Booking a badminton court at one of Singapore's 100-odd community centers can be a workout in itself, with residents forced to type in times and venues repeatedly on a website until they find a free slot. Thanks to artificial intelligence (AI), it could soon be easier. The People's Association, which runs the community centers, worked with a government tech agency to build a chatbot powered by generative artificial intelligence to help residents find free courts in the city-state's four official languages. The booking chatbot, which could be rolled out shortly, is among more than 100 generative AI-based solutions spurred by the AI Trailblazers project, launched last year to find AI-based solutions to everyday problems.

The human ability to repurpose objects and processes is universal, but it is not a well-understood aspect of human intelligence. Repurposing arises in everyday situations such as finding substitutes for missing ingredients when cooking, or for unavailable tools when doing DIY. It also arises in critical, unprecedented situations needing crisis management. After natural disasters and during wartime, people must repurpose the materials and processes available to make shelter, distribute food, etc. Repurposing is equally important in professional life (e.g. clinicians often repurpose medicines off-license) and in addressing societal challenges (e.g. finding new roles for waste products,). Despite the importance of repurposing, the topic has received little academic attention. By considering examples from a variety of domains such as every-day activities, drug repurposing and natural disasters, we identify some principle characteristics of the process and describe some technical challenges that would be involved in modelling and simulating it. We consider cases of both substitution, i.e. finding an alternative for a missing resource, and exploitation, i.e. identifying a new role for an existing resource. We argue that these ideas could be developed into general formal theory of repurposing, and that this could then lead to the development of AI methods based on commonsense reasoning, argumentation, ontological reasoning, and various machine learning methods, to develop tools to support repurposing in practice.