Many people lost their manufacturing jobs to robots, but will the same thing happen with trucks? (Revised)

Big tech money is chasing the development of self-driving trucks. Google, Uber and Tesla are investing heavily in this technology and a new autonomous truck startup called Embark has already pulled in $17 million of series A funding.

Though Silicon Valley is pouring money into self-driving trucks, it’s hard to tell when this technology will become widespread and cause an economic dislocation for a significant part of the American workforce.

Accurately pinpointing a time frame for when this disruption will occur is important for trucking, its related industries and consumers. But there are many variables that still need to be accounted for when estimating how many years it will realistically take for these trucks to become widespread.

Because of the inherent uncertainty in self-driving trucking projections, it is unclear how immediate the labor problem is. According to an Obama-era White House report, two million trucking jobs out of 3.27 million are already threatened. Automation is going to happen, but when it does and the extent to which it will affect jobs is up in the air, said University of Pennsylvania professor of economic sociology, Steve Viscelli.

“There’s a dichotomy of it’s [automated trucks] either never going to happen,” Viscelli said, or automation could happen in the near term and create a trucking jobs crisis.

As of now, most truckers are still employed. But within three to ten years though, Viscelli says Google, Uber and Embark, along with other companies could surmount the difficulties that self-driving trucks are currently facing.

But Jerry Lake, who runs a trucking business with his son and wife out of small-town Montrose, Colorado, says the variables that he faces daily on the road are hard for a machine to predict and he thinks it’s a bad idea. He doesn’t see the complete switch to self-driving trucks happening as soon as Viscelli predicts or even happening at all.

“I don’t even know what the advantage is or what they are trying to accomplish other than the fact that they can do it,” Lake said. “Then you’re taking jobs away from people in America.”

For Lake’s local business, it doesn’t make any sense for him to switch to automation at all for his small fleet of two trucks.

First, retrofitting trucks for full automation is expensive. It costs about $23,400, according to the American Transportation Research Institute, and would not be cost effective for Lake’s business. Second, the specialized, localized trucking that Lake does requires extra knowledge of county and city roads, as most of the driving he does — 65 miles one way between Montrose and Grand Junction — aren’t on interstates.

Lake has trouble believing self-driving trucks can keep up with the monotony of long-haul trucking. “I have a problem with all the variables you run into — accidents and weather — that the truck can react in time and the drivers can’t always do that either,” he said.

Mapping roads in a way that is compatible with these trucks is another difficult variable to overcome. Google claims that they have mapped 99 percent of public roads in the United States, as of 2014; but that still leaves around 40 thousand miles of unmapped roads, or 8 round trips from L.A. to Miami.

Viscelli said basic sensor limitations hold back trucking as well. Most light detection and ranging (LIDAR) systems in use on these prototype trucks can only see three to four hundred feet in front of them. But driving at 55 miles per hour, it will take over 400 feet to stop a truck with an air brake system, according to the Department of Motor Vehicles. The automated system leaves no room for error and can pose a safety risk.

In an economic sense, the cost-benefit analysis doesn’t make sense yet. It will cost more to total a truck and possibly kill people on the road due to faulty automation programming or equipment than to deliver freight or a package without paying a driver.

At the same time, self-driving technology is making major strides in its development. Uber’s truck Otto transported 51,744 Budweiser cans for 120 miles between Fort Collins to Colorado Springs. The delivery had a police escort and a driver observed from inside the truck. Still, the proof of concept is rock solid.

The TraPac terminal in the Port of Los Angeles is completely automated; from the cranes to the four-legged trucks that load crates onto still human-operated tractor-trailers. And Long Beach isn’t too far behind. Amazon warehouses use robots instead of fork lifts and they are already working on using drones for deliveries.

The manufacturing sector has lost around 8 million jobs because of automation (which was started by General Motors in 1961), globalization and the Great Recession from 2008 to 2010. Trucking could also displace a large majority of America’s workforce with the allure of a more technologically-oriented supply chain.

Not having to pay for driver’s wages and benefits will translate to lower prices in the store for consumers, but at the expense of a large portion of the population being unemployed and failing to reach their productive capacity.

The trucking industry is dominated by white males with an average age of 45. Around 95 percent of people who work in the industry are male and 75 percent are white. That matches up surprisingly well with the rest of the U.S., which is 77 percent white. So if trucking were to ever be completely automated in any way at least 10 percent of America’s workforce will go away.

Race distribution in trucking.

Truckers have won a small battle in U.S. Congress to ban legislation on self-driving trucks and cars that are under 10,000 pounds, but as more pressure from tech companies mount, it’s unlikely to hold forever.

When self-driving trucks eventually become commonplace, the driver demographic will have trouble finding other work that requires higher level education. Most truckers don’t have college degrees, according to the Bureau of Labor Statistics. And middle-aged drivers will find that university education has skyrocketed at a rate faster than inflation. In a Bloomberg report, college tuition and fees have increased 1,120 percent since 1978.

Plenty of other professions are at risk too. An Oxford survey predicted that 47 percent of jobs around the world will be taken by robots in the coming decades. And it’s probably going to hit truckers first.

 

 

 

 

 

 

 

 

 

 

 

 

Many people lost their manufacturing jobs to robots, but will the same thing happen with trucks?

Trucking is the backbone of the U.S. and international supply chain, delivering and exporting nearly 13 billion tons of finished and unfinished goods from factories overseas to doorsteps across America and vice versa. The next step in trucking — taking drivers out of the equation — will yield cheaper consumer goods and safety but could cause unemployment for well over three million people.

U.S. Department of Transportation

Uber has been investing in self-driving technology since launching their Advanced Technologies Group in 2015 out of Pittsburgh. While most companies are still focused on autonomous cars, Uber has started developing autonomous trucks in their division Otto.

One of their competitors, a startup called Embark, just received series A funding for $17 million. Embark has partnered with trucking manufacturer Peterbilt, which will undoubtedly give them a leg up against other self-driving truck companies.

Google has also entered the self-driving truck sphere too with Waymo, its autonomous driving division. Google sued Uber for taking its proprietary laser systems that they used for self-driving capabilities. A former manager at Waymo illegally downloaded information that he used to found Otto.

Google’s self-driving truck

These three self-driving competitors could threaten nearly two million jobs according to an Obama era White House report, though no one can really say when that will happen and many disagree on a time frame. 

The industry is dominated by white males with an average age of 45. Around 95 percent of people who work in the industry are male and 75 percent are white. That matches up surprisingly well with the rest of the U.S., which is 77 percent white. So therefore, most people who drive trucks in the US, and who could also be displaced by automation, make up a large majority of the population. If trucking were to ever be completely automated in anyway a large portion of the workforce will go away and have trouble finding another line of work.  

Some experts including economic sociology lecturer at the University of Pennsylvania, Steve Viscelli, disagree with the dire estimates some people, like the White House, are floating.  

“There’s a dichotomy of it’s either never gonna happen is one response or it’s going to happen and we’re going to lose 3 million trucking jobs,” Viscelli said. He admits it’s hard to tell with tight-lipped Silicon Valley executives.

Still, based on the research he’s done for his book, The Big Rig, which explores how long-haul trucking has declined recently, there are many obstacles that these companies need to surmount before automation can replace jobs.

The mechanization of non-driving movement, the one thing that truck drivers have over automation, is a problem that has to be solved if big rig automation will take over the human element, Viscelli said. Port to warehouse and/or store trips will likely happen sooner as there are less tedious steps in between. In those direct routes, all the truck has to do is drive.

But for places that don’t have easily accessible loading docks or none at all and have variables that aren’t taken accounted for in the computer, trucking companies will still need humans to drive. There are other tasks that truck drivers do — opening and closing doors, inspecting the truck, performing ad hoc maintenance and driving in narrow city streets filled with pedestrians — that a robot simply can’t do and won’t be able to do any time soon on a large scale.

Viscelli estimates that real labor disruption won’t take place for at least three to ten years.

Mapping roads in a way that is compatible with these trucks is yet another problem. Google claims that they have mapped 99 percent of public roads in the United States, as of 2014. But, that’s only including public roads. There are just over four million miles of paved roads in America, according to the Bureau of Transportation Statistics. Even if that is only including public roads, they haven’t covered around 40 thousand miles of roads, or 8 round trips from L.A. to Miami. A massive investment of time is required to make sure maps provide a good enough base to automate with.

Viscelli said basic sensor limitations hold back trucking as well. Most light detection and ranging (LIDAR) systems in use on these prototype trucks can only see at three to four hundred feet. Driving at 55 miles per hour, it will take over 400 feet to stop a truck with an air brake system according to the Department of Motor Vehicles. Waymo’s truck also uses ultrasonic sensors and radar.

Integrating and processing nearly 6 million data points every few seconds from different sensors requires a lot of computational power and technical computer programming, also adding to the time it will take for these trucks to be pervasive on the road.

In an economic sense, the cost-benefit analysis doesn’t make sense yet. It will cost more to total a truck due and possibly kill people on the road due to faulty automation programming or equipment.

Jerry Lake, who runs a trucking business with his son and wife out of small-town Montrose, Colorado, says the variables that he faces daily on the road are hard for a machine to predict. He’s been driving trucks, on and off for 51 years, that’s 72 percent of his life.

“In this situation there are lives at stake with traffic around a self-driving truck,” Lake said. “I have a problem with all the variables you run into — accidents and weather — that the truck can react in time and the drivers can’t always do that either.”

One of the hardest difficulties for these trucks to overcome is visibility on the spectrum of white. Though Waymo, Embark and Otto trucks have omni-directional cameras, they have trouble determining if what’s in front of it is snow, fog or a white trailer, according to Lake, though they also use ultrasonic and radar to see object. A human would be much better at judging what visibility conditions are like.

Lake transports fuel around the Colorado foothills for Shell and used to transport jet fuel for the Montrose airport. He said it wouldn’t make sense for him to ever consider buying a self driving truck to add to his small fleet of two. Most of the driving he and his son do are off the interstate, between Montrose and Grand Junction, about 65 miles one way. Conditions on those roads harder to predict.  

Trucking jobs, though at risk like they have never been before, will still exist for a very long period of time. Regional trucking is still important; artificial intelligence would have trouble keeping up with a combined 70 years of driving experience in Lake’s company. In their promotional video, Otto still has truckers taking over once the truck gets off of the interstate, and many current drivers think that it will be human and machine working together.

But those who are employed in large trucking companies, contracted out by even larger multinational corporations, are the ones who can lose as they look to replace more people with automation to keep costs low. Keeping costs low will translate to lower prices in the store for consumers, but at the expense of a large portion of the population being unemployed and failing to reach their productive capacity.

Manufacturing jobs are an important point of comparison as they were the first sector to make use of automation. The first automation technology was installed by General Motors in their factory in 1961. Since the 1980s, the manufacturing sector has lost a lot of jobs. It went from around 19 million to its lowest point at 11 and a half million in 2010, likely in part due to the Great Recession.

Bureau of Labor Statistics

Even more, a study by the National bureau of Economic Research, showed that one robot per 1,000 people could reduce the employment to population ratio by as much as 0.34 percentage points and reduce wages by as much as 0.5 percent. The graph above still shows a resurgence in jobs, but it will likely never go back to that 20 million number.  

For trucking, it illustrates that while automation could cause job loss, humans are still needed in some capacity to fix things when they break down and monitor them for safety. Automation may even reduce the sleep-deprivation that many truckers have by allowing them to sleep more on straight stretches of road without having to stop.

There’s still many obstacles these companies need to overcome before they can put these machines on the road. That includes the people that drive trucks as they will likely get in the way of any legislation that would legalize self-driving trucks with their livelihoods on the line. So for now, truck drivers will not face drastic unemployment, and may not for a long time because the human element can react better than any robot can. They could be on the road in three years or longer than 10 — it’s almost impossible to predict.

Lake still doesn’t see any benefits from automating trucking because for him it wouldn’t accomplish much.

“I don’t think it’s a good idea period to even be developing these trucks” he said. “I don’t even know what the advantage is or what they are trying to accomplish other than the fact that they can do it. Then you’re taking jobs away from people in America.”

The future of NAFTA

The North Atlantic Free Trade Agreement is probably one of the biggest trade deals in the world, linking Canada, Mexico and the United States together. The deal has been in place since 1994, but now as it is being renegotiated its fate isn’t so clear.

NAFTA essentially encourages trade between countries by lowering tariffs on goods. Lowering tariffs makes goods cheaper because production can be easily outsourced and importing countries can easily take advantage of another country’s comparative advantage.

Unfortunately it hurts the manufacturing sector in the United States because there is cheaper labor in Mexico and U.S. companies don’t have to worry about paying an arm and a leg to get the assembled parts across the border.

For example, the U.S. Commerce Department is entertaining a tariff on imports of commercial planes of 220 percent to protect Boeing from their Canadian competitor.

Donald Trump has made it his goal to re-draft NAFTA to help support American workers and reduce the United States’ trade deficit with Mexico and Canada, both of which add up to about 52 billion dollars, less than a quarter of a percent of America’s GDP. But at the same time, there’s no argument NAFTA helps the consumer.

There are a few issues that the U.S. is trying to renegotiate, but the two biggest are rules of origin and article 19 on arbitration of trade disputes. Rules of origin basically means that country “a” can export to country “b” with limited tariffs only if country “b” is part of NAFTA.  Article 19 allows any trade grievances one country has with another country to be reviewed by a panel, and if they deem necessary, that panel can ask the relevant parties to negotiate a valid solution.

And Trump wants to add a sunset provision to the agreement, meaning that NAFTA will no longer be in effect after five years unless action is taken to renegotiate it. The problem with that idea is it creates a lot of uncertainty but it also allows the member countries (Canada, Mexico and the U.S.) to fix any potential problems that may arise with specific parts of the agreement.

Negotiators are hoping to renegotiate NAFTA before the end of the year, which may be difficult considering the diversity of each country’s economy. In the first three talks, no real progress has been made regarding article 19, the sunset clause or rules of origin.

There’s no doubt NAFTA is good for consumers, but since manufacturing is an important part of the American economy and Trump made campaign promises to protect the manufacturing industry, there’s no guarantee the renegotiation will be successful.

Sources:

https://www.forbes.com/sites/johnbrinkley/2017/10/02/trump-administration-goes-after-canadian-aircraft-maker-during-nafta-talks-why/#6f27890e27b9

http://thehill.com/opinion/finance/353444-nafta-talks-a-chance-to-refit-trade-for-the-future

http://money.cnn.com/2017/08/20/news/economy/nafta-negotiations/index.html

http://www.sice.oas.org/Trade/NAFTA/chap-191.asp

https://www.bloomberg.com/news/articles/2017-09-14/ross-says-u-s-wants-five-year-sunset-provision-for-nafta

 

For a sport that’s only been around for 10 years or less, competitive gaming is already turning into a lucrative field.

A Business Insider report released in March of this year shows that $800 million will be made on eSports in 2020. That doesn’t include media broadcasting rights, which, if included, are estimated at $1.5 billion.

This year eSports raked in about $700 million and Goldman Sachs has it growing at 22% per year.

For comparison, the National Football League made about $13 billion in the 2015-2016 season. That’s roughly 13 times more than what eSports is making now, but it’s hard to compare eSports to the NFL because it isn’t as much of an established brand.

This year, eSports has about 400 million viewers. Last year, the NFL had about 18 million views per game during the regular season, which adds up to 4.3 billion viewers.

But the NFL has seen a drop in viewers over the past couple of years, while eSports has seen a steady increase. The purpose of comparing these two sports helps add context to the numbers. Even though eSports is growing it won’t take over NFL viewership anytime soon.

You may ask yourself, how do people playing video games competitively generate millions in revenue? One, the popularity is immense. The finals for the popular game League of Legends sold out the Staples Center. Two, companies can sponsor players and teams which helps generate revenue. And finally, selling media licensing to broadcast games is very profitable, and will likely even be more profitable once media companies realize the sport’s popularity.

The majority of the people who consume eSports are young and view almost all content digitally. Getting advertisements to that demographic is no problem, but getting them to respond to it is another story.

A lot of companies are already looking at entering the space. Twitch, a platform primarily used for people to stream themselves playing video games but also used for eSports, was purchased by Amazon in 2014. ESPN has an eSports vertical on their site. YouTube has their own gaming section.

There are unique ways that eSports can be monetized so it will be interesting to see how this medium will grow in the future.

http://j469.ascjclass.org/2017/09/20/3249/

Here’s One Way to Measure How People are Doing Financially

Gross domestic product growth can provide valuable information about the health of a nation’s economy, but it rarely goes any deeper than that broad lens. Disposable personal income is one way to indicate how people are doing on a more narrow level.

Disposable personal income is a measure of how much money families have once taxes are deducted from their paycheck. Disposable personal income is usually displayed in billions of dollars.

Disposable personal income shows how much people have left over, not just what they spent. If consumption is low but disposable personal is high it could mean people are putting more money towards necessities and/or saving.

This metric can also be compared to other indicators, like food prices, to determine what percentage of a person’s disposable personal income is being spent on necessities.

The USA Today said in a recent article that people are spending almost half of what they used to on food, which may mean that they are spending more of a percentage of their disposable personal income on other necessities, like housing and healthcare.

Disposable personal income has been on a steady upward trend since 1960 and before the great recession between 2008-2009 it briefly spiked from 10.8 trillion to 11.4 trillion (numbers adjusted for inflation). During the recession disposable personal income contracted.

Disposable personal income since 1960.

Since the recession, the trend moved upward, and in 2012 reached a sudden peak of 13 trillion. More recently, in 2017 disposable personal income contracted by around 4 billion.

Disposable personal income in 2016 – 2017.

2017’s lower numbers could account for stagnant wages, higher taxes and a number of other things.

Disposable personal income is a helpful economic indicator because it can be compared easily to other indicators and shows how the average person is doing in the economy. But as it is in the aggregate it leaves economic inequality out of the picture.