When outsourcing annotation, which is crucial for building AI, you need to choose between a domestic company (onshore) or an overseas company (offshore).
Annotation is the process of tagging data such as text, audio, and images to make it ready for AI learning. By tagging data through annotation, the data is put into a state where AI can learn from it.
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In annotation work, the accuracy of the tags assigned to the data is of course important, but there are other elements vital for proceeding efficiently, such as communication with the outsourcing company. In this article, we introduce the advantages and disadvantages of onshore and offshore, and explain which type of company is better to outsource to from an annotation perspective.
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When outsourcing annotation work, you need to choose between onshore and offshore.
The accuracy of annotation is deeply related to the precision of the resulting AI. In many cases, annotation is performed manually, so depending on the data volume, it will require many personnel and man-hours.
By performing annotation through outsourcing, you can obtain high-quality data while reducing personnel and man-hours.
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First, we will explain onshore and offshore.
Onshore refers to cases where the outsourcing or sub-contracting partner is in the same country or region.
Because the culture and time zone are the same, communication is easy, and in times of emergency, many tasks can be handled due to the ease of access. Furthermore, because the industry is the same, they may provide proposals tailored to your specific needs. However, costs are often higher compared to offshore companies.
Offshore refers to cases where the outsourcing or sub-contracting partner is located overseas.
In offshore, it becomes possible to suppress costs by ordering from countries where labor and material costs are inexpensive. You can request work from a wide variety of human resources overseas, which may also lead to the cultivation of overseas markets. When making a request, you need to be careful of differences in cultural systems and time zones, and there is a tendency for it to be difficult to control fine details of the work.
| Advantages | Disadvantages |
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We will explain the respective advantages and disadvantages.
Points to emphasize when performing annotation include clarifying annotation standards and creating an environment where communication is possible.
When requesting an onshore company, you can clearly define the standards that are important for annotation.
For example, if you want to develop an AI that detects the position of humans in an image, you will need the vertices of a rectangle showing the position of the human in the image as training data. By deciding whether the rectangle position should be from the top of the head to the tip of the toes or just the upper body according to the objective, high-quality data can be generated.
If the annotation standards are not clear, training data that deviates from the target AI will be generated, resulting in low-quality data.
| Related Article: The importance of establishing annotation rules: Introduction to examples and key points |
Points to emphasize when performing annotation include <strong>creating an environment where communication is possible</strong>. Depending on the company, you can consult about the target AI and have them determine the annotation standards, making it possible to request work even if you do not have specialized knowledge of AI.
Also, when data that is difficult to judge appears, it is possible to communicate quickly and discuss the response.
Even if clear standards have been established, data may emerge during the annotation process for which the worker cannot determine how to apply tags. In the case of AI for human detection, examples include cases where people overlap and standards cannot be seen.
Regarding things that cannot be judged, if a worker proceeds with annotation arbitrarily, the data quality may drop, so it is important to provide an environment where consultation can occur immediately.
Because the request is to a domestic company, the initial costs tend to be high. On the other hand, rework due to lack of communication with workers is unlikely, so it is rare for additional costs to occur.
Related Article: What are the costs and market prices of annotation? Ways to keep costs down and what to look for when outsourcing!
| Advantages | Disadvantages |
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We will explain the respective advantages and disadvantages.
Initial costs can be lower than when requesting a domestic company. Offshore also has the secondary benefit of overseas market development.
Selecting important standards for annotation and addressing problems becomes difficult when requesting an offshore company due to the language barrier. Since defining standards in detail affects data quality, these disadvantages significantly impact the accuracy of the AI.
If standards are not communicated well, problems such as rework may occur, potentially costing more than the initial setup, so please be careful when requesting.
| Onshore | Offshore | |
| Initial Costs | × | ◯ |
| Communication | ◯ | × |
| Dealing with issues | ◯ | × |
| Rework | ◯ | × |
Onshore annotation has higher initial costs, but communication is easier compared to offshore. Determination and changes to annotation standards can be done smoothly, lowering the probability of rework.
Offshore annotation makes it difficult to create an environment for communication, so determining standards and dealing with problems is difficult, and the probability of rework is higher compared to onshore. If rework occurs, caution is needed as costs may become higher than onshore.
We introduced offshore and onshore annotation.
The respective advantages and disadvantages are as follows.
| Advantages ・Annotation standards can be clearly determined, and consultation is possible ・Quick response is possible when issues arise Disadvantages ・Initial costs are high |
| Advantages ・Initial costs are low Disadvantages ・Difficulty in defining clear annotation standards or consulting due to language differences ・It takes time to deal with issues when they arise |
Basically, we recommend onshore annotation, which allows you to obtain high-quality data while minimizing communication costs. If you absolutely want to keep initial costs down, you may use offshore annotation, but be careful about creating an environment for communication.