem-solve and understand with the ability to interpret and read between the lines. This is also true on not only the receiving side, but also on the giving side. Meaning, in order for computers to have artificial general intelligence, they need to not only understand human tone and context, but they also need to be able to dish it out.