Why does Amazon always pay people thousands of dollars to move into a very expensive area, and then pay them above market rate? (I don't work for Amazon, but it makes the point.) Because labor costs aren't a big deal when you are so well automated.
As long as the revenue per employee is so high... It makes much more sense to pay 200k to bring in 1,000k than to pay 50k to bring in 500k. You make 800k vs. 450k. Paying someone 0 isn't even worth it, because of management overhead. Dealing with people is hard. You deal with computers when you can. No matter how cheap that pay gets, as long as the difference in revenue is greater than the pay difference, it is a no-brainer.
This is why people who know how to automate solutions get paid so much. It isn't about productivity of coding. It is about business-level productivity. The relevant cost is not the cost of labor, but the ability to scale vs. the overhead of managing product and scale, which spreads that cost out until it is almost nothing.
This is why professional services is dying. Throwing people at the problem is a waste of everyone's time. Everything has to be able to work self-service, and at unlimited scale. Everyone doing that is making a ton of money.
I get job candidates that want more than 100k because they are programmers, but they have never automated a thing in their life. They come in after being in several failed startups, complaining about a lack of business plan. I wouldn't even pay them 0 because they bring failure. They don't even know how to do basic sysadmin stuff.
That is why devops is a thing now. The ops part makes the money. The dev is just a means to that end.
I don't believe that we will ever run out of "jobs". Even today, we are nearly fully automated in our survival needs. Even in the 1920s, philosophers were talking about forcing people to only work part time days because automation reduced the need to work to survive, and we are far more productive now than then. But nearly everything is about increased luxury and entertainment, even today. People will keep paying for that forever, even when they don't have to worry about survival.
The only economic issue is that the income inequality is so great that consumers can barely afford to pay for their consumption tech, and can't afford to risk the development of their production capacity. I think nearly everyone should be both consumers and producers. We don't really *need* capitalism or communism or socialism. We just need whatever system we use to share consumption with production. Let's face it. The only productivity issue we face today is environmental issues. We need to go clean, and incentivize that fast. That's it. The rest is just annoying foreign policy stuff that will be resolved when we can share consumption in a clean way, and no one will be incentivized to be violent anymore, even with silly religion memes.
We are talking about economic fairness between generations, which is indeed generally understandable by looking at the well-documented flow of money between generations.
Straw-man arguments are exactly why I just point to the data these days. Since you are apparently so good at logic, that is all the more reason why you should be looking at the data.
I have been talking about it for 15 years, and there is only one thing I have seen so far that is even going in the right direction.
What is that one thing?
I'm glad you asked. HTM is the first thing that I have seen that comes from the study of how intelligence works in connection to the physiological component.
The importance of the physiological component was first identified by Hermann Helmholtz, the founder of modern physiology. In the 1860s, he came up with a theory for studying any sense system, and basically created a modern aesthetic theory in order to study physiology. He described the aesthetic flow of information from the physical, to the physiological, to the psychological, and was the first to posit that proper psychology needs to interface properly with physiology, and that the philosophical error of ignoring the physiological component is what leads to problems in studying both psychology and physiology.
I found this while actually studying aesthetic theory to develop a proper descriptive music theory. In order to find anything on aesthetic theory, I had to read original sources going back centuries, and found that scientists back then spent a lot of time explaining their philosophical approach, because any major work involved the creation of a new scientific field, and this needed to be explained philosophically to be credible. So nearly all aesthetic theory is tied in with scientific work on the senses, and existentialist philosophy, and most of that is tied to destroying the philosophical error of mind-body duality, which, as you are probably guessing by now, is something that must be done for the field of Artificial Intelligence to make any sense at all.
To this day, the philosophical error of mind-body duality is still blocking a lot of Artificial Intelligence research. When you do not integrate your model of the mind with a model of the body, you can't get past one of the most famous philosophical errors going back thousands of years.
And this, of course, explains my skepticism that humans will be so easily replaced. It would first require a total defeat of the mind-body duality problem, and that has been a struggle dating back thousands of years. Even after it is defeated philosophically, it takes decades for this to produce its output on society. Historically, it takes about 50 years, and that is not limited by knowledge but by the speed that humans *forget*, meaning that people need to *die* for progress to happen. The ironic thing is that, as technology has increased modern lifespans, it has been harder and harder for real paradigm shifts to happen.
I mean, we in the US still can't get over our bad relationship with Russia, simply because not enough politicians have died of old age. The Baby Boomers are still afraid to hand over the reigns of the country. Sorry, I have a tendency to ramble off on tangents. I'll shut up now.
That's why it's good to have absolute numbers, like at census.gov. The National Academy has been citing the data for years with tons of insightful research into which policies are more or less fair. When you have absolute numbers, it is really easy to define fair and equal. Hint: it involves an equals sign.
This is the scientific way to measure fairness, as opposed to the political way of controlling the visibility of contexts to make an argument. Every question you raised rhetorically has a scientific answer that is waiting for you in data that is already freely available, and thousands of people research this, and no one listens to them. It is frustrating to see this. We need fewer lawyers and more scientists in politics.
The cruising aspect would be too much of a problem. Can't have a bunch of slow cars driving around. You could just have ZipCar allow cars to be parked in random spots, but only if someone else has agreed to take responsibility for it, otherwise you will have parking ticket issues. But anyway, there seems to be a lot of room for improvement without needing to have 100% automation. Maybe have ZipCar negotiate parking with the city, and a small fleet of people move ZipCars around to where demand is higher.
I think the 100% automation goal is basically a fundraising tactic, since you can tie valuation to the 100% automation assumption. But it is a lot further off than people think. Meanwhile, Amazon is going to be making real, incremental improvements, and not making a big deal about 100% automation, because they just automate what makes sense at any given moment. But Amazon is much more smooth at convincing people that they will be ahead in the end, without needing to trump up this 100% automation claim.
I think Uber thought that they could trump up 100% automation, and use the funds to leverage their way into China, and then realized that economic forces are greater than their imagination. Now they are getting hit with reality day after day. In software, we are used to being divorced from physical limitations, and it seems that Uber is a prime example of the software mentality going a step too far.
Human beings were created by water to transport it uphill.