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My question might spark a fair amount of discussion, however I think it could be a simple discussion.

Will future computer scientists slowly attain ideas and concepts from a much more rounded field (cybernetics) but still claim it is comp-sci domain? will cybernetics (as a philosophy, not cyborg creation) slowly become a smaller field within another field? Or will eventually cybernetics be the backbone for every engineer wanting to design a system, of any kind? I'm new to engineering and have been an arm-chair philosopher for a while. I will edit my question if it is too vague.

An underlying question needing an answer would be:

"would studying cybernetics aid engineers/designers in in their approach to creating better systems? Cybernetics seems swept under the rug, it is thought of as 'people who make cyborgs', but if I were to enter into deeper studies, would it benefit me in my engineering future"?.

  • Could you clarify what "cybernetics as a philosophy" would be? – shane May 20 '14 at 19:32
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What is your definition of "the much more rounded field of cybernetics?" One definition might be "control-theory applied to try to explain other fields" another might be "anything that cites a paper by McCulloch and Pitts," pretty much everyone has their own definition. "Cybernetics" (whatever it is) and Artificial Intelligence (whatever that is) suffer a problem that is also shared by philosophy: They deal with problems that we don't really understand. As soon as the problem Cybernetics/AI/Philosophy is trying to solve becomes well enough defined to solve the problem, it becomes its own discipline.

If you want to be a good engineer you should take a lot of applied mathematics.

  • Every engineer will benefit from taking a course in control theory at the level of, say, the book Modern Control Engineering by Katsuhiko Ogata (3rd or 4th year undergraduates with a strong background in linear systems, systems of differential equations, network (circuit) theory, linear algebra, calculus of variations, and transform methods). Most Mechanical Engineering, Electrical Engineering and Chemical Engineering departments will offer such a class.
  • Every engineer will benefit from taking a lot of statistics. Communication systems engineering (detection/estimation/modulation), image processing and (so called) "machine learning" are all heavily dependent on and/or outgrowths of the field of statistics.
  • Every engineer will benefit from learning to program (most modeling is done by writing computer programs). This includes getting a strong background in numerical methods.
  • Every engineer will benefit from taking as many courses in optimization as they can find. This would include at least linear optimization.
  • I come from a computer engineering background, so I think every engineering student would benefit from a course that emphasizes practical techniques in abstraction, hierarchical design and information hiding. (In computer engineering this would be taught in a Software Engineering course, often to 2nd year students with a book like Program Development in Java by Liskov and Gutag. I don't know what they do in other engineering fields.) I also think an algorithm design course at the level of Cormen, Leiserson and Rivest's book is invaluable, but that might be much too specialized for other engineering disciplines.
  • that is great guidance, I can see how that fits in to place. I've been reading a fair bit since original question. I downloaded a few ebooks "Where are the Cyborgs in Cybernetics?" -Ronald Kline and "An introduction to cybernetics" by W. Ross Ashby. @Wanderin Logic Thanks for your answer, the question seems so naive now. Cybernetics doesn't have such clearly defined walls/limits as a field of research that could help an engineer. So some bedtime reading will suffice, and focus more on other topics such as you mentioned. – ClankWarrior May 20 '14 at 9:15
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There's tremendous overlap between the domains labelled "artificial intelligence" and "cybernetics" with no clear division. To generalize the difference, I'd say AI is a branch of computer science while cybernetics is not. Working in AI there's (usually) an underlying assumption that a computer will be involved, while cybernetics isn't so constrained.

Cybernetics preceded AI, and AI builds upon some areas of Cybernetics, but something like neural network pattern recognition (originally developed under the banner of cybernetics) would now be considered AI. In a sense AI has poached much of cybernetics. This might simply be because so much of the work in these areas is performed by people called "computer scientists", or that "artificial intelligence" is a more accessible or exciting name than "cybernetics".

In any case, the work of cybernetics pioneers (like Gregory Bateson) is definitely of interest to anyone that designs systems, computer or otherwise.

  • thanks. That's great. I'll look up G.B. what you said totally harmonises with what I'm reading. I love philosophy and also engineering. Cybernetics seems to be a great field for an inquisitive mind. – ClankWarrior May 21 '14 at 14:56

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