As artificial intelligence (AI) and machine learning (ML) become more widespread, there’s a growing need for labeled data sets. These sets help train the AI to understand specific types of inputs and produce desired results. This is leading to a surge in jobs related to data labeling, opening up new business opportunities.
Reports suggest that by 2030, automation will change the job landscape significantly. Around 5% of all jobs might disappear, and a third of existing jobs could be automated. However, it’s not all doom and gloom. AI and machine learning are also creating new jobs. Data scientists, AI engineers, and especially data labelers are likely to be in high demand in the AI-driven future.
In today’s guide, I wanted to explore what data labeling is and how it functions. I will also include ways you can find legitimate AI data labeling jobs.
What is Data Labeling?
Data labeling means taking raw data, like photos, text, or videos, and tagging it with labels to give it context. This helps a machine learning model learn and improve. For instance, labels can help identify whether a picture contains a bird or a car, what words were spoken in an audio clip, or if an x-ray shows a tumor. Data labeling plays a key role in various tech fields, such as image recognition, language understanding, and speech recognition.
And, in my experience, it’s easier than you think.
You could be marking objects in images, categorizing texts like product descriptions, or even transcribing audio files. This work is simple, and anyone with a computer and internet can do it without breaking a sweat. You might wonder why someone would pay you for these easy tasks. Here’s the deal: these tasks help train artificial intelligence (AI) systems. Companies want to improve their AI tools, products, or services, so they need quality data to teach their AIs how to function better.
How Does Data Labeling Work?
To train machine learning or deep learning systems, you usually need a large amount of data. This data has to be labeled correctly to help the AI sort the inputs and produce the right outcomes. The process involves three main steps:
- Data Collection: Start by gathering a ton of data like pictures, videos, and text. The more diverse and abundant your data is, the better the AI will perform.
- Data Tagging: Humans use special software to label or tag the data. They might be asked to say if a picture has a person in it, or to track a moving object in a video.
- Quality Assurance: The labels have to be accurate for the AI to work well. That’s why it’s important to double-check the labeled data to make sure it’s good quality.
What Do Data Labelers Do?
The job of a data labeler is pretty straightforward but goes by many names like data annotator or machine learning labeler. Don’t mix this up with roles like data scientists or AI engineers, as those jobs require a deeper understanding of how to build and use machine learning algorithms.
Data labelers help computer algorithms recognize specific images by drawing boxes around certain parts of those images and giving them descriptive tags. The type of work a data labeler does depends on the goal of the AI or machine learning model they’re supporting. For image recognition, for example, it’s crucial to be detail-oriented. When drawing a box around a specific part of an image, whether it’s a tree, a bike, or a cat, you have to be super precise.
To be good at data labeling, you’ll need a few key skills:
- Attention to Detail: Small mistakes may not seem like a big deal, but they can mess up the training of the model if they pile up.
- Long-term Focus: You need to be the type of person who can concentrate for long periods without getting distracted. This helps to avoid errors and maintain the quality of your work.
- Tech-Savvy: You’ll be working a lot with computers, not people. This could be hard for some but ideal for others. On the bright side, many data labeling jobs allow for remote work and flexible hours, making it a good fit for freelancers or those looking to shift careers.
How Much Do Data Labelers Make?
The pay for data labeling can vary a lot based on the project, the company, and your own background. However, it looks like the average hourly rate is somewhere between $3 to $10+, according to my research. It’s not much, but it needs to be treated more like a survey company where you can log in and complete jobs at your leisure. You definitely won’t get rich, but you can make a few dollars here and there.
Each platform has its own set of tasks. Some are simpler and some are a bit more challenging, but the harder the task, the more you can earn. In some cases, top performers are making between $100 and $250 a month. I wouldn’t expect much more than this.
My advice is that you don’t put all your eggs in one basket. Sign up for multiple platforms to maximize your opportunities and earnings.
Where Can You Find Data Labeling Jobs?
If you’re interested in data labeling, there are plenty of ways to find legit jobs, especially freelance gigs. Many online platforms specialize in connecting data labelers with companies that need their skills. Some of my favorites include the following:
If you’re interested in getting started with data labeling, Amazon Mechanical Turk is a good platform to consider. Known as MTurk, this service connects people like you to companies that need help with data tasks. You’re not just limited to data labeling; there’s a whole range of tasks, called HITL jobs, you can pick from. The best part? You get to choose what kind of work suits your skills and interests. It’s a flexible gig that lets you decide your workload. Check out my guide as to how you can make up to $50 per day using the platform.
Another platform to keep an eye on is Appen, which focuses more on artificial intelligence and machine learning projects. This isn’t your typical odd-job platform; Appen often offers longer projects that involve things like audio transcription or classifying text and images. If you’re after something more stable, Appen is a solid choice because it often provides long-term work opportunities.
For those who are new to data labeling and want a user-friendly experience, Clickworker has you covered. This platform also offers a variety of small jobs, including writing and polling tasks. The cool thing about Clickworker is that you’re in control. You can complete tasks whenever it’s convenient for you, making it a really flexible way to earn some extra cash.
Remotasks is a platform that offers a variety of small tasks, including data labeling. It’s a solid choice for those who are new to this type of work, as the platform offers training and the chance to build up experience. It may not have as many tasks as the bigger players, but it’s a good starting point for anyone interested in data-related gigs.
Microworkers is another platform that provides an array of microtasks, not just data labeling. You’ll find a variety of jobs, from simple tasks like surveys to more complicated ones like content creation. It’s a versatile platform that’s well-suited for people looking to pick up extra work in their spare time.
TELUS International is a bit different than the other platforms. Known for its strict quality standards, this international company provides data labeling services along with other AI and machine learning work. If you’re interested in taking on more challenging tasks and improving your skills, TELUS International offers good pay and even training opportunities..
Teemwork is a platform specializing in tech-focused tasks. It often works with big-name companies, offering projects that require a variety of skills, from language translation to software testing. If you’re looking to gain experience in tech-related fields while working remotely, Teemwork might be a good fit for you.
Toloka is a crowdsourcing platform that offers tasks which help train AI models, including data labeling. It’s known for its user-friendly interface and international accessibility, making it a convenient choice for people all over the world. Whether you’re a beginner or have some experience, Toloka offers a flexible way to earn money and contribute to AI projects.
UHRS stands for “Universal Human Relevance System,” and it’s a platform where you can find a variety of data labeling and other microtasks. Often integrated with other freelancing websites, UHRS offers tasks that include things like data categorization, search engine evaluation, and more. The platform has a reputation for offering decent pay rates for the work involved, and it’s a good option if you’re looking to tackle a mix of tasks beyond just data labeling. With its straightforward interface, UHRS makes it easy for you to find projects that match your skills and interests.
To wrap up, you won’t get rich doing data labeling, but it’s a decent way to make some extra cash. It’s flexible, easy, and you’re helping to train the AIs of the future.
If you’re interested in any of the jobs mentioned above, check out the links above to the companies I found. I reviewed most of them, but there are still a few I need to look into.
That’s going to do it for now.
As always, if you want to comment on your experiences or add to the list, you’re more than welcome to do so in the comments below.
Want $5 free?
Try out Swagbucks, the most popular reward program I make the most money with. Simply answer survey questions and get paid!
Join Now to Get $5!