For any business that’s implementing a machine learning (ML) solution to use on data for analysis and business intelligence purposes, no part of the process is more labor-intensive than data labeling. Without it, ML algorithms can’t complete their supervised training, which is a prerequisite to establishing reliable learning patterns. Put simply, data labeling is the foundation upon which deep learning systems are built.
Due to the mission-critical nature of the work, though, it’s common for businesses to outsource the task. They do it to lower overhead, and to ensure that the work is done right at every stage of the process. But outsourcing data labeling comes with some risk attached. For that reason, businesses considering such a move know what they’re getting into before they commit to a data labeling outsourcing plan. Here are the risks involved and how to minimize them where possible.
Adverse Reputational Effects
Since the need for data labeling has been on the rise for some time, it has turned into a blue-collar job. The tools and techniques used to do it have become standardized and easier to use, which has lowered the knowledge requirements of the workers tasked with handling it.
As a result, these tasks are often given to people in developing economies where there is less regulation. It’s a way of keeping overhead low by containing labor costs. This is a good thing for businesses trying to get the job done quickly and affordably, but it is an arrangement that can backfire, too.
Companies that pursue outsourcing agreements using low-paid workers in developing countries run the risk of creating a public relations and branding disaster when their plans go public. As with many other types of outsourcing, there’s a considerable backlash from displaced local workers as well as those who consider the practice a form of exploitation of foreign workers. The possible reputation damage alone might be enough reason to avoid outsourcing data labeling tasks.
Difficulty Selecting Reputable Partners
Not all outsourcing is bad, especially if you take care to work with reputable outsourcing firms. For example, you can make sure you outsource your work with a company that pays employees a living wage. You can also make sure the culture within the company is positive and supportive of all workers.
Sure, this might mean you’ll have to pay a little more for their services, but the reality is the costs are still a fraction of what any in-house option would be. But it’s not always easy to tell when an outsourcing partner will live up to the standards you expect. This is especially true when the firm you’ve partnered with is in another part of the world where it’s impossible to monitor their day-to-day operations.
The only option in such cases is careful research. Reviews about the company you’re considering working with are often the best resources to rely on. If you are thorough, you should be able to find a company that cares about its workforce and that will carry out the work in a reputable manner.
Communication Difficulties
Working with a company elsewhere in the world means you may not be able to communicate easily with the team handling your work. And given that data labeling is a critical task and part of a larger, more complex process, poor communications can have all kinds of adverse effects.
The only way to mitigate this risk is to thoroughly vet your outsourcing partner to make sure that they’re using workers fluent in the native language spoken by whoever in your organization will be overseeing the work. The likelihood of finding a company with top-to-bottom fluency in your native tongue is slim, but that doesn’t mean you won’t find a company with at least a few people who know your language well enough to form a critical communications bridge with the rest of the staff.
For extra peace of mind and to make sure that there won’t be any surprises, you can ask that all offshore employees take a comprehension test before you commit to using them. It’s the most direct way you’ll be able to verify that their communication skills are good enough to work on your project.
Unintentionally Exposing Sensitive Data
Businesses, big or small, are under attack by cyber criminals on a near-constant basis. These attacks have cost companies incredible amounts of money whenever they succeed in penetrating their defenses. Data breaches not only put customers in danger of their identities being stolen, but also make it hard for companies to regain people’s trust once they’ve suffered a breach. This is the reason companies now devote so many resources to cyber security.
When outsourcing data labeling, though, your company’s data will only remain as secure as your outsourcing partner keeps it. The partner you plan to work with may not take the precautions your company has taken to secure their networks. You could be trusting your company’s data to a third party that is vulnerable to malware or virus attacks.
Depending on the sensitivity of the data you’re handing over, you might need to request a thorough cyber security review of all your partner’s digital systems. You also need to worry about the employees. If you are sharing sensitive and valuable data, you need to make sure the employees from this third party won’t try to steal data from you.
There are several steps you can take to ensure your data is safe from the employees, like insisting that every worker submits to a background check. You can also ask employees to sign a non-disclosure agreement that’ll provide some legal recourse and a deterrent against a rogue employee. An additional step could be ensuring the third-party company disables employees’ ability to download data.
The Bottom Line
Outsourcing data labeling is definitely something businesses should consider. Those that don’t forego what could be a significant operating advantage over their competitors. The important thing to remember is the choice can’t be made blindly; you have to recognize the disadvantages so that you can properly address them before they become a problem for you down the road.
The good news is that there are plenty of ways, like those discussed here, to limit the risks associated with the outsourcing of data labeling. By taking the time to craft and execute a thorough outsourcing plan, a business can enjoy all of the benefits of outsourcing data labeling without worry that the decision will come back to haunt them later.