In 2016 consumers spent around $30 billion on video games. Historically, video game consumers spent that money on a single game that unlocked all of its features. However, more recently, video game developers are distributing free-to-play games on the App Store, the internet, Steam, etc. in exchange for introducing microtransactions.

Microtransactions are transactions within a game that allow players to unlock virtual items that help them progress in a game or make their character look better with weapon skins.

With the advent of the App Store, small game developers saw this as an opportunity to sell their games for free but work in transactions so that players could add to the game. Clash of Clans, despite being a free game on the App Store, made $2.3 billion dollars last year. Microtransactions go beyond the App Store, too. League of Legends, a free game made by Riot Games, made $1.6 billion in 2015 off of Microtransactions.

Microtransactions are leeching into full-price video games as well. The new game, Star Wars Battlefront II, was released with a lot of controversy. The $60 dollar game (the deluxe edition costs $80) was going to be released with a microtransaction system. To get loot crates, which can unlock heroes like Darth Vader and Luke Skywalker, and help a player progress through a game, people would have to pay up. Electronic Arts removed that system before the game came out, after public outcry by gamers and a post which earned EA the highest number of downvotes ever on Reddit.

For big box games like Battlefront, the idea is to create a continual revenue stream for a game even if its initial price depreciates. Within a year some games can lose more than half of their value as new games come out and replace the old ones, similar to cars, though at a much faster rate.

Microtransactions employ behavioral economics. There are a whole slew of tactics, but there are two main ideas that trick people. First, they have weird conversion rates from dollars to an in-game currency, so it is hard for players to know how much money they have spent. Second, developers treat microtransactions like gambling. Players can put in money to get that in-game currency in the hopes that when they unlock a loot box they will get a great prize.

Microtransactions are likely going to be around for a while, and as artificial intelligence takes off, they will probably become more specified to a person’s play style, the friends they have online and a whole host of other variables. Gamers have at least staved off microtransactions in Battlefront, for now.

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.

https://www.youtube.com/watch?v=nfwOVvjK-sc&feature=youtu.be

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.”

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/

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.