AI deep learning has made gains in image recognition and translation but howlers highlight still glaring misses
This is the second installment in a series. Read part 1 here.
The ultimate root of the stupidity of AI systems, I argue, lies in their strictly algorithmic character. AI as presently understood is based on digital processing systems that carry out binary-numerical operations in a step-by-step fashion according to fixed sets of algorithms, starting from an array of numerical inputs.
Some may object to this characterization, pointing out that AI systems can constantly change their own “rules” – reprogramming themselves, so to speak. That is true; but the self-reprogramming must follow some algorithm.
The same applies to the processes by which the system reacts to various inputs. Ultimately each AI system is governed by a set of rules and procedures that are embodied in the design of the system, and that remain unchanged during its operation as long as the system remains intact.
Alan Turing, one of the great pioneers of artificial intelligence, succeeded in giving a precise definition for the general notion of “algorithm” or “mechanical procedure,” which subsumes all AI systems that could possibly be realized on the basis of digital hardware. Turing demonstrated that any such system is mathematically equivalent to an abstract entity now known as a “Turing machine.”
Moreover, there is a single, universal Turing machine that can simulate any other one, when the latter’s design is input in suitably coded form. On this basis one can investigate the theoretical possibilities and limitations of AI systems by mathematical methods (speed and other physical aspects being left out of consideration)
Abstract scheme of a Turing machine. Source: Wikimedia
The diagram shows an endless tape with squares in which either zero or one is written. The machine has a head that can read, erase or print a zero or one, and move the tape one step to the right or left. The numbered rectangles below contain the rules (program) of the machine.
Rule 1 says, for example: if you read a zero, then erase it and print a one, move the tape one space to the right, and go to rule 4; but if you read a one, then leave the one unchanged, move the tape one space to the left, and apply rule 1 again. The machine starts at rule 1 with some sequence of zeros and ones written on the tape. There can also be a rule that tells the machine to stop.
You can link to a (rather slow) animation, showing how a Turing machine works.
No matter how sophisticated an AI system might be, no matter how we might combine AI systems in various ways in interacting parallel and self-modifying hierarchical architectures, what we end up with always boils down to a Turing machine operating under a fixed set of governing rules.
....MUCH MORE
Stupidity is built into AI systems, both at the lowest and the highest levels.
On the micro level we have the billions of individual switching elements on the IC chips, each of which carries out its on-off transitions in a 100% deterministic, rigidly mechanical fashion. They are 100% stupid. That is what they were built to do. They hardly resemble the living cells – neurons and glial cells, embedded in the interstitial system of the brain – that constitute the substrate for human mental processes.
At the macro level the behavior of an AI system is subservient to its governing rules. It has no way to change them from the inside. It interprets and reacts to all events accordingly and will continue to do so, even when they lead to disaster....
