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