Artificial Intelligence in New Zealand: applications and innovation

Abstract

Artificial Intelligence (AI) is playing an increasingly significant role in various scientific research areas and real-world applications, ranging from AlphaGo design through medical imaging analysis, earthquake prediction to fish species classification, and fruit maturity estimation to online product recommendation. With world-leading researchers and practitioners, Aotearoa New Zealand is playing an important role in the global AI community. There have been significant achievements in AI in recent years. This special issue aims to highlight recent advances in AI research and developments from the New Zealand community in terms of theory and applications of AI. This special issue includes ten high-quality manuscripts (Chiewchan et al. 2023, Bi et al. 2023, Babu et al. 2023, Lim et al. 2023, Wilson et al. 2023, Cranefield et al. 2023, Bartlett et al. 2023, Rodger et al. 2023, Sagar et al. 2023, Wang et al. 2023). They cover a wide range of AI techniques and various real-world application areas of AI. AI techniques involved range from traditional AI areas like image analysis and computer vision, natural language processing and multi-agent systems to more recent techniques such as evolutionary machine learning, deep learning, few-shot learning, and explainable AI. These papers also explore how AI can be applied to our daily life, including the primary industries of NZ like agriculture and aquaculture, the critical areas like environment, health and medical, and wellbeing, as well as the considerations of te ao Māori, privacy, transparency, law, social impact in AI. Agriculture has been significantly impacting the world in various ways and is becoming more critical with the increasingly high food demand caused by the fast population growth. Many traditional methods used by farmers are either too costly in human labour or not sufficiently productive. AI provides great opportunities and potentials for boosting the efficiency and productivity of agriculture in a sustainable and safe way (Talaviya et al. 2020). In this special issue, Chiewchan et al. (2023) develop a multi-agent system for water irrigation in the Canterbury Region of New Zealand, which has the largest proportion of irrigated land (70%) in the country. Water resource consent has been introduced to control water usage, but it can be too expensive and lengthy for farmers with relatively small land to apply. Instead, they can join a community irrigation scheme, but it is hard to accurately estimate how much water they need, since it depends on many factors, such as the type of crop, the size of the farm, any imposed water reduction, and the priority of crops to irrigate. This paper explores a multi-agent system with auction-based negotiation for building an intelligent irrigation management system, to maximise water sharing within a community. Each agent represents a farmer to negotiate with other farmers and make decisions during the buying and selling process. Different auction mechanisms are investigated and the results show the multiunit uniform auction strategy performs the best in effectively distributing excess water in the community.