The Future of Learning: AI Writing Tools and Tacit Knowledge

The Future of Learning: AI Writing Tools and Tacit Knowledge

In recent years, the rise of AI writing tools like ChatGPT has sparked debates about their role in education. Some argue that these tools facilitate cheating, while others see them as valuable learning aids. Sally Brandon, a communications lecturer at Melbourne's Deakin University, discovered that a significant number of essays she marked had detectable bot assistance. This alarming trend has led some schools in the US to ban the use of such tools to maintain academic integrity. However, it is essential to understand that AI writing tools like ChatGPT are not databases; they generate new prose based on learned characteristics. They are not infallible and may contain knowledge gaps and biases.

Rather than banning these tools outright, educators should focus on teaching students how to use them ethically and responsibly. Pope, an innovative and proactive educator, emphasizes the importance of developing students' awareness, knowledge, and skills in the ethical use of AI tools. By doing so, students can become digitally fluent citizens and employees who leverage these tools as efficiency aids rather than shortcuts.

Interestingly, universities have been aware of students using AI writing tools for some time. Professionals in various industries have also been utilizing these tools, blurring the line between cheating and legitimate use. Cheating has been a persistent issue throughout history, and as technology evolves, people will always find ways to exploit it. The key lies in fostering a culture of integrity and teaching students the value of genuine learning and critical thinking.

Moving beyond AI writing tools, another crucial aspect of learning is tacit knowledge. Tacit knowledge refers to knowledge that cannot be effectively conveyed through words alone. Instead, it is acquired through emulation, action, and apprenticeship. Tacit knowledge instruction involves imitating and internalizing the principles behind expert actions. When someone explains something with numerous caveats, it often indicates the presence of tacit knowledge in action. This kind of knowledge encompasses complex judgment and decision-making, which cannot be adequately learned through explanation alone.

Attempting to encode tacit knowledge into explicit rules or procedures has proven challenging. Expert systems that aim to capture all the nuances and considerations of human expertise often fall short. Providing individuals with a rigid set of procedures denies them the opportunity to develop true expertise and hampers their ability to engage in creative problem-solving. It is far more valuable to focus on gaining tacit knowledge directly, rather than hoping for a breakthrough in making it explicit.

Deliberate practice, on the other hand, is a concept that applies primarily to domains with well-established pedagogy, such as music, math, and chess. It involves following a set of predefined steps to improve performance. However, when it comes to acquiring tacit knowledge, deliberate practice is not as effective. Instead, individuals must seek out masters in their respective fields and learn through emulation, feedback, and osmosis. This method allows for a deeper understanding of the underlying principles and facilitates creative problem-solving.

The field of Naturalistic Decision Making (NDM) is dedicated to enhancing the effectiveness of this type of learning. NDM methods that focus on tacit knowledge hold great potential for revolutionizing expertise. By acknowledging the existence and significance of tacit knowledge, we can prioritize efforts to acquire it directly. Warren Buffett's years spent under Benjamin Graham exemplify the power of learning through emulation and osmosis.

In conclusion, the future of learning lies in striking a balance between leveraging AI writing tools like ChatGPT and embracing the acquisition of tacit knowledge. Rather than viewing these tools as a threat, they should be seen as valuable resources for efficiency and productivity. However, it is crucial to instill in students a sense of ethical responsibility and critical thinking. Three actionable pieces of advice to achieve this are:

1. Educate students on the ethical and responsible use of AI writing tools, emphasizing the importance of developing their own critical thinking and writing skills.
2. Encourage students to seek out mentors and experts in their fields of interest to learn through emulation, feedback, and osmosis.
3. Stay informed about advancements in Naturalistic Decision Making (NDM) and explore methods that focus on tacit knowledge acquisition, as these hold immense potential for enhancing expertise.

By embracing the possibilities offered by AI tools and nurturing the acquisition of tacit knowledge, we can shape a future of learning that combines efficiency and deep understanding.