Artificial intelligence (AI) refers to the field of computer science focused on creating machines or software that can perform tasks that would normally require human intelligence. These tasks include data analysis, pattern recognition, and repetitive task automation.
At its core, AI is about creating systems that can mimic cognitive functions such as learning from data (machine learning), analysing and processing language (natural language processing), and even supporting decisions (autonomous systems). AI can be classified into two broad categories:
Narrow AI (or Weak AI): This refers to systems designed to perform a specific task or a limited range of tasks. Examples include chatbots, recommendation systems (like those on Netflix or Amazon), or autonomous vehicles.
General AI (or Strong AI): This would be an AI system capable of performing any cognitive task that a human can do. It remains largely theoretical and has not been achieved yet.
While the concept of AI has existed for centuries in philosophical thought, the field of artificial intelligence has been actively developing for about 70 years, with significant advancements in the past two decades. The study of AI itself— its implications, risks, and governance— has become a major area of academic research, ensuring that AI technologies are developed and deployed in an ethical and responsible manner. For an excellent overview of the AI field, enrol in Sage Campus' Introduction to Artificial Intelligence course.
Generative AI fits within the broader field of artificial intelligence, but it is a specific subfield focused on systems capable of creating new content— whether this is text, images, code, music, video, or other forms of media— based on patterns generated from existing data.
Examples of Generative AI applications include:
Generative AI explained in 2minutes (2:00 mins) by AI-Campus is licensed under CC BY-SA 4.0
RMIT's position is that students must gain the capability to use generative AI as part of preparing them for the current and future workplace. (See the RMIT Educator Resource Hub.) Teachers at RMIT have a central role to play in helping students build familiarity and confidence in using generative AI.
Generative AI affects teaching in several different ways. It is available for teachers to build and improve their courses. Similarly, it is available to both teachers and students in the classroom. Finally, it is available to students in their own personal learning journey and when they tackle their assessments. The purpose of this guide is to connect teachers with the diverse resources available on each of these three aspects, to assist teachers navigate the interaction between generative AI and student learning.
This guide introduces:
In the years since generative AI first began to influence tertiary education, many policies, guidelines and resources have been developed across and beyond RMIT. Links to the most relevant and essential are provided in this guide. A good starting place is the RMIT module on Artificial Intelligence in Learning and Teaching, below.
Use of AI at RMIT is regulated by policies and guidelines. Below are listed the governance framework, along with collections of supporting policies from the Tertiary Education Quality and Standards Agency, and the RMIT Center for Education Innovation and Quality.
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