To clarify, I am not saying blowback is completely unpredictable. You are absolutely right that there are times when blowback can be predicted in a general sense. My argument is that a general directionality of blowback is generally not useful for crafting policy.
You're completely right that it was easy to predict that there would be some consequences to automation and people losing their jobs. Yet I do not think it was easy to predict what shape those would take. As a result, it was functionally impossible to offer useful policy measures. You can say "We should reform society away from believing productivity is king and self-worth is tied to employment", but that's itself not specific enough to be useful. "This may lead to a crisis in society" is similarly rather non-specific. How do you craft policy around "this may lead to a crisis"?
In practice, I see two recurring patterns when people try to predict blowback. First, people use fears of blowback to launder their anxieties. If you look at the conversation around AI, you will see this happening in many forms.
Second, people often use predictions about blowback to advance policies they wanted anyway. Artists want to be hired more and stronger intellectual property laws, the same things they wanted yesterday. Advocates for saving small towns in the rust belt will suggest the same retaining and social safety net policies they suggested yesterday before anyone asked them to predict blowback.
In my opinion, these two patterns are deeply linked. They are both about trying to turn confirmation bias into policy. None of the answers from this are automatically wrong, but none of them are novel. Most worryingly, neither approach offers any kind of way to reliably predict blowback so it can be dealt with via policy.
In my career, I've seen any number of engineering teams devote significant time and effort to trying to solve technical problems that never arose. Not because they were solved in advance, but because the team's predictions about where issues would arise were wildly incorrect. From this, I have drawn the lesson that we are well-advised to approach the task of trying to predict failure in complex systems with deep humility.
The more complex the system, the more humble we need to be. At some point, trying to make any prediction more specific than "something will probably go wrong" becomes a poor use of time.
This is neither the Luddite case nor the techno-optimist case. It's an argument to be skeptical of our own ability to make good predictions about the future except in, as you wisely and correctly say, very general ways.