Why Tacit Knowledge and Japan's AI Data Policy Are Changing the Game

Why Tacit Knowledge and Japan's AI Data Policy Are Changing the Game

In the world of learning and expertise, there has been a long-standing debate about the importance of tacit knowledge versus deliberate practice. Tacit knowledge refers to the knowledge that cannot be easily explained or captured through words alone. It is the type of knowledge that is acquired through emulation, action, and apprenticeship. On the other hand, deliberate practice is a more structured approach to learning, commonly found in fields like music, math, and chess.

Many argue that tacit knowledge is more valuable than deliberate practice. This is because tacit knowledge encompasses the embodied feelings and intuitive decision-making that are essential for true expertise. It is the ability to make complex judgments, balancing multiple considerations, that sets experts apart. And this type of knowledge is almost impossible to learn through explanation alone. It requires hands-on experience and a deep understanding of the principles behind the actions.

In fact, attempting to encode tacit knowledge into explicit procedures or expert systems often fails. The nuances, branches, and gotchas that experts navigate effortlessly cannot be easily captured in a step-by-step process. By providing people with a list of procedures to follow blindly, we deny them the opportunity to build their own expertise and hinder their ability to engage in creative problem-solving.

Instead, we should embrace the existence of tacit knowledge and focus on finding ways to gain it directly. Learning from masters through emulation, feedback, and osmosis allows us to internalize the principles behind their actions. This approach has been successfully employed by individuals like Warren Buffett, who spent years working under Benjamin Graham to learn the ropes.

Interestingly, the field of Naturalistic Decision Making (NDM) is dedicated to making this practice of acquiring tacit knowledge more effective. Keeping an eye on NDM methods and exploring ways to enhance our understanding of tacit knowledge can greatly benefit our journey towards expertise.

Speaking of groundbreaking approaches, Japan recently made headlines with its bold stance on AI data training. The Japanese government announced that it will not enforce copyrights on data used in AI training. This means that AI can freely use any data, regardless of its source or purpose.

Keiko Nagaoka, the Japanese Minister of Education, Culture, Sports, Science, and Technology, confirmed this decision, emphasizing that Japan's laws won't protect copyrighted materials used in AI datasets. While this move has sparked concerns among anime and graphic art creators, who fear that AI could devalue their work, the academic and business sectors are pushing for the use of relaxed data laws to propel Japan to global AI dominance.

One of the driving factors behind Japan's AI data policy is the need for access to high-quality training data. While Japan has a rich literary tradition, the availability of Japanese language training data is significantly lower compared to the English language resources in the West. Therefore, Japan seeks to tap into Western data to enhance its AI capabilities. This move adds an interesting twist to the ongoing debate about data regulation.

In conclusion, the importance of tacit knowledge cannot be underestimated in the pursuit of expertise. It is through emulation, action, and apprenticeship that we truly internalize the principles and intuitive decision-making required for mastery. While deliberate practice has its place in certain fields, the ability to navigate complex judgments and engage in creative problem-solving sets experts apart.

To harness the power of tacit knowledge and AI, here are three actionable pieces of advice:

1. Seek out mentors or masters in your field who can guide you through emulation, feedback, and osmosis. Learning from their expertise will allow you to gain tacit knowledge more effectively.

2. Stay updated on the advancements in Naturalistic Decision Making (NDM) methods. Explore ways to integrate these methods into your learning and problem-solving processes to enhance your understanding of tacit knowledge.

3. Embrace the potential of AI and its ability to process vast amounts of data. While ethical considerations are important, finding ways to leverage AI's capabilities can greatly enhance our understanding and application of tacit knowledge.

By combining the power of tacit knowledge with the advancements in AI, we can unlock new levels of expertise and problem-solving capabilities. So, let's embrace the importance of tacit knowledge and the potential of AI to shape a future where mastery and innovation go hand in hand.