The Impossible Leap

Why Machines Can Never Equal Humans

Photo by Gaelle Marcel on Unsplash

No problem can be solved from the same level of consciousness that created it — Albert Einstein

This essay provides a framework for my readers to conduct small thought experiments of their own to come to their own opinion on whether a world ruled by robots is a possibility. My endeavor here is to not use any charts, data or expert opinions to guide my thoughts. This simplicity is intentional — I don’t want anything except my own personal biases (which I have many) to complicate the issue.

As of today, such a radically alternate reality doesn’t appear to be a possibility to me. These paragraphs outline why. I tend to believe there is a minuscule chance I am wrong.

Then again, I often laugh at my own self when I ask myself: who am I? The irony of the matter is that this joke of a question ‘who am I?’ is also an existential one. It holds the answer to what AI or even AGI can eventually become or not become.

A Few Underlying Assumptions

In the absence of another template, we are using the human brain as a template to model Artificial Intelligence and Artificial General Intelligence (AGI). That is my first assumption.

Second, I also assume that many people would already be familiar with viewpoints on both sides of this popular debate. There are very famous personalities arguing on both sides of the equation. Some claim machines can surpass human intelligence and even reach human level existence while many others think that singularity is not possible. I am not claiming to be anywhere close to these colossally gifted minds. Frankly, I am just a common man trying to make sense of this world.

Third, it is possible and will be possible to use algorithms to progressively convert data to intelligence and to automate many human jobs. There are three considerations here : the hardware or computing power (normal or quantum), the software or AI algorithms and the quantity of data (collected using sensors). Data and computing power will continue to grow while the algorithms (productivity) will continue to improve.