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[–]Disbursed-operant5 points6 points7 points (5 children) | Copy Link
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I highly second this and other replies that are voting for fundamental CS than just 'coding'. When learning CS the right way (i.e. through projects), you'll learn coding as a side-effect. But CS is more than coding. It is a mindset. As a programmer (now-a-days at least) you read the manual (stackoverflow) and put pieces together until they work. With CS, you develop the mindset of what can and cannot be automated, what is a worthwhile goal and what is a waste of time. So going by your other replies in this thread, I'd say you're on your way to developing a CS mindset. Formal CS education will sharpen it. While studying it though, keep your ears firmly pressed to the ground and look for opportunities. Frequently, they're found in the most unlikely places.
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Obviously no one will have a definitive answer to this question. I think that while AI will replace the more mundane automation jobs, it will probably not replace jobs that require creativity. I'm not using the word 'creativity' in a shallow sense like women do (e.g. sitting on a beach in a bikini reading a cheap paperback softporn). In creativity I'm including coming up with a plumbing hack in a tight space, tracing that tricky electrical fault, finding that elusive computer bug, inventing a new supply-chain paradigm, finding a legit tax loophole to benefit from, coming up with a novel sales or marketing pitch, thinking on your toes in a tough client-setting, ...
So, despite the recent advances in having AI replicate styles of the great painters and musicians of the past, its just that: a replication. In my mind, it all boils down to the P vs NP problem. I believe that P!= NP, which in simple terms means that 'creating something' is harder than 'verifying or replicating something once a solution is available'. In other words, real life situations have too many variables for a computer to loop through. Some examples are: Natural language has too much nuance for a neural net to capture perfectly. Real-world driving conditions have a greater variability than what can be encoded in software. Business decision making, even at a middle management level, has too many subtleties to be performed by a robot (some might argue whether we need middle management). These and many many other examples have me firmly in the camp that AI will not automate (male) creativity.
Make no mistake, AI will irreversibly shift the jobs landscape. "Lookup"-based jobs, consistency-checking and verification jobs etc will be automated (already are). But creativity-based jobs will not. So to answer your question (in my limited capacity), one path is to learn CS/AI (its much less exciting than what MSM paints it to be). Other is to find employment in fields where there are 'too many variables'.
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A perfect problem is a 50-50 of manual labor (domain expertise) and automation. Too many programmers have the skill but arent close to the problem space. IMO its better to be a domain expert who knows programming (and sell your solution for $$) than to be a pure programmer who is a world-expert at automating, but has nothing to automate. Access to gnarly problems is worth much more in the real world than deep programming knowledge in a vaccum.
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