The New Age of Automation#

So, how long do you reckon it’ll take before machines can do your job better than you?

You know, automation used to be about those big, clunky machines doing the same simple things over and over in factories. But today? They’re landing planes, helping doctors figure out cancer, and trading stocks! We’re stepping into a whole new era of automation, totally different from anything we’ve seen before.

A study back in 2013 suggested that nearly half of all jobs in the US could possibly be automated in the next twenty years. Pretty wild, huh?

Automation: Then vs. Now#

Hold on, though. Automation’s been around for ages, right? So, what’s the big deal this time?

Things used to be simple. Innovation came along, made human work easier, and boosted productivity. That means you could make more stuff or provide more services per hour with the same number of workers. Yeah, this did get rid of many jobs, but it also created other jobs, and usually better ones. This was super important because the population kept growing and people needed work.

So, to put it simply:

• Innovation happened.
• Productivity went up.
• Fewer old jobs were needed.
• Lots of new (and often better) jobs popped up.

Overall, this worked out pretty well for most folks, and living standards improved.

There’s been a clear path in how people made a living throughout history:

1. For the longest time, we worked in agriculture.
2. With the Industrial Revolution, we shifted to production jobs.
3. As automation became more common, humans moved into service jobs.
4. Then, just a blink ago in history, the Information Age arrived.

Suddenly, the rules changed.

The Information Age Shift: Fewer New Jobs#

Now, machines are taking over our jobs way faster than they did before. Yeah, that’s worrying, for sure. But hey, innovation will save us, right? That’s what always happened!

Here’s the thing: Even though new industries in the Information Age are booming, they’re creating fewer and fewer new jobs.

Let’s look at some examples:

• General Motors (1979): Employed over 800,000 workers and made about $11 billion USD.
• Google (2012): Made about $14 billion USD while employing just 58,000 people.

You might not love comparing a car company and a tech company, but think of Google as an example of the kind of innovative new industry that created tons of jobs in the past.

Traditional innovative industries, like cars, are kind of running out of steam job-wise.

• When cars first became a thing 100 years ago, they sparked massive industries.
• They completely changed how we lived, our roads, and our cities.
• Millions of people got jobs, directly or indirectly.
• Decades of investment kept that going.

Today, that whole process is mostly done. Innovation in the car industry just doesn’t create as many jobs as it used to. Electric cars are cool and all, but they won’t magically create millions of new jobs by themselves.

Okay, but what about the internet? Some tech folks say the internet is as big a deal as electricity was. If we go with that comparison, we can see how today’s innovation is different.

• The internet did create new industries.
• But they aren’t creating enough jobs to keep up with more people being born or to make up for the jobs the internet is wiping out.

More examples:

• Blockbuster (Peak 2004): Had 84,000 employees and $6 billion USD in revenue.
• Netflix (2016): Had 4,500 employees and $9 billion USD in revenue. (Yep, more money with way fewer people!)

Or even look at us (Kurzgesagt). With a full-time team of just 12 people, we reach millions. A TV station with the same huge audience would need way, way more staff.

So, in the Information Age, innovation doesn’t equal enough new job creation. That’s bad enough on its own, but now, a new wave of automation and fancy new machines are slowly taking over.

Why Automation is Different This Time#

To get a handle on this, we first need to understand a bit about ourselves. Human progress is built on division of labor. As we’ve gotten smarter over thousands of years, our jobs have become more and more specific, more specialized.

Even the smartest machines we have are still pretty bad at doing really complicated jobs overall. BUT, they are amazing, extremely good, at doing tasks that are narrowly defined and predictable. This is what hammered those factory jobs.

But think about a complex job for a long time, really look at it, and you’ll often find it’s actually just a bunch of those narrowly defined, predictable tasks strung together. Machines are getting scary good at breaking down those complex jobs into lots of simple, predictable steps. For many people, this means there might not be any room left to specialize away from what a machine can do. We’re getting close to being outcompeted.

How do digital machines do this? Through something called machine learning. This lets them learn stuff and gain skills by looking at loads of data. They get better at something by finding patterns and relationships in that data. Basically, machines teach themselves.

We make this possible by feeding a computer a massive amount of data about whatever we want it to get good at. Show a machine everything you’ve ever bought online, and it’ll slowly figure out what to suggest so you buy even more stuff.

Machine learning is hitting its stride now because, in recent years, humans have started collecting data on everything:

• How people behave
• Weather patterns
• Medical records
• Communication systems
• Travel info
• And yes, data about what we do at work!

What we’ve accidentally created is a giant library that machines can use to learn exactly how humans do things and then learn to do them better.

These digital machines might be the biggest job killers yet.

• They can be copied instantly and for free.
• When they get better, you don’t need to build a new factory; you just update the software (use the new code).
• And they can improve really fast.

How fast? If your job today involves complicated work on a computer, you might be out of a job sooner than the folks still working in factories.

Real-World Example: Project Management Software#

There are already real examples showing how this transition is starting to happen.

Imagine a company in San Francisco. They offer software for big corporations to manage projects. The idea is this software can get rid of middle management positions.

Here’s how it works when a new project comes along:

1. The software first figures out which parts of the project can be automated.
2. It identifies precisely where actual professional humans are still needed.
3. It then helps build a team of freelancers over the internet.
4. The software hands out tasks to the human freelancers.
5. It checks the quality of their work.
6. It tracks how each freelancer is performing until the project is done.

Okay, that doesn’t sound totally bad, right? While the machine gets rid of one job (middle management), it creates jobs for freelancers, doesn’t it?

Well, here’s the catch. As the freelancers do their tasks, learning algorithms watch them. They collect data about their work and what specific tasks make up that work. So, what’s really happening is the freelancers are teaching a machine how to replace them eventually.

What are the results? On average, this software cuts costs by about 50% in the first year, and by another 25% in the second year.

This is just one story out of many. Machines and computer programs are getting as good as, or better than, humans in all sorts of jobs:

• From pharmacists to analysts
• Journalists to radiologists (doctors who look at X-rays/scans)
• Cashiers to bank tellers
• Even the person flipping burgers.

These jobs won’t vanish tomorrow, but fewer and fewer humans will be doing them. We’ll dive into a few more examples in a future video (like Part 2).

The Broader Impact: Job Decline and Productivity#

But while jobs disappearing is bad, that’s only half the picture. It’s not enough just to swap old jobs for new ones. We need to be creating new jobs constantly because the world population keeps growing.

In the past, we fixed this problem through innovation. But, since 1973, the rate of new job creation in the US has started to shrink. And the first decade of the 21st century was the very first time the total number of jobs in the US didn’t grow at all. In a country that needs to create up to 150,000 new jobs every month just to keep up with population growth, that’s really bad news.

This is also starting to mess with how well people live. It used to seem obvious that as productivity went up, more and better jobs would be created. But the numbers tell a different story.

Let’s look at the US again:

• 1998: US workers worked a total of 194 billion hours.
• Over the next 15 years (by 2013), their output (productivity) increased by 42 percent.
• 2013: The total number of hours worked by US workers was still 194 billion hours.

Think about that. Productivity shot up dramatically. Thousands of new businesses opened. The US population grew by over 40 million people. Yet, there was absolutely no growth in the total number of hours worked over 15 years!

At the same time:

• Wages for new university graduates in the US have been going down for the past decade.
• Up to 40 percent of new graduates are forced to take jobs that don’t even require a degree.

Productivity is basically separating from human labor. The way innovation works in the Information Age is just different from anything we’ve dealt with before. This process started years ago and is already happening. Even without big new things like self-driving cars or robot accountants changing everything overnight.

It really looks like automation is different this time. This time, the machines might actually take our jobs.

Facing the Future: Challenges and Possibilities#

Our economies rely on people buying stuff and using services (consuming). But if fewer and fewer people have decent jobs, who’s going to be doing all that buying? Are we just making things cheaper and cheaper only to reach a point where too few people can afford to buy anything we make?

Or, will the future be one where a tiny group of super-rich people who own all the machines end up controlling everyone else?

Does our future have to look so gloomy?

While this video has been pretty dark, it’s definitely not set in stone that things will turn out badly. The Information Age and modern automation could actually be a massive chance to change human society for the better and cut down on poverty and inequality a lot. It could be a huge, landmark moment in human history!

Looking Ahead: Potential Solutions#

We’ll talk about this positive potential, and possible solutions like a universal basic income, in the next video in this series (Part 2).

We need to start thinking big, and think fast. Because one thing is certain: the machines aren’t just coming; they are already here.