Because one will be a net benefit to society and the other probably won’t be?
I'll concede that automating manual labor has made consumer products cheaper. Whether that is wholly a net benefit, I think, is up for debate. When you consider the externalities like the environmental effects of rampant consumerism and the erosion of the middle class via a reduction in manufacturing jobs, I think there's plenty of basis for at least arguing there is tipping point on automating away manual labor. To say automating manual labor bluntly (and without careful consideration of blowback) always leads to a better society, I think one needs to define what they mean as society and what metrics they're using to define "better." I, personally, don't think raw GDP is a good measure of the health of a society.
If anything, I think automating knowledge work has as at least a potentially larger upside. The downside will largely be borne by the upper-middle and upper-classes, which is why the GGP can read like a classist perspective.
That aside, what exactly is suspect about finding meaning or joy in work? Is the quintessential experience meant to be soulless and grating?
Of course not. Few things in life are more fulfilling than a job you absolutely love and are excited to whack at every single day.
But your question raises another one of equal stature: Is the quintessential experience meant to be a job? If we are creative enough to make rocks that can learn to do our jobs for us, surely we are creative enough to craft an economic model which allows us who no longer need to work to paint or write poetry or rebuild antique engines without needing to starve?
As far as crafting a post-scarcity economic model goes, it's not the problem of dreaming one up, it's the pervasiveness of scarcity. Even if all of humanity's basic necessities are one day a given, scarcity won't disappear, just shift around (maybe as transportation for the otherwise-infinite supply of consumer goods? Or living space away from dense urban centers? Maybe even the kind of heuristic analysis abilities humans are unmatched in to keep the matter replicators functioning?)
More to the point, saying that this kind of luxury will exist in a thousand years doesn't nullify the concerns of the present, and probably wouldn't convince most people to forfeit their employment to machines likely owned by the uppermost classes.
I think there's a distinction in that I was referring to "knowledge work" which isn't explicitly creative/expressive/stimulating. Many would classify much of research or law as "boring" even though they are knowledge work.
>what exactly is suspect about finding meaning or joy in work?
I did not mean it as wrong to find joy in your work. On the contrary, I think that's a worthwhile goal. But the distinction I make is that any work can be found to be fulfilling. It's the distinction between "finding your passion" and "cultivating your passion." I've worked with people who found meaning in their job cleaning offices and others who treated the design of rockets as soul-crushing. I think it has more to do with the person than the job. So I push back a bit on the false dichotomy created by classifying "knowledge" jobs as inherently worth saving from automation while manual work should be fodder for it. I also think the focus on a job for fulfillment is a bit of a red-herring. I think what people really need are to be valued members of society and, for many, a job is a means to that end (and maybe not even a good one).
Higher wages in agriculture would mean a combination of less profit and/or higher consumer prices. That is not a sin. It is mostly politicd that demand that food prices have to be low so that the population don't realize how poor they are and much they are being robbed on corruption and waste.
It's perhaps worth pausing to consider if we have any kind of useful ability to predict blowback on anything but a trivial scale. It was fifteen years between the invention of HTTP and the creation of Facebook. It was twenty five years between the invention of HTTP and the Cambridge Analytica breach. I do not think any person could have meaningfully predicted those on those timescales.
If we cannot currently usefully predict blowback, then what reason is there to try to anticipate it as a matter of policy?
We can certainly predict that when automation happens people will lose jobs. In a country where productivity is king and self-worth is tied to employment, we can predict this may lead to a crisis in society. And we also know people tend to turn to vices like drugs during those times. So I don't think things like the opioid epidemic that hit the former manufacturing centers of the country are unrelated nor completely unpredictable. They just sometimes take decades to play out.
I'm not making a Luddite case that technology needs to be stalled. But I'm also not making the techno-optimist case that everything will eventually work out if we just plow forward with reckless technological abandon. The latter runs the risk of a lot of increased human suffering in the short term at the very least.
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.
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.
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.
When your system is predicated on taxes borne from income, and you implement a disturbance that displaces that income, it doesn’t take a rocket surgeon to see there will a problem looming on the horizon. It’s really just connecting two very obvious points that doesn’t need hindsight centuries later to see. People have been ringing the alarm for decades now, policy makers just found it easy and expedient to ignore them.
I think many politicians knew this but policy development has a different wrinkle. Politicians are incentivized to take a short term perspective because election cycles don’t operate on the same time scale as large scale societal issues. It’s the same reason they are incentivized to raid the general coffers for projects that will be completed during their tenure and leave long time horizon problems for someone else to fix. (If you disagree, look at Illinois and their public pension issues)
(And not to be pedantic, but automation dates back a couple thousand years, at least to the use of water wheels to automate grain flour production. The industrial revolution dates to the late 18th century. While they are related, they aren’t the same thing)
Replacing a task with AI that otherwise will be done chemically with environmental degradation or not done at all because people won't or can't-- AI in that context makes things better.
As for attempts to deploy AI as a replacement for sophisticated human work like "automating knowledge work", the output will be worse and it's a race to the bottom on quality. As we see from our algorithmic-driven tech industry friends, robot-led workstreams benefit society only in the short run. In the long run, people come to miss-- and their lives are diminished by-- an absence of quality, humanity, agency, caring, fairness, all the things algorithms cannot and will not ever be or do.
Anyone who is serious about this topic only discusses in terms of AI + humans (as a combination) and not AI as a replacement for sophisticated work. Statements beyond that reflect a lack of appreciation for either the complexity of the topic or for what society actually expects out of a "knowledge" workstream.
>an absence of quality, humanity, agency, caring, fairness, all the things algorithms cannot and will not ever be or do.
I would argue that automation can be quite better than humans on many of these domains. When they do fall short, it's often because they are reflecting (and in worse cases, amplifying) the shortcomings of humans in these same areas.