Implementation and Explicitization of theories
Recently while exploring a certain topic through chatGPT, one of it's lines mentioned the explicitization of certain theory(ies), which caught my attention, and made me psuedo-realize (half-realize ? basically transferred a thought from my sub-conscious to conscious) that the entire branch of computer science has mostly been about the implementation and explicitization of various academic theories we have come up with over the years.
Thus, as per my love of making lists, here we are, trying to list down all the theoretical fields or theories which computer science has helped implement/explicitize:
Mathematics. Most obvious, in fact, the entire field of computer science is the real life realization of math or mathematical concepts. Computation happens when we can express certain logic and transitions in our real world. Computing devices existed a long time before modern computers came into being. On a more abstract level, the type system makes mathematical proofs explicit.
Economics. At first, we might think that certain simulations could be considered as the explicitization of economical theories, but it's not what prompted me to write this piece. Through programmable money is how we can make theories about economics more explicit, hence: crypto currency. I am not sure if cryptocurrency is a viable solution of the question that is money, but I do agree with the llms on this point: if we decide to create a global crypto-currency (especially with smart contracts), we thus could explicitize/codify various theories or ideas, and directly influence human behaviour (to a certain extent).
Morality/Ethics. With the advance of certain areas of AI and robotics, we must decide on a universal code of ethics, since it may turn out to be necessary in real life scenarios: the trolly problem posed to a self-driving car. With the advent of large language models, this has become even more important. The LLMs must be able to tell apart moral actions from immoral ones, and must have an internal moral compass, lest it falls into the wrong hands. Another example would be AI psychosis.
Law. Now this is a mere attempt, and no where near real-life usage, but rather just an experiment: This paper explores how high-level programming could make policies/laws more explicit through converting laws into code. Though this is still limited, as it requires a lawyer and a programmer both, to clarify ambiguities, which means any bias or error in the initial interpretation of the law would get implementation into a unambiguous and explicit form, code, and stay like that until corrected or challenged.
Simulations. This seems like an overall implementation to either check or implement various theories, from economics, evolution to civilizations. Physics engines, chemical reactions are also some other examples of simulation. Though this is a legitimate way computers have helped us implement certain theories, this doesn't feel like explicitization, but rather the setting up of initial conditions, and letting computation perform it's magic.