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The changing role of AI human resources in DX | SIGNATE aiming to develop human resources to accelerate DX in Japan!

Attention to DX is increasing, and the use of data and digital technology is accelerating. On the other hand, there are still not many human resources who can handle DX, and urgent and large-scale human resource development is required.

Under these circumstances, how are the demands and required roles for the attention- grabbing “AI human resources” changing?

This time, we interviewed Shu Saito, CEO of SIGNATE Co. , Ltd. , which operates a data science competition platform and trains excellent data scientists, about the role that AI human resources should play in the DX era and SIGNATE’s efforts. Did.

Table of contents

  • AI human resources in an environment where DX is promoted
  • SIGNATE to develop AI human resources who will support the next generation
    • What barriers do you face in your first career as an AI human resource?
    • Increase in the number of students learning AI and the proliferation of AI training institutions
  • Future prospects of SIGNATE
  • lastly

AI human resources in an environment where DX is promoted

ーーWhat role do you think AI human resources should play in DX initiatives?

Saito: The role AI human resources should play is “implementation” . The SIGNATE Quest we are working on at SIGNATE also incorporates a program that will help you acquire implementation skills .

With DX aiming not only to improve operational efficiency but also to transform the business model, the reality is that there are not many people in the company who can take the lead when asked who will take the initiative. This shortage of human resources is said to be insufficient in the hundreds of thousands when viewed over the long term.

Also, among the AI ​​human resources who can implement it, not only the technical part, but also human resources who can be used in business will be needed . It is necessary to create value while communicating well with stakeholders on the business side, so AI human resources and data scientists need not only technology, but also basic skills and application skills for society in general. .

According to a survey by the Ministry of Economy, Trade and Industry, if the demand for IT human resources continues to increase at the current rate, it is predicted that there will be a shortage of approximately 790,000 IT human resources by 2030 . In order to promote in-house DX, we need human resources who are not only knowledgeable about the company’s business model, but also knowledgeable about IT and AI .

ーDo you mean that the requirements for AI human resources have changed to include not only data science skills but also communication and internal coordination?

Saito: Statistics and machine learning techniques are technical skills that are still needed today. Trends in the field of machine learning (deep learning, etc.) change easily, so it is necessary to catch up with information, but when looking at technology from a macro perspective, we do not see that much of a change.

In terms of business-side skills, AI human resources are not limited to the phase of building AI ; It is important to extend the

There is a trend toward more and more use of digital technology and data in business, so I think there will be more situations where business-side skills are required.

ーーIt means that AI human resources need to reach out beyond their specialized areas in DX initiatives.

Mr. Saito: Yes. I don’t think Japan is lagging behind other countries when it comes to technology. Recently, the number of papers has been increasing, and I don’t think there is any difference in the level of actual coding and development.

What I am concerned about is that the business side has not developed a foundation for utilizing the capabilities of AI human resources . I think it’s also connected to the story of DX, but since we don’t have a business model that utilizes data, we will continue to fall behind China and North America in terms of AI utilization.

There are still relatively many opportunities to utilize AI in the IT (Web) field, but in large companies and research and development organizations in other industries, there are many AI human resources who do not make full use of their specialized skills. It can be said that there is a shortage of

In order to change this situation, it is not enough to just wait for top management to work on DX and create opportunities for AI human resources to play an active role. We believe that a bottom-up approach to developing and implementing solutions for small on-site issues and accumulating a track record is the shortcut to DX success.

Of course, I don’t deny top-down, but I recommend a bottom-up approach because even if the president calls out to work on it, the environment won’t change immediately

SIGNATE to develop AI human resources who will support the next generation

What barriers do you face in your first career as an AI human resource?

ーーAre there any changes in the attributes of the SIGNATE participants?

Saito: “SIGNATE” evaluates not only the results of competitions within the service, but also other activities such as Kaggle. Thanks to you, we have collected a lot of data.

Looking at the distribution of participants, there are many Kaggle grandmaster level players among the top rankers of SIGNATE, and of course there are many beginners. The number of people who are interested in AI and those who want to challenge tasks that are close to practical work are increasing.

Junior-level AI personnel have knowledge of AI and data science, but have the problem of not having actually worked on it . This problem is a ” chicken and egg” problem . On walking, it becomes a big wall.

ーIt’s hard for juniors to get their first job.

Mr. Saito: It is very disappointing that even in the area of ​​engineering schools, there are cases where even if someone says, “I have studied seriously,” they cannot be hired because they do not have practical experience.

Therefore, SIGNATE is a service that links to practical skills as much as possible . With SIGNATE Quest, you can also work on actual corporate issues, so I think we can produce educational results that will be recognized as ready-to-work.

I would like to make it a service that people who are interested in AI and DX and want to have an impact on society in this field can work with SIGNATE Quest and be evaluated by companies and lead to their next job .

ーーHas there been any change in the client’s reaction?

Mr. Saito: We are very grateful for the high evaluation we receive from our clients. I work with SIGNATE clients with the stance of solving problems together .

In large companies, it is often difficult to take on new challenges out of intellectual curiosity because of the limitations of existing businesses. With SIGNATE’s service, you can take on exciting challenges using open innovation, so I think that point is also appreciated.

Also, due to the nature of SIGNATE’s competition, there are many opportunities for companies to be exposed, such as influencing many people and encouraging participation, so there is also a media effect.

Increase in the number of students learning AI and the proliferation of AI training institutions

ーーHas there been any change in the student participation rate for SIGNATE Quest?

Saito: The number of students is also increasing. The overall ratio is less than 30%, but it is an area that we would like to focus on in the future.

When I watch competitions for students, I see many students with high abilities. Five years ago, 10 years ago, data scientists were said to be the main force around the world, but recently there are also excellent students.

Especially in the field of deep learning, students have an advantage in all conditions, such as publication of papers and repositories, and time to work.

Today, the style of job hunting is also changing. Our company wants to provide a new UX for people who want to go on to professional jobs, so we will focus on services for students from now on. I would be happy if the number of student users increased further as a result.

ーーSome people are working on reforms on the academia side, but it’s quite difficult, isn’t it?

Saito: I am also a member of the evaluation committee, and the reform of data science education at universities promoted by the Ministry of Education, Culture, Sports, Science and Technology is progressing steadily. As for private schools, I look forward to future changes at universities that can take bold challenges , such as Musashino University’s Faculty of Data Science and Nihon University’s Faculty of Humanities and Sciences .

However, when I attended a conference, some students said, “My university has established an institution that can develop AI human resources, but it looks shady.” AI and DX are popular these days, so such institutions may be crowded.

I think that such institutions will be sorted out in the future, but it is important whether the content is accompanied when students gather the courage to come into contact with specialized fields .

ーーAre you thinking about collaborating with universities in the future?

Saito: SIGNATE provided SIGNATE Quest and Competition to universities free of charge during the corona crisis. At the beginning of the first wave of the spread of the new coronavirus infection, there was a period of time when students could not go to school, so at a university in Hiroshima Prefecture, more than 1,000 first-year students were able to use the service. It has been highly evaluated within the university, and has already reached the stage where its educational effects have been quantitatively proven. Currently, we are also promoting academic license sales for universities.

In the future, we will make further use of “PBL”, which is the strength of SIGNATE Quest. One of the difficulties in data science education is designing teaching materials that use realistic themes and data . To do this, it is necessary to cooperate with industry, but the university side is also struggling with not being able to cooperate well. Therefore, we would like to increase the opportunities for students to learn by playing the role of a bridge .

PBL: An abbreviation for Project Based Learning, this is a learning method in which students set their own problems, devise solutions to them, and implement them. A lot of knowledge can be obtained in the process of execution.

Future prospects of SIGNATE

ーーPlease tell us about your future prospects.

Mr. Saito: Looking at the recent DX initiatives in Japan as a whole , I think that there is not enough DX human resources, but also businesses and mechanisms .

SIGNATE is very successful as an example of developing AI/DX human resources, but since the number of members is about 50,000, we would like to increase the scale first. In order to promote DX in Japan, we need to have enough human resources to meet the demands of all domestic industries, so I would like to get involved in projects in various fields and promote training.

If the current situation continues, even if companies say they want to work on DX, there will be a shortage of supply, so there will be competition for human resources and jobs. This will result in many lost opportunities.

In order to prevent such a situation, we aim to develop DX human resources who can handle projects for multiple companies, rather than one project for one company. I believe that in order to develop such human resources, it is necessary for society as a whole to work together. We would like to offer our knowledge.

lastly

“AI human resources”, which was newly recognized a few years ago, is now attracting attention again as an important position responsible for DX in society. If you have experience working in a specific area so far, you will be able to get the chance to participate in a new project by stretching yourself a little more and expanding the scope of your work. Don’t miss the opportunity to make a big impact on your company and take on the challenge.

In the future, SIGNATE will work to expand the scale of its services in order to accelerate domestic DX. Attention will be focused on the future movement of SIGNATE, what kind of results the students who will lead the next generation will produce, and how far the influence will spread.

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