The growing need for human robot-minders could juice the remote workforce
wsj.com
wsj.com
[1] https://www.nytimes.com/2013/05/04/us/where-mail-with-illegi...
https://www.lesswrong.com/posts/7pNJ9aQxRMrWAnkmf/thank-you-...
That article is essentially refuting itself.
The "good case" was typesetting. The introduction of the Linotype enormously increased the volume of material printed and created more printing and typesetting jobs.
The "medium case" was bottle making. Hand-made bottles were expensive, taking a trained group of about five people to blow a bottle. Machine-made made bottles were cheaper, and required far fewer people to make. Cheaper bottles increased demand for bottles, but, overall, employment in bottle making was about the same or less. Also, much of the labor was now low-skill machine tending - putting in sand, taking out bottles. Only a small number of bottle-making machine experts were needed.
The "bad case" was the stone planer. Brick buildings used to have stone lintels over doors and windows, and there was an industry of big guys with chisels hammering out those things. The stone planer was simply a big steam powered planer for stone slabs. This required far fewer people. But it didn't increase demand for stone lintels, because they were a minor building component, not significant enough in cost to increase demand for brick buildings.
I'm going to ask for a cite. Automation would have led to a resurgence of the textile industry in the US if that were the case.
Most of the textile mill towns are gone, never to return.
It's the canonical story in the history of automation and jobs. You're one of today's lucky ten thousand :-)
A car going at 60mph (~100kmh) travels at 26m/second. 4G has a ping of ~70ms* on top of the time from the cell tower to the operator's computer.
However, I found quite a variance in pings when browsing on the phone, anywhere from 200-300ms at times (maybe due to changing the tower).
So round trip might be at 600ms. Then we account for variance in bandwidth, human reaction time etc. All in all we might be looking at a delay of at least 1s. Guesstimating, of course. That's still 26m of a 2 ton vehicle going at 100kmh without oversight.
* According to https://www.4g.co.uk/news/4g-injecting-new-lease-life-online...
A 200ms round-trip would still be comparable to some drivers on the highways right now, but it's certainly suboptimal.
Instead imagine a system that is "good enough" that at it's most risk averse configuration it will drive itself in normal conditions, but occasionally it will seem to slow down for now good reason, or even stop, while it waits for a human to intervene because its not sure if its correctly reading the environment ahead.
It would need to be good enough to be able to work well enough of the time to be able to reliably come to a safe stop, but it would mean you'd be able to have one person monitor many vehicles.
The exception is when I know I will trigger an age check.
But to the car comparison: If that happens enough that people won't use them, then they're not good enough unless it drives the cost down enough that people decides it's worth the wait.
But, I there are scenarios where remote operation is safe. Maneuvering in a tight alley. Any scenarios that don't require speed and where a failure scenario is bricking an already stationary vehicle. It could also be identifying obstacles (car thinks steam venting from the sewer is a solid object) or approving rule-breaking (allowed to place a wheel on the sidewalk.
But, I think the bigger problem is coverage and reliability. Relying on mobile networks for this type of life-or-death functionality strikes me as extremely dangerous, and that would remain true even if we increased reliability by a factor of three.
- awkward roads with cones, tricky parking etc
- high speed collision avoidance where the car transfers legal liability to an offshore contractor immediately before impact
Imagine a HFT bidding market like adwords. Guilt as a service. Wonderfully dystopian. Paging Mr. Doctorow....
When you rob someone of their humanity, then you too lose your humanity, making us all robots that can be disposed of anytime...
Think about the pin makers at the beginning of John Adams' "The Wealth of Nations." Atomation of meanieal tasks like these means the pin makers are replaced by educated generalists (at least to some extent) who operate and maintain machines.
This terrifies me. The speed of light RTT from the west coast to India and back again is around 100msec. This is on the order of human reaction time. Real world latency we are talking way more than that. I get wacky routes to India traversing most of the world, so I get pings >400msec from the US to India. 400msec is more than enough latency to kill you. Teleop is a silly idea for big fast death machines on wheels (cars), especially if there’s significant latency in the teleop.
This sort of real-time control would probably have to be done on the same continent at most, because of purely physical limitations.
//The real argument
They fraudulently claimed that they had some kind of machine learning system that enabled them to quickly, accurately and privately convert voice mail to text. The reality was that they had a call centre in India manually transcribing.
With AI currently set up as the "next big thing" this article is just another version of the "Natural Language Processing" and human augmented AI, that is being used by almost everyone to "fake it until you don't need humans any more" (see Apple, Amazon, Google listening to our audio as a backup for Siri, Alexa, and Now). A necessary stop gap.
I think there is a big opportunity to look past the stop gap and talk about technologies that are going to 10x the things humans are already good at (creativity, empathy, intuitive problem solving, ...).
Though, there is legal indemnification which could be used to get a contractor (the company) to pay when there is a screwup. But that's a matter of contract negotiations between companies.
Now they are actually in the process of automating the trains, which has been criticised by many as a vanity project. Certainly it has not been shown that it makes financial sense. And it has been decided that they will retain a "captain" aboard the train, for safety reasons, as someone has to lead passenger evacuation in case of an emergency. So the total salary savings will be essentially zero.
Fully level-4 automated may makes sense for new builds. But for retrofits, you can't satisfy the overall requirements without a human physically present.
If you want to erect barriers to increase safe station capacity, you need that too.
Finally, the automated trains will have smoother acceleration and braking, reducing wear and tear on the trains and tracks.
The DLR has been driverless, since it was introduced in 1987 ─ it is a working example of the paradox of automation, which states: the more efficient the automated system, the more crucial the human contribution of the operators. Humans are less involved, but their involvement becomes more critical. This will be the unwritten hard limit for the time-being, when it comes to implementing the levels of autonomy, irrespective of the condition of the rolling stock or wage costs, which are moot.
https://en.wikipedia.org/wiki/Docklands_Light_Railway
https://www.citymetric.com/transport/one-picture-dlr-morning...
[1] https://jalopnik.com/meet-pat-the-drill-thatll-dig-a-new-und...
[2] https://sf.curbed.com/2018/6/18/17464616/bay-area-subway-tra...
is as good a place as any to start. It also has plenty of citations of its own if you want to dig further into any aspect.
Basically. the biggest cost of building a tunnel is excavation cost and the cross sectional area of a tunnel is the biggest factor affecting excavation cost for any given ground condition.
Secondly once you add people you have to add emergency escape tunnels and related systems which is just more tunnel that needs digging.
And perhaps the most important thing - when there is a human driver, he is also responsible for his own life, so he will drive very carefully.
This is a shit idea and it will fail.
^Traditional in the "standardized job that 5k people do for us."
Quick-reaction collision avoidance will be controlled by radar (77 GHz etc.) or lidar.
If you look at the first chart in that article, bank teller employment peaked at a bit over 600,000. If you follow the link to the BLS projections given near the end of the article[1], you'll see that bank teller jobs in 2018 are down to 472,000 and expected to decline by another 58,000 over the next decade. Bank teller jobs per capita is declining more rapidly, since population is still growing.
[1] https://www.bls.gov/ooh/office-and-administrative-support/te...
In order to render millions of people jobless, we have to achieve Artificial General Intelligence.