I think you'd have to count the American Civil War as a conflict caused at least in part by the industrial revolution, which would dramatically increase the toll it took in North America.
The cotton gin was textbook automation. In a strange twist of fate, it actually increased the demand for labor. Because it was very labor intensive to remove the seeds from a cotton boll, cotton wasn't a very profitable industry. After the gin (short for engine, what developers call automation engines), demand for labor and land skyrocketed.
The cotton gin is an example of an automation removing the need for labor (deseeding cotton) and subsequently creating a greater need for labor elsewhere (planting and harvesting). Of course, in this example, the increased labor demand ultimately resulted in 720K deaths.
As I've mentioned before, there's a book from 1926, "Chapters on Machinery and Labor", which outlines the three basic cases of what happens when new technology is introduced. Their examples are the Linotype, the glass-bottle blowing machine, and the stone planer.
The Linotype was a win for printing workers. Typesetting had been bottlenecking the process, and with fast typesetting, book and newspaper prices came down, and the volume of printed material increased enormously. That's the good case.
The glass-bottle blowing machine is the not-so-good case. Bottle-blowing used to take a team of five people trained to work together and manipulate molten glass, blowpipe, and mold with tight coordination. This was a skilled trade and paid well, but bottles were expensive. Automatic bottle-making machines could make bottles rapidly with minimal labor. Bottle sales went up, and the bottle business grew, but the skilled trade was dead. Most of the workers were shoveling sand in one end or taking bottles out the other. This didn't take much skill. Operating the machines was not too hard. You probably needed a maintenance guy who really understood them, but only one for many machines. So most of the skilled jobs went away, replaced by low-paid entry level jobs.
The worst case was the stone planer. Back when brick was the key building material, stone lintels were used over doors and windows to provide structural support for the bricks above. Stone was chipped by hand by big guys with big hammers and big chisels to make flat, rectangular stone beams. The stone planer was a powered machine for squaring off a block of stone. Like a wood planer, but heavier-duty. No more need for big guys with chisels. Huge increase in productivity. But the market didn't grow, because stone lintels were a minor building component and cheaper stone lintels didn't mean more demand for them. So most of the workers lost their jobs.
Those three outcomes still apply to many cases of computerization.
Great examples. Really demonstrates the complexities we face.
This may be the best argument for basic income. Why don't we just admit that we just haven't a clue how things are going to pan out? Things could be fine, or things could get very nasty. Looked at this way basic income is not analogous to social welfare/security – when we admit that we have no clue how the future is going to unfold then basic income looks more like social insurance.
This puts me in mind of a thought I had this morning. Why are narratives compelling? Because they explain events. In the past before formal methods allowed us to develop accurate models humans used a narratives even where they are inappropriate. Now, because models have been so successful the pendulum has swung the other way and we tend to over-rely on model based explanations when really we have no clue.
What am I saying? Just suppose that the "elephant curve" has been brought about by automation or the 4th industrial wave as the article calls it. We have many many people predicting outcomes based on economic and social models that may fail to apply in spectacular fashion. Maybe what would be better would be to institute basic income to ride out digital automation while models are tested and refined. But also let us collect stories from now and from the recent past to use as cautionary tales whose main purpose is emphasize the point "we don't really have a clue and anybody who tells you they do is talking out of their ass".
