3 ms·
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 sens
by Kalium 3y ago
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.
- bumby 3y agoYou are right that I was speaking in generalities, in part because a forum isn't the best format for these types of in-depth policy discussions and also because I don't claim to be a policy-wonk. In fact, that's why I prefer engineering roles. But I'll try to clarify a bit. Let's dilate on "This may lead to a crisis in society" to try to get to a policy. If we can agree on two things we might be able to get a rough scaffolding of a framework to discuss policy. 1) government programs, like everything from social security to roads/bridges take money to run and 2) the vast majority of federal funds come from taxes related to work, like income taxes and social security taxes. By extension, if automation effects jobs, it then affects the programs that create a stable society. So one aspect is: as automation takes people's jobs, it potentially threatens the ability of government to fund its programs. If a society ignores this, it faces a potential "crisis" if those programs help create the conditions for a stable society. There's a few ways one could address this. On the cost side of the equation, we could use austerity measures to reduce the cost burden. There's certainly something to be gained here, and it would be a long digression to decide which policies are a priority. (For example, I've heard research saying that roads provide the most benefit on a cost basis, followed by early education programs like Head Start). On the supply side of the equation, it seems like there are two options: a) help workers get replacement jobs that pay at, or near, what they had before their job was automated away or b) get the money through a different, non-income based policy. It didn't seem like we did a good job crafting policy in the rust belt related to a). There wasn't much re-investment into those communities or workers, compared to what was gained by automation. There are various ways to address b), including restructuring corporate taxes or instituting an automation tax to make up for the displaced incomes formerly garnered by workers paying a tax. But we went the other way on those, too. While I concede those are very high-level, the intent is to show there are real discussion points that can be crafted into policy and it's not just some hand-wavy rhetoric.
- Kalium 3y agoI believe you may have overlooked one of my key points: we did not have any useful way to predict those consequences at the time production was being automated that would have marked them out as particularly likely. Automation started in the 1780s, with the industrial revolution. The initial impacts had a lot to do with creating vast numbers of jobs, driving down the cost of all kinds of consumer goods, and heavily driving urbanization. I can't see any easy way to get from there to the rust belt if I'm someone looking forward in 1780. Right now we can treat this as obvious only because we have the benefit of hindsight. I cannot imagine any way in which the modern history of Detroit would have been reasonably and usefully predictable from 1780 (at the time it was a frontier fort under British military control). You're right, impacts can be decades off. They can even be centuries off. There were a lot of equally credible people who thought automation was going to have utopian consequences that didn't include people losing their productive economic positions. This isn't a binary, either. There were plenty of other possible outcomes as well. How were people in 1780 to know what we do know? What happens if every predicted outcome is taken seriously? What happens if they're then all wrong, or not right on a sufficient timescale? I know how I would expect that to interact with limited government resources. At the end of it, I think we're likely limited to dealing with consequences and trivially short-term prediction. Those, at least, we have a reasonable shot of observing.