As artificial intelligence and robotics systems advance, people worry that more and more jobs will become automated.

When people talk about artificial intelligence and the job market, they often talk about how AI will take jobs from human workers.

Is this a legitimate worry?

Of course it is.

However, at the same time there are ways that AI is creating jobs on a large scale.

AI is doing more than creating thousands of remote jobs around the world. Numerous AI companies are even finding ways to employ people in lesser-developed countries to create a positive social impact, while turning a profit at the same time.

I know what you’re thinking. How can something that people thought would harm the job market, actually be creating jobs?

How Does AI Create Jobs?

There are two sides to every coin. In this case, the other side of the coin is a crucial stage in the AI development process: data creation and data annotation.

Whether it be the ability to identify cars in an image or understand human speech, AI technologies are built to replicate or even surpass the things humans can do.

In order to do this, the AI has to learn from humans, that is, from human-annotated data.

This data is often referred to as AI training data, or ground truth data. This data serves as the building blocks for the AI algorithm to learn from, in order to perform well.

For a chatbot, this data could be in the form of customer service email histories.

With speech recognition technology, like Amazon Alexa, this training data might be recordings of natural conversations.

For autonomous vehicles, some of the ground truth data would be in the form of traffic images with cars, traffic lights, and pedestrians.

However, autonomous vehicles require more than just raw traffic images. They also require the cars, bikes, and pedestrians in those images to be accurately labeled like in the image below.

The task of labelling images, text, audio, and other forms of data, is done by human workers. Humans look at each piece of data and label it according to the project’s needs.

Hundreds of thousands, if not millions, of jobs in AI come from a growing demand of annotated data.

However, when we talk about annotating data, we don’t mean a couple hundred images or words.

In fact, many AI algorithms require millions of pieces of data in order to perform and generalize well. That means millions of cars need to be labeled or millions of audio clips need to be transcribed.

As a result, many annotation projects require thousands of contributors.

Where Can You Find Data Annotation Jobs?

If they wanted to, data scientists could sit at a computer all day and label the data they need on their own.

However, when you take into account the simplicity of the tasks, i.e. drawing a box around a car, it becomes inefficient for a data scientist to spend their time on annotation.

Data scientists want to spend their time researching, developing, and testing.

Therefore, many tech companies outsource their annotation tasks, rather than assign the work in house.

Thus, an entire market around AI training data was born. Today, there are a multitude of data annotation companies that offer a variety of services and annotation tools.

The best part about data annotation jobs is that most tasks can be done completely remotely. All you need is a decent laptop and internet connection.

The remote nature of the work allows employers to hire annotators all over the world.

If you’re looking to find entry level online jobs in data annotation, here are a few places to start:

Data Annotation Companies

The data annotation market is just one of the many ways that AI is creating remote jobs around the world. As the industry continues to grow and new technologies continue to emerge, we may see the birth of even more new markets. Hopefully, these new markets will also provide new job opportunities.

Is it true that AI poses some risks to the human job market? Yes, and it is our job to create rules to control it.

Is AI creating new jobs? Definitely, and we will likely see even more AI jobs emerge in the near future.