Task 1: 1000-1500 words #1 Apply microeconomic principles to business decisions.#2 Apply macroeconomic principles to evaluate economic policy.Task 2: 1500 - 2000 words #1 Apply microeconomic principle

Task 2

The Economics of Artificial Intelligence

Artificial Intelligence (AI) has arrived in a big way. Businesses are investing large resources in developing and training AI models. AI models are being used for a wide range of activities ranging from relatively sophisticated tasks such as lenders evaluating the credit worthiness of potential borrowers to relatively mundane tasks such as writing emails, generating images, and classifying movie reviews according to whether they are positive or negative. While AI is touted as the next major revolution due to its potential in improving productivity, there is a dark side of AI too due to the massive carbon footprint of training and using AI models. It is also not clear what will happen to jobs overall as there is no guarantee that people who will lose their jobs to AI will be able to find jobs quickly enough, if at all.

This case study invites you to critically evaluate both the positives and the negatives of AI by using the conceptual lenses developed in this course. Specifically, you are provided with a set of readings. Based on these readings, you are given a number of questions, which you can answer by applying the concepts discussed in this course. You can further enrich your answers with the help of additional readings that you find interesting and relevant. Please note that the relevant module is mentioned next to each question implying that once the relevant module has been discussed in class, the corresponding question can be addressed. Based on past experience, attempting a case study of this nature, question-by-question, that is, thinking about and drafting your response to a question immediately after the relevant module has been discussed in the class usually works best.

Readings/Sources

Goldman Sachs (2024), “AI is poised to drive 160% increase in data center power demand”, May 14.
Noble, G. and Berry, F. (2024), “Power-hungry AI is driving a surge in tech giant carbon emissions. Nobody knows what to do about it”, The Conversation, July 8.
“AI images consume as much energy as charging your smartphone”, The CSRUniverse Team, March 8, 2024.
Watch the video titled, “How this AI powered money lender is challenging the credit system”. Available at: https://www.youtube.com/watch?v=-c1htWDXDwE
Stareika, M. (2024), “How alternative finance companies can use AI to help streamline SME lending”, Forbes Business Council, Jan. 10.
Farmonaut (2025), “Revolutionizing Australian SME financing: How AI driven lending is fueling business growth in a challenging economy”. Available at: Revolutionizing Australian SME Financing: How AI-Driven Lending is Fueling Business Growth in a Challenging Economy –

Questions

Q1) (Module 1): Discuss the opportunity costs associated with using ChatGPT.

Q2) (Module 2): Assume that ChatGPT and other generative AI models become very popular globally. For example, let’s say people start using ChatGPT instead of simple Google search to find what they are looking for. As a ChatGPT query requires 10 times as much electricity as a simple Google search, when hundreds of millions of people start using it, this has a large impact on how electricity is used in the world. Assuming that this shift lowers the world’s growth rate by 25 basis points, how large will the impact of this reduction in the growth rate be in a quarter of a century? (Use the average growth rate of 2021, 2022, and 2023 as the representative growth rate in the world. Use the real GDP level in 2022 as your starting point).(Cite your sources).

Q3) (Module 3): In the market for fossil fuel-based electricity generation, show the impact of generative AI.

Q4) (Module 4): What happens to the negative externality associated with the fossil-fuel based electricity generation as a result of the generative AI? Draw a clearly labelled diagram (of the negative externality) to show the impact. Provide a brief and clear explanation.

Q5) (Module 5 and Module 6): By using the AD-AS framework, illustrate and explain both the short-run and the long-run impact of using AI for mundane tasks that do not improve productivity (such as classifying movie reviews according to whether they are positive or negative, writing emails, generating images, and queries just for fun without a direct link to any productivity improvement etc.)

Q6) (Module 5 and Module 6): By using the AD-AS framework, illustrate and explain both the short run and the long run impact of using AI to improve access to finance to SMEs.

Q7 (Module 7) Discuss whether an increased reliance on AI makes RBA’s task of controlling inflation more difficult or easier. Clearly explain your logic.

Q8) (Overall Course/All Modules): Suppose you are a member of a committee tasked with studying the potential impacts of AI on the Australian economy and to provide recommendations for enhancing the positives while mitigating the dark side of AI. What recommendations will you provide?

Organization of the Case Study

This case study should be organized as follows:

Executive Summary (not counted in the word count but 100 words is typical)

Table of Contents

Introduction (not counted but 100 words is typical)

Question 1 (150-250 words)

Question 2 (150-250 words)

Question 3 (150-250 words)

Question 4 (150-250 words)

Question 5 (150-250 words)

Question 6 (150-250 words)

Question 7 (150-250 words)

Question 8 (150-250 words)

Conclusions (not counted but 100 words is typical)

References

Appendix (If any)

The overall word-count is expected to be in 1500-2000 words range. Table of Contents, References, and Appendix (if any) are also not counted towards the word count.