Objections to Computationalism and Arguments Against Artificial Intelligence
Artificial intelligence (AI) has two aspects, technological and philosophical:
(1) Technological AI
Technological AI is a set of techniques (reducible to algorithms) for simulating some aspect of human intelligence in a machine. The machine is usually a general purpose computer. Whether the intelligence implemented in a machine is capable of doing anything truly novel, or is merely 'canned' procedures following logical tracks and switches, is open to debate. Typical examples of technological AI are expert systems, chess-playing programs and neural networks (which can either be implemented in relay-hardware or modelled in software on a computer).
(2) Philosophical AI or Computationalism
Secondly, and of more relevance to this discussion, is computationalism or philosophical AI, (sometimes also known as Strong AI), which is the view that all human mental activities are reducible to algorithms, and could therefore be implemented on a computer. Computationalism is an essential tenet of materialism, which states that there is no need to assume any spiritual or non-algorithmic aspect to existence.
Computationalism is thus diametrically opposed to Buddhist philosophy, which regards the subtle mind (that which survives death and goes on to the next life) as a fundamental aspect of reality, not an emergent property or epiphenomenon of matter. Buddhism views a sentient being, human or animal and its mind, as a totally different kind of thing from a machine or automaton.
Syntax and Semantics
There are a number of arguments against computationalism . Algorithms do not contain within themselves any meaning. For example, the following two statements reduce to exactly the same algorithm within the memory of a computer
(i) IF RoomLength * RoomWidth > CarpetArea THEN NeedMoreCarpet = TRUE
(ii) IF Audience * TicketPrice > HireOfVenue THEN AvoidedBankruptcy = TRUE
Such considerations have led critics of computationalism to claim that algorithms can only contain syntax, not semantics [SEARLE 1997]. Hence computers can never understand their subject matter. All assignments of meaning to their inputs, internal states and outputs have to be defined from outside the system.
This may explain why the process of writing algorithms does not in itself appear to be algorithmic. The real test of Artificial Intelligence would be to produce a general purpose algorithm-writing algorithm. A convincing example would be an algorithm that could simulate the mind of a programmer sufficiently to be able to write algorithms to perform such disparate activities as predicting the movements of the planet Neptune, controlling an automatic train, regulating a distillation column, and optimising traffic flows through interlinked sets of lights.
According to the computationalist view this 'Mother of all Algorithms' must exist as an algorithm in the programmer's brain, though why and how such a thing evolved is rather difficult to imagine. It would certainly have conferred no selective advantage to our ancestors until the present generation (even so, do programmers outreproduce normal people?).
The proof of philosophical AI would be to program the Mother of all Algorithms on a computer. At present no one has the slightest clue of how to even start to go about producing such a thing.
According to Buddhist philosophy this is hardly surprising, as the Mother of all Algorithms is itself NOT an algorithm and never could be programmed. The mother of all algorithms is the formless mind imputing meaning onto its objects (i.e. imputing meaning on to the sequential and structural components of the algorithm as it is being written).
The non-algorithmic dimension of mind, of understanding of meaning, is needed to turn the user's (semantically expressed) requirements into the purely syntactic structural and causal relationships of the algorithmic flowchart or code.
Finally, deep mathematical criticisms of AI have been made by the physicist Roger Penrose [Penrose 1989] on the basis that there are certain mathematical truths such as Gödel's theorem, which are apparent to a human observer but can never be proved by any algorithm.
[SEARLE 1997] Searle, John. R. The Mystery of Consciousness, p10 (London: Granta Publications, 1997, ISBN 1 86207 074 1)
[PENROSE 1989] Penrose, Roger, The Emperor's New Mind, (London: Vintage, 1990, ISBN 0 09 977170 5)
- Sean Robsville
Arguments against Buddhism
In order to understand the strengths of a philosophy one should attempt to refute it.
Qualia - Subjective versus objective experience
'...The Buddhist does not doubt that the brain does some very sophisticated ordering of its incoming nerve impulses into the datastructures which are the objects of knowledge. But when all is said and done, those data structures remain as objects. They are not themselves knowledge, neither are they that which performs the function of knowing.
A datastructure by its very nature must have form. But according to Buddhist beliefs, the mind is formless and is capable of grasping any object of knowledge, including facts about the mind itself, which then become objects of knowledge in their own right. Consequently the mind is potentially unbounded...'
Algorithms and datastructures
'...All systems subject to the laws of physics can be simulated by algorithms. Hence any system which cannot in principle be simulated by an algorithm must have a non-physical component. The ability to demonstrate any non-algorithmic function of the mind would be evidence that some of the mind's activities have a non-physical basis...'
'...The mind cannot be an emergent property of the brain or any other physical system, since emergent properties and emergent phenomena are psychological in origin, and require the pre-existence of an observer's mind in order to become manifest...'
The unreasonable effectiveness of mathematics in science and engineering
'...So we are left with something of a mystery. According to the physicalist worldview, the mind (including mathematicians' minds) is an epiphenomenon of matter which has evolved solely to ensure the survival of the selfish genes which code for it. Why should this 'top-level' phenomenon have such intimate access to the 'bottom level' phenomena such as quantum physics? After all, the two levels are supposedly separated by less well-understood (in some cases) explanatory layers such as evolutionary psychology, neurology, cell biology, genetics, molecular biology, and chemistry...'
The very subtle mind
'...The mind is neither physical, nor a by-product of purely physical processes, but a formless continuum that is a separate entity from the body. When the body disintegrates at death, the mind does not cease. Although our superficial conscious mind ceases, it does so by dissolving into a deeper level of consciousness, called 'the very subtle mind'. The continuum of our very subtle mind has no beginning and no end....'
'..The great difficulty in talking about non-algorithmic phenomena is that although we can say in general terms what they do, it is impossible by their very nature to describe how they do it. (If we could describe in a stepwise manner what was going on, then the phenomenon would be algorithmic)...'
Beyond the Doubting of a ShadowMinds, Machines and Mathematics
A Reply to Commentaries on Shadows of the Mind
by Roger Penrose
by David J. Chalmers
If we regard Buddhism as a combination of a philosophy, psychology and religion, then how much mileage can we get from the first two aspects before we have to start invoking religious faith?