Comment by IggleSniggle
4 years ago
I disagree. It’s the offloading of a decision space very carefully explored. Perhaps “language” and “syntax” can be generalized (ie “excrement”), but the ability to offload a decision space about how to react to a given scenario, without requiring someone to be actively thinking about the minutiae of the problem space, will always have value.
Whether that takes the form of a dependency graph in a software application or a set of assumptions (with their corresponding citations) in a scientific journal, the decision tree (inclusive of dependency graph) will always be essential.
if source code takes the form of human language I would no longer call it source code - it still might be excrement but not necessarily so.
I feel as though many problem spaces are already expressible in human language, but that “code” is just a more concise expression of the same thing.
The main issue with common language encoding is dialect (this happens in code, too, especially “common” languages like C++, Java, or JavaScript). That is to say, the assumptions you bring with you about what for example a “schedule” is affects all subsequent decisions based on it, but there are many possible interpretations for the semantics of such a thing.
It seems to me that most programming languages of today are better than “human language.” They more concisely AND precisely express the decision space.
I assumed “better tooling” meant some deeper heuristic wherein you might expect an AI to interpret your meaning based on your own enculturation, accepting the high subjectivity of any request/definition and producing an output formed by these assumptions.
I would still call this “source code” however, in much the same way that legal precedent is the source code for the next legal decision.