Course Title: Economics of Artificial Intelligence
Part A: Course Overview
Course Title: Economics of Artificial Intelligence
Credit Points: 12.00
Course Coordinator: Chris Berg
Course Coordinator Phone: .
Course Coordinator Email: chris.berg@rmit.edu.au
Course Coordinator Location: City Campus
Course Coordinator Availability: Appointment by email
Pre-requisite Courses and Assumed Knowledge and Capabilities
Assumed knowledge: ECON1623 Economic Foundations of the Digital World
Course Description
This course explores the economic implications of Artificial Intelligence (AI) in the digital economy. Through an industry-oriented and practical approach, you will investigate AI's potential to drive innovation, enhance economic growth, and unlock new opportunities. Over the course of the semester, you will critically examine the economic, ethical, regulatory, and societal challenges posed by AI, such as automation-induced inequality and data privacy concerns. You will engage with real-world cases, simulations, and industry scenarios to practically address the economic impacts of AI and formulate informed, innovative solutions.
Objectives/Learning Outcomes/Capability Development
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On successful completion of this course, you will be able to:
CLO1: Analyse the foundational economic theories relevant to the adoption and impact of AI technologies.
CLO2: Evaluate the transformative economic effects of AI on productivity, labour markets, innovation, and market competition.
CLO3: Critically analyse the ethical, social, and regulatory dimensions of AI implementation in economic contexts.
CLO4: Formulate evidence-based strategic responses to economic challenges and opportunities presented by AI.
CLO5: Develop effective methods to communicate effectively and clearly, integrating interdisciplinary knowledge related to AI economics.
Overview of Learning Activities
In this course, you will actively engage in diverse learning activities, including interactive class discussions, multimedia content exploration (videos, podcasts), critical review of academic literature and industry reports, participation in real-world simulations and scenario planning, reflective writing tasks, and collaborative projects with peers. These varied activities support applied learning and professional skill development, preparing you for the dynamic landscape of the digital economy.
The delivery of this course is blended comprising of face-to-face and online learning.
Overview of Learning Resources
Various learning resources are available online through MyRMIT Studies\Canvas. The lecture notes and workshop notes are posted on Canvas.
Resources are also available online through RMIT Library databases and other facilities. Visit the RMIT library website for further details. Assistance is available online via our chat and email services, face to face at our campus libraries or via the telephone on (03) 9925 2020.
Additional resources and/or sources to assist your learning will be identified by your course coordinator and will be made available to you as required during the teaching period.
Overview of Assessment
The assessment tasks, their weighting and the course learning outcomes to which they are aligned are as follows:
Assessment Task 1: 20%
Linked CLOs: 1
Assessment Task 2: 40%
Linked CLOs: 2, 3, 5
Assessment Task 3: 40%
Linked CLOs: 3,4,5
Feedback will be provided throughout the semester in class and/or in online forums through individual and group feedback on practical exercises and individual consultation.