Call for Papers: Special Session on AI Education, ICONIP 2024

AI Education

There has been an explosion in the applications of Artificial Intelligence (AI). While Large Language Models such as ChatGPT have garnered much of the attention, other AI technologies have also found wide application, such as the predictive keyboards on mobile devices, and facial recognition systems in supermarkets. Some technology venture capitalists have reported that 80% of the funding pitches they receive involve AI. Many business owners believe that AI is going to put them out of business, unless they adapt to the technology. Others are desperately searching for ways to get onto the AI bandwagon. This surge in interest in AI has led to a worldwide shortage of AI engineers. Furthermore, the inappropriate application of AI, whether through the use of biased data or unethical applications, has also led to social and economic fallout. 

The increased public awareness of AI technologies has also led to a proliferation of media commentary, of varying degrees of competence, and governmental regulation. Some students have taken to using AI tools to assist in their assignments, while others have changed their career pathways due to a perception that AI is going to destroy their future job prospects.

There is, therefore, a need for education about AI. This need spans nearly all levels of education, from primary school through to postgraduates. At primary and secondary level so that people enter the working world with the basic knowledge of AI and how it affects their lives. At tertiary undergraduate and postgraduate level so that we have a steady supply of engineers and developers who can utilise AI in an appropriate and ethical manner.

This all raises a fundamental question: How is this education being done?

This special session is intended to attract papers dealing with all aspects of AI education. Topics of interest include, but are not limited to:

• Incorporating AI into teaching curricula at all levels of education
• The design and implementation of AI-specialist teaching curricula
• Technologies used to teach AI
• Teaching the ethics of AI
• Policy making around AI education
• The teaching of specialist topics within AI
• Work-integrated learning and project-based teaching in AI

A special session of ICONIP 2024, to be held in Auckland, New Zealand 2-6 December, 2024.

Important Dates

Paper Submission Deadline: 7 June 2024

Notification of Acceptance: 26 July 2024

Camera Ready Submission: 30 August 2024

Registration Deadline: 30 August 2024

Conference Dates: 2-6 December 2024

Important Links

Main conference site: https://iconip2024.org/

Organisers

Mike Watts is a Senior Lecturer in Artificial Intelligence, and Programme Coordinator of the Bachelor of Information Technology at Media Design School, Auckland, New Zealand. He was previously a research fellow in the School of Earth and Environmental Sciences at the University of Adelaide, Australia. Before that, he was a post-doctoral fellow in the School of Biological Sciences at the University of Sydney and at the National Centre for Advanced Bio-Protection Technologies at Lincoln University, New Zealand. Mike completed his PhD in artificial intelligence at the University of Otago, New Zealand, in 2004 and has published more than 80 peer-reviewed publications in the field of AI and ecological modeling.

Akbar Ghobakhlou is Data Science and Machine Learning lecturer within the School of Engineering, Computer & Mathematical Sciences at Auckland University of Technology. His research centres on practical uses of intelligent technologies like monitoring, visualization, and predictive models. His interests cover data mining, machine learning, image processing, smart sensors in precision agriculture, and environmental monitoring. Akbar is an active member of the IEEE community, specifically within the Instrumentation and Measurement Society (IMS). He organised and chaired the annual IMS two-day workshop in 2023. Akbar completed his PhD in artificial intelligence at the University of Otago, New Zealand has numerous peer-reviewed publications in the field of AI and IoT applications.

Ranpreet Kaur is a Lecturer in the Department of Bachelor of Software Engineering and Artificial Intelligence at Media Design School. She was previously a research and teaching assistant in the School of Engineering, Computational, and Mathematical Sciences at Auckland University of Technology. She has 15 years of academic career primarily focused on teaching and research. She has completed her PhD in Computer Science and Artificial Intelligence from Auckland University of Technology. She has published more than 20 high-quality research papers such as into Q1 and Q2 journals, international conferences, book chapters, and symposiums. She has been currently involved in various research projects.