The keynote session explores strategies for integrating generative AI in education to enhance cognitive skills. Dr. Keirah Comstock emphasizes the importance of intentional use of AI tools and shares insights from her experience in developing AI policies and workshops for educators. Encourages educators to experiment with generative AI tools to enhance learning experiences.

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At the Grand Prix, innovative AI prompts were proposed across various fields, showcasing their potential. There is an ongoing increase in the types of generative AI becoming available, encompassing a wide range of applications such as text generation, image and video creation, and educational support. The utilisation of generative AI holds great promise in diverse fields such as education, healthcare, and design, and further advances are anticipated. In particular, generative AI’s potential for fostering non-cognitive skills in education was highlighted. However, considering risks (e.g., hallucinations), learning and employing appropriate prompt engineering techniques for effective use is essential.

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Recently, AI has made significant advances in the medical field. Notably, OpenAI’s GPT-4 successfully passed the Japanese medical licensing exam, demonstrating its diagnostic capabilities and showing its potential application in healthcare settings. Currently, methods to optimise patient hospital visits have become vital. Optimisation benefits patients because they can avoid unnecessary medical expenses for non-urgent symptoms, while hospitals, many of which face a shortage of doctors, can better utilise medical resources. Against this backdrop, an efficient and effective system is needed for both patients and healthcare providers. Our project leveraged the latest large language model and prompt engineering techniques to develop a system which diagnoses and advises patients on whether they need to visit a hospital. By using detailed symptom information provided by users, the AI offers appropriate medical advice, helping patients evaluate their symptoms confidently and reducing the burden on healthcare facilities. We expect this system to serve as a bridge between patients and medical institutions.

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Based on practical examples of design-specific prompts, we developed a new application that navigates to recommended AI software and provides design-specific prompts for that software. We named the application BLEND YOUR IMAGE.0 to 1.

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In this study, we developed a method for generating systematic and reproducible research data based on the knowledge learned by ChatGPT. Specifically, we designed and introduced a prompt that extracts the required data from ChatGPT to visualise the complex adversarial and cooperative relationships among major military powers. Using this prompt, we obtained structured data and applied multi-dimensional scaling to visualise the positional relationships between countries. The results showed that average values from multiple responses enhance the reproducibility of the data. This study contributed to further analyses by transforming ChatGPT’s responses into usable research data.

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‘Sakura Vision’ is a tool specialised for generating images of contemporary Japan. It is based on the GPTs of ChatGPT. Sakura Vision generates images of contemporary Japanese people and modern-day Japan with short, simple prompts without needing to specify detailed elements such as nationalities and the scene. In ChatGPT, prompting ‘Japanese people doing XXX’ often generates images of traditional Japanese people wearing kimonos or in Japanese-style rooms, which are far from reality for modern Japanese people. This issue may be caused by people with poor prompt settings playing with image generation, as it is not a part of their daily lives. Using Sakura Vision, we aim to generate images in a way that is easy for Japanese people to use, ensuring that the visuals align with contemporary Japan. This approach not only makes the tool more practical and relevant but also encourages wider adoption of image generation technology in everyday contexts, enhancing its integration and utilisation as a general tool.

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This prompt facilitates an immediate enhancement of individual motivation and productivity, maximising performance on time-sensitive tasks. Integrating the SCAMPER methodology, Nudge Theory and Maslow’s hierarchy of needs deeply addresses psychological needs, improving satisfaction and mental health in the workplace. Nudge Theory encourages desirable behaviour naturally, creating a stress-free work environment. Incorporating personal preferences in motivation strategies fulfils self-actualisation needs and maximises individual potential, boosting organisational performance and overall societal productivity. This approach also extends to education and welfare, promoting autonomous learning and activities, thereby enhancing knowledge and welfare quality in society. By employing a comprehensive framework, this prompt improves individual and organisational efficiency and contributes to broader social benefits, making it a valuable tool in various sectors.

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In recent years, the remarkable development of conversational generative AI (Generative AI) technology has enabled its application across various fields. This paper introduces a way to learn problem-solving skills using Generative AI. We tasked first-year university students with designing a lunch menu using local ingredients and plant-based foods. Collaborating with Generative AI, the students unleashed their creativity and generated innovative ideas. They learned how AI operates and what it can do, enhancing their AI literacy. This experience not only stimulated their imaginations but also provided practical insights into the potential of using AI in the creative processes. Through this task, students developed a better understanding of AI’s capabilities and limitations, preparing them for future technological advances. Integrating Generative AI in education offers a dynamic approach to learning by fostering creativity and technological proficiency among students.

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