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This, so much this. I feel that society as a whole is eeking slowly into 80-90's level computing, but it is completely asymmetrical. Some parts of society are hyper-evolved, like social media and entertainment, but others are stuck in earlier phases like your example. In that case even 70's level tech and theory would be an improvement. CS and educated tech people in general are in a hyper-educated bubble where it is normal to talk about distributed systems and algorithmic complexity, but there are an awful lot of smart people without those backgrounds. A lot of knowledge that's traditionally branded as "technical" is IMO generally useful, but overlooked. For example basic queuing theory in of itself is exceedingly useful. Nothing fancy, just the steady-state, blocking probablity, what chance of how many "clients", etc. I witness very large (gov) organisations lacking any kind of in/out flow modeling, statistics, etc. No dashboards, no insights. Just going by feel. Everybody is "overworked", but if you dare to say it might be a good idea to start quantifying some of those parameters you'll be in a very silent, very awkward room and will never be asked anything ever again. I wish I was kidding. AI? Let's start previous-century level process automatization and professionalization first and we'll see in a few decades if we're anywhere near ready for the next step. Edit: It's btw interesting that most (high-level) managers at these orgs are all alphas, like history and political science majors. I guess it's no wonder they are trying to solve production problems through "consensus" and endless meandering, but it's also frustrating. |