If you’ve heard anything about technology in the past few years, you would know that
computers gaining human-like intelligence is a hot topic.
But many people, such as Elon Musk and Stephen Hawking have cautioned against the misuse
and danger of uncontrolled and fully conscious AI.
Though Before we even think should we use conscious AI, we have to answer the question
of can we even create a fully conscious AI?
The concept of AI started with British Mathematician Alan Turing.
In a paper published in 1950, Turing outlined his logic on why a computer should be able
to think like a human: since humans make decisions based on logic and reason, computers could
as well.
The first of many breakthroughs for AI came in the summer of 1956, when Allen Newell,
Cliff Shaw, and Herbert Simon presented their program, Logic Theorist.
This program was able to recognize patterns in the proofs in the Principia Mathematica,
recreate them, sometimes even making what the creators considered a more elegant proof.
For the next 20 years, artificial intelligence found growth in a great amount of funding,
more powerful computers, and improved algorithms for machine learning.
While at Carnegie Mellon University, Geoffrey Hinton developed and applied the backpropagation
algorithm, setting the stage for modern deep learning.
The idea of consciousness does not come from the mainstream artificial intelligence that
is incorporated in your home assistant or video game.
These are examples of what is called artificial narrow intelligence, meaning a computer is
able to perform a task at the level of a human, but a very specific task.
Artificial General Intelligence or AGI, is the concept that a computer can achieve human
level mastery, in any subject or field which is chosen.
Along with the ability to learn, the computer also has the ability to drop that subject
and begin and succeed at learning something new.
According to Aristotle, sentience and consciousness comes from perception, and perception of that
perception, and further extension of perception.
Aristotle called this higher-order thinking, and he believed that higher order thinking
was the mark of a truly intelligent being.
According to Ray Kurzweil, the singularity is the point in time when the intelligence
of computers surpasses the intelligence of humans.
After the abilities of artificially intelligent machines grow exponentially and reach the
Singularity, the computers will hold more power than all humans combined, and the intelligence
which now holds control will start to seep into the surrounding universe.
Kurzweil hypothesized that the advancement of artificial intelligence will continue exponentially,
even after Moore’s law becomes obsolete, by greater understanding of the brain in a
computational sense, improved algorithms for deep learning, as well as perhaps a gradual
switch from an organic brain to portions of a digital brain.
The singularity gets its name as the point at which man and machine become integrated
Lex Fridman, a professor at MIT, believes that AGI is an inevitable step in the development
of technology.
Fridman notes the biological inspiration in the perceptron, based on the neurons in the
physical human brain.
With the current architecture of artificial neural networks, the method of “learning”
is very similar to the method of learning our brains use, in that it is a series of
simple computations that occur at large scales.
There is a sequence in which these computations occur in order to give us the ability to think,
which we consider intelligence.
As has been noted in many of the topics, one of the primary barriers to achieving human-like
consciousness is the lack of in-depth knowledge of the brain.
The human brain is known to have the densest cerebral cortices for all animals, providing
the intelligence which allowed us to surpass other animals in survival.
Unfortunately, as a result of this density, the human brain is rendered near impossible
to map or model.
By our current technology, this task is considered truly impossible.
Furthermore, backpropagation, the algorithm on which all current deep learning algorithms
are based, is nowhere as efficient or comprehensive as the algorithm used in our brains when we
learn.
For a more detailed analysis of why we may never achieve artificial general intelligence,
check out the video by Phrenotopian, it takes a look at how AI may never achieve human levels
of consciousness
But before you check out Phrentopia’s awesome channel, be sure to drop a like, hit that
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intelligence and other fascinating aspects of our cosmos.And as always, stay tuned for
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