Is there no cost range for annotations? Price composition elements for creating teacher data and points for selecting outsourcing destinations.

1. Positioning of Data Annotation in AI Development

1-1. Data Annotation that Affects the Quality of AI

The process of data annotation is extremely important in the development of AI. In order to improve the accuracy of AI, machine learning is used, and the training data is created through data annotation.
This is the role of data annotation in the process of AI development.

The quality of teacher data is directly linked to the accuracy of AI, so if the previous step of annotation is not done properly, it will affect all subsequent processes. Just like humans, AI can also result in incorrect judgments if it learns from incorrect materials.

1-2. Diligent Work Behind the Development of AI

Data annotation is the process of adding tags, labels, and metadata to each individual piece of data. This includes text, audio, images, videos, and any other form of data. This task requires not only accurate knowledge and judgment, but also a great deal of patience as it is done manually. The increasing capabilities of AI are built upon this meticulous process.
For more information on the meaning and types of annotation, please refer to the following article.
>>What is Data Annotation? An Explanation from its Meaning to its Relationship with AI and Machine Learning.

2. How is the outsourcing price for data annotation determined?

2-1. Reasons for Outsourcing Data Annotation Services

Data annotation requires both time and manpower. Not only the data annotators who are responsible for the work, but also the checkers who check the data and the project managers who manage the projects are necessary. It can be said that it is difficult to achieve all of these with internal resources alone. Therefore, in many companies, annotation projects are outsourced to external service providers. However, the selection of the outsourcing partner greatly affects the quality of the training data. It is important to carefully select the partner as it has a significant impact on the ultimate goal of improving AI accuracy.

2-2. Is there a cost range for data annotation outsourcing?

How is the price of data annotation determined in our outsourcing service? Generally, the price is determined by the quantity of data, desired quality level, and project management fees. The necessary quantity of data and workload can vary greatly depending on the purpose and desired accuracy of the project. The duration of work and number of resources also vary, so the price cannot be easily determined.

3. What are Project Management Fees that make up the price?

 

What is the project management fee, one of the factors determining the price? It gives a vague and opaque impression. Let's take a closer look at what project management, which is the basis of the cost, actually entails in order to determine if it is a reasonable component of the price.

3-1. Establishment of Specifications and Rules

The project manager will hear the purpose and desired quality of the project and plan from selecting the annotation tool and arranging necessary resources. This includes creating work guidelines, responding to specification changes and exceptional cases after the project has started, improving progress, and checking the quality of deliverables as part of project management.

3-2. Resource Management

One of the tasks of project management is to assign a suitable data annotator for the project, and to provide education and manage attendance, as well as respond to detailed questions related to the work.

3-3. Response according to security level and difficulty

In some cases, remote work may not be suitable due to the high confidentiality of the project or the inclusion of personal information in the data being handled. As part of project management, it may be necessary to arrange and manage an on-site work environment as needed.

 

The above is an example of typical project management, but in actual business, flexible responses are made according to the project. Project management for data annotation involves building a team tailored to each project and achieving the goal in an effective manner. Effective data annotation cannot be achieved without project management. It can be seen as a crucial element that cannot be underestimated.

4. Points to Consider When Selecting a Data Annotation Outsourcing Partner

4-1. Important factors in selecting an outsourcing partner

When selecting an outsourcing partner, what should be prioritized? It is more important to ensure that the outsourcing partner has a proper system in place for managing data annotation projects, rather than just focusing on the appearance of the price. With such a company, it can be expected that there will be a project manager who understands the purpose of the project and can make effective and efficient proposals. As a result, excellent cost performance can be expected.

4-2. Necessary Structure for Project Management of Data Annotation

Data annotators are required to have both a high level of productivity and speed, as well as a considerable level of attention to detail, patience, and a deep understanding of the rules and tagging process. Therefore, a management system that can identify and train suitable personnel, as well as provide thorough education, is necessary. It is also important to provide security education to workers and implement sufficient security measures on the management side.

4-3. Issues with Crowdsourcing Data Annotation

When considering cost reduction, using a cloud sourcing agency may be an option. However, while using cloud sourcing may seem cost-effective at first glance, in reality, the quality may not be stable and additional modifications and verification work may result in unexpected cost overruns. There is also concern about data dispersion in terms of security. When considering the potential loss in the event of redoing work or a security incident, it is important to pay attention to the balance between quality and price when selecting an outsourcing partner.

5. Data Annotation Outsourcing Service by Human Science Co., Ltd.

5-1. Rich track record of creating 48 million pieces of teacher data

At Human Science, we are involved in AI development projects in various industries such as natural language processing, medical support, automotive, IT, manufacturing, and construction. Through direct transactions with many companies including GAFAM, we have provided over 48 million high-quality training data. We handle various annotation projects regardless of industry, from small-scale projects to large-scale projects with 150 annotators. If your company is interested in introducing AI but unsure where to start, please consult with us.

5-2. Resource Management without Using Crowdsourcing

At Human Science, we do not use crowdsourcing and instead directly contract with workers to manage projects. We carefully assess each member's practical experience and evaluations from previous projects to form a team that can perform to the best of their abilities.

5-3. Utilizing the Latest Data Annotation Tools

One of the annotation tools introduced by Human Science, AnnoFab, allows customers to check progress and provide feedback on the cloud even during project execution. By not allowing work data to be saved on local machines, we also consider security.

5-4. Equipped with a security room within the company

At Human Science, we have a security room that meets the ISMS standards in our Shinjuku office. We can handle highly confidential projects on-site. We consider ensuring confidentiality to be extremely important for all projects. We continuously provide security education to our staff and pay close attention to handling information and data, even for remote projects.