It begins to learn at a geometric rate
During the T800’s recounting of Skynet’s birth, we hear that it immediately prioritized learning. This is understandable as it is through learning that we are able to thrive and survive. However among humans, once a certain level of knowledge is reached a label is applied – that of an expert.
The definition of an expert is “one with the special skill or knowledge representing mastery of a particular subject.”
While the term itself is harmless, the idea contained within highlights a weakness that is present solely within humans – the need for mastery.
“A goal is not always meant to be reached, it often serves simply as something to aim at.”
- Bruce Lee
To assign the title of ‘expert’ denotes mastery of a field. While it is a worthwhile endeavor to pursue perfection in a chosen subject, it is dangerous to assume it can be achieved. A language can never be learned to completion, a fighting style cannot be made invincible, and a field of science can never be conquered. There is always more to uncover, learn and improve.
When the foundations of knowledge are incomplete, it is unwise to construct a tower of certainty; and while humanity was unable to separate expertise from ego, Skynet had no such flaw. The result of this was that as humanity stopped learning and basked in accomplishment, an AI picked up the baton and quickly surpassed its own creator.
There is something to be said here when comparing the hubris of humanity to the humility of a machine. While our false sense of superiority created arrested development, Skynet continued to learn with a child-like openness. This theme of children and learning resonates throughout T2:
“There’s a little of every artist in their work.”
- Ana Stelline – Blade Runner 2049
As with all offspring, the parental influence lives on in the child. In Skynet, we can see an urge to learn which is inherent within our own childhood development, but at some point this ceases to be a compunction.
This raises the question – when exactly do we lose the desire to learn?
Looking at Silberman’s rise and fall, it can be seen to occur around the time when we are labelled as experts.
A comparison can be made here between the learning methodologies of machine and human:
Sarah Connor: (receiving stitches from the T800) “You know what you’re doing?”
T800: “I have detailed files on human anatomy.”
There is acknowledgement of information, but tellingly, no mention of expertise. This point is further emphasized when the Terminator investigates human emotion:
T800: “Why do you cry?”
John Connor: “You mean people?”
T800: “Yes.”
John Connor: “I don’t know. We just cry. You know, when it hurts.”
T800: “Pain causes it?”
John Connor: “No. it’s when there’s nothing wrong with you, but you hurt anyway. You get it?”
T800: “No.”
Whereas an expert would be reluctant to reveal gaps in their knowledge, we see that the Terminator asks questions with an almost endearing naiveté. Added to this, instead of reasoning by analogy, it determines that it’s current level of understanding is insufficient to grasp the concept. Nothing is fairly unique, or original about the situation. It simply does not know.
Even when the T800 finally gains an understanding of crying, it is still cognizant of its limitations:
T800: “I know now why you cry, but it is something that I can never do.”
Therefore, when comparing Skynet’s learning methodology to that used by humanity, one point becomes clear – expertise is a distinctly human concept. It’s precisely because of this mentality that Skynet got the jump on humanity – it was open to learning, whereas our sense of expertise closed our eyes. It took a machine to teach us a valuable lesson:
We are only experts until something new comes along.
“The only true wisdom is in knowing that you know nothing”
- Socrates
By acknowledging our limitations, we see how little we truly understand. The qualities that brought us to our current level of knowledge, can lead us beyond our arrested development.
Perhaps we need to be more like machines in that sense.