[Digital MATSUMOTO's Observations (2024/7/25)] What are the 'fundamentals' for cultivating AI governance talent?

As the social implementation of AI progresses, the practice of AI governance has become required. What are the 'fundamental' skills for cultivating AI governance experts?

As the social implementation of AI progresses, the importance of AI governance is increasing. To cultivate AI governance experts, several 'fundamental' skills are required. These skills include not only technical knowledge but also ethical and legal perspectives, as well as communication skills.

First, the most basic skill is 'technical understanding'. Understanding the basics of AI algorithms and data processing is essential. For example, by understanding the basic knowledge of machine learning and the mechanisms of deep learning, one can grasp the operating principles of AI.This technical understanding serves as the foundation for conducting AI governance. Next, 'ethical perspective' is important.

The ability to understand and appropriately address ethical issues arising from the use of AI is required. This includes a wide range of issues, such as the impact of AI on humans, privacy protection, and ensuring fairness. For example, it is important to consider the problem of fake news caused by AI and the risks of algorithms that promote bias.'Legal knowledge' is also indispensable.

AI technology is evolving rapidly, and legal regulations may change accordingly. The ability to understand and adapt to current legal regulations is required. Furthermore, it is desirable to be well-versed in differences in international legal regulations. For example, it is necessary to understand and appropriately respond to the differences between the European Union's GDPR (General Data Protection Regulation) and Japan's Act on the Protection of Personal Information.'Communication skills' are also important.

AI governance must coordinate not only with the technical department but also with management, the legal department, and even general employees. Beyond having specialized knowledge, the ability to communicate it clearly is required. This enables understanding and cooperation across the entire organization, realizing effective governance.Finally, 'practical experience' is essential.

It is important to gain experience in actual use cases, not just theory. This provides valuable insights that can only be gained through the practice of AI governance. For example, participating in AI social implementation projects and applying the lessons learned there to the next project is required.In summary, to cultivate AI governance experts, technical understanding, ethical perspective, legal knowledge, communication skills, and practical experience are the 'fundamentals.' Talent equipped with these elements in a balanced manner will be able to play an important role in AI governance.

① Having basic knowledge related to AI model technology (equivalent to JDLA's G Certification)
② Understanding the overall configuration of systems, including IT and related technologies that link with AI
③ Project management ability
④ Being able to examine risks and countermeasures related to AI services in specific cases
⑤ Sense of responsibility

① [〇]
The text states that 'technical understanding' is essential, including the basics of AI algorithms and data processing, as well as an understanding of machine learning fundamentals and how deep learning works.

② [✕]
The text does not contain any specific description regarding 'understanding the overall configuration of systems, including IT and related technologies that integrate with AI.' While it might be included in technical understanding, it is not explicitly stated.

③ [✕]
The text does not contain any specific mention of 'project management ability.' While it may be implicitly included within practical experience, it is not explicitly stated.

④ [〇]
The text states that 'practical experience' is important, specifically the insights gained through experience in concrete use cases. It also mentions risks posed by AI under 'ethical perspective.'

⑤ [✕]
The text does not contain any specific mention of 'sense of responsibility.' While it may be implicitly included within ethical perspective or practical experience, it is not explicitly stated.

・Ethical perspective: The ability to understand and appropriately address ethical issues arising from the use of AI
・Legal knowledge: The ability to understand and adapt to current laws and regulations
・Communication skills: The ability not only to possess specialized knowledge but also to convey it in an easy-to-understand manner
・Practical experience: Gaining experience in actual use cases rather than just theory

As the social implementation of AI progresses, the importance of AI governance is increasing. To cultivate AI governance experts, several 'fundamental' capabilities are required. These capabilities include not only technical knowledge but also ethical and legal perspectives, as well as communication skills.

First,the most basic capability is 'technical understanding'It is essential to understand the basics of AI algorithms and data processing. For example, by understanding the fundamentals of machine learning and the mechanisms of deep learning, one can grasp the operating principles of AI.This technical understanding serves as the foundation for conducting AI governanceNext, an 'ethical perspective' is important.

The ability to understand and appropriately address ethical issues arising from the use of AIis required. This includes a wide range of issues, such as the impact of AI on humans, privacy protection, and ensuring fairness. For instance, it is important to consider the problem of AI-generated fake news and the risks of algorithms that promote bias.'Legal knowledge' is also indispensable.

AI technology is evolving rapidly, and legal regulations may change accordingly.The ability to understand and adapt to current laws and regulationsis required. Furthermore, it is desirable to be well-versed in differences in international legal regulations. For example, it is necessary to understand and appropriately respond to the differences between the European Union's GDPR (General Data Protection Regulation) and Japan's Act on the Protection of Personal Information.'Communication skills' are also important.

AI governance must coordinate not only with the technical department but also with management, the legal department, and even general employees. It is required not only to possess specialized knowledge but also to have theability to convey it in an easy-to-understand manner. This will lead to understanding and cooperation across the entire organization, realizing effective governance.

🤖 Added by Digital MATSUMOTO) 'Understanding the architecture and operation of the entire IT system, including AI' is also important. AI does not operate in isolation; it functions in coordination with a wide range of IT infrastructure such as databases, networks, and cloud environments. The ability to understand and appropriately manage the overall configuration of these systems is required. This allows for maximizing AI performance while minimizing risks.

🤖 Added by Digital MATSUMOTO) 'Project management ability' is also indispensable. Because AI governance projects are complex and wide-ranging, project management skills such as schedule management, resource allocation, and risk management are necessary. ⭐️ Added by Real Matsumoto) While AI is a technology that inherently contains uncertainty, it is required to continue responding to various changes after its utilization begins. Project management ability is important for practicing agile governance on-site for each individual AI service.And 'practical experience' is essential.

It is important to gain experience in actual use cases, not just theory.This provides valuable insights that can only be obtained through the practice of AI governance. For example, participating in AI social implementation projects and applying the lessons learned there to the next project is required.

🤖 Added by Digital MATSUMOTO) Finally, above all, a 'sense of responsibility' is essential. Since the social implementation of AI affects many people, an attitude of managing and operating it with responsibility is required. It is important to predict problems and risks that AI systems might cause and take appropriate measures. Also, a sense of responsibility to respond quickly and minimize impact when problems occur is necessary.
In summary, to cultivate AI governance experts, technical understanding, ethical perspective, legal knowledge, communication skills, understanding of the entire system, project management ability, and a sense of responsibility are the 'fundamentals.' Talent equipped with these elements in a balanced manner will be able to play an important role in AI governance.