The Economics of AI from Coursera

What's inside

Syllabus

What is Intelligence?

Welcome to the Economics of AI! This week, we are starting with an analysis of the nature of intelligence, its relationship to agents and goals, and the basics of information theory. We will also take a quick look at recent advances in AI and what they entail for our economy. These are materials that are not typically covered in economics courses, but they are crucial for understanding the profound changes that AI will trigger in our economy. We will build on them in the economic models that we will cover in the following modules. As you are working through the course materials, please share your impressions in our discussion forum. The forum also has a section in which I want to invite you to discuss the most up-to-date technological advances in AI and speculate how they will affect us.

Modeling Technological Progress

Welcome to week 2 of the Economics of AI! I hope that you have enjoyed the material so far, and that it has changed your outlook on AI. This week, we are going back to a more traditional economic theme: how to capture technological progress in economic models.We will pay particular attention to the possibility of labor-saving progress and to the increasing role of information goods, which differ fundamentally from more traditional factors because they are non-rivalrous. Given the growing importance and use of micro data, we will also cover the economics of production networks, which allows us to capture the effects of innovation at a more granular level. Please share your take – including any difficulties that you have with the materials – on the discussion forum. (And if you are on top of the material, I hope you'll go there to help your fellow classmates :)

AI and Economic Growth

Welcome to week 3. After last week’s materials on modeling technological advances, we are turning to their effects on economic growth, which has traditionally been the main driver of people’s living standards. Humanity has spent much of its history in a Malthusian state in which our material means were just enough to survive. The Industrial revolution marked a sea change and gave rise to continuous growth as captured by e.g. the Solow model. Will growth in the Age of AI follow a similar trajectory? Will it give rise to super-exponential growth or a singularity? Or will it throw us back into a Malthusian state?

Labor Markets and Inequality

Welcome to week 4 of the Economics of AI, in which we will zero in on the implications of technological advances such as AI for labor markets and inequality. We’ll start by looking at the effects of progress on labor markets in a neoclassical model. Next we’ll investigate the scope for technological unemployment and find that we should perhaps be even more concerned about inequality. After going over the developments in labor markets of recent decades, we’ll ask what it would mean for humanity if labor was phased out at in the future.

Economic Policy in the Age of AI

Welcome to week 5. We are using this week to examine how economic policy can respond to the economic challenges generated by advances in AI – based on an in-depth analysis of the relationship between technological progress and welfare. The economic policy responses that we’ll analyze include not only measures to enhance efficiency, such as technology policy, antitrust, or intellectual property regimes, but also measures to make the distribution of income more desirable, including pre-distribution and instruments of redistribution such as a UBI. We’ll also investigate how to steer technology into more desirable directions.

The Economics of Transformative AI

Congratulations on making it to the sixth and final week of our course, in which we will focus on two topics that are a bit more futuristic. First, we will examine how to think about an economy in which humans aren’t the only intelligent agents. Second, we will use the tools from economics to analyze the AI control problem. We conclude by highlighting the important role that thoughtful economic analysis can play in creating a better future.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Covers important topics like technological unemployment and control of AI algorithms

Examines the relationship between technological progress and economic growth, an important topic in economics

Taught by Anton Korinek, who is an expert in the economics of AI

Suitable for learners with a background in economics who want to specialize in the economics of AI

Requires learners to come in with a foundational knowledge of economics

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in The Economics of AI with these activities:

Connect with AI economics researchers or professionals

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Gain insights and guidance from experts in the field

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Identify potential mentors through professional networks or online platforms
Reach out and ask for guidance or collaboration
Meet regularly to discuss AI economics concepts and research

Read 'The Economics of Artificial Intelligence' by Ajay Agrawal, Joshua Gans, and Avi Goldfarb

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Gain a foundational understanding of the economic principles driving AI

View HBR's 10 Must Reads on AI (with bonus article... on Amazon

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Read and summarize each chapter

Participate in online discussion groups

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Expose yourself to multiple perspectives by engaging with peers online

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Join online discussion groups dedicated to AI and economics
Read and participate in discussions, asking questions and sharing insights

Four other activities

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Create a notebook or online repository for the course

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Organize course materials for easy reference and revision

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Collect materials such as lecture notes, readings, and assignments
Categorize and organize the materials

Practice mathematical models

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Gain deeper comprehension of theoretical concepts by applying them

Browse courses on Math

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Find exercises and problem sets related to AI economics
Solve the problems and compare your solutions with others

Complete online coding exercises on AI economics

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Gain hands-on experience applying AI economics concepts to real-world problems

Browse courses on Math

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Find online coding platforms that offer AI economics exercises
Solve the exercises and compare your solutions with others

Develop a blog or website on AI economics

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Improve comprehension and communication of AI economics principles

Browse courses on AI

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Choose a specific aspect of AI economics to focus on
Research and write articles or blog posts explaining the concepts
Share the content with others and gather feedback

Career center

Learners who complete The Economics of AI will develop knowledge and skills that may be useful to these careers:

AI Engineer

An AI Engineer designs, develops, and deploys AI systems. This course is an excellent fit for anyone in this career field, as it exposes learners to AI's economic implications. This understanding will help you to build AI systems that deliver a strong return on investment.

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Data Scientist

A Data Scientist makes use of data to inform decisions. This course provides context on how the data that you are analyzing is generated. It will also help you to understand how the data may change in the future, which could help you to make more forward-looking, actionable recommendations.

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Machine Learning Engineer

A Machine Learning Engineer develops machine learning models. This course is helpful because it will help you to identify situations in which machine learning models can be used to solve problems.

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Quantitative Analyst

A Quantitative Analyst develops and implements mathematical and statistical models to analyze and solve problems. This course will help you to develop your skills in these areas.

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Economist

An Economist researches economic issues. This course will help you to stay up-to-date on current economic issues and trends.

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Data Analyst

A Data Analyst makes use of data to inform decisions. This course provides context on how the data that you are analyzing is generated. It will also help you to understand how the data may change in the future, which could help you to make more forward-looking, actionable recommendations.

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Software Architect

A Software Architect designs computer software. This course helps build a foundation in the economics of artificial intelligence. Understanding the economics of AI will help you to make better decisions during the architectural design phase regarding what AI components to include in your software design and what features to deprioritize.

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Policy Analyst

A Policy Analyst develops and analyzes public policies. This course may be useful for gaining a better understanding of AI's economic implications.

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Financial Analyst

A Financial Analyst analyzes the financial performance of companies and industries. This course may be useful for gaining a better understanding of the financial implications of AI.

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Consultant

A Consultant provides advice to businesses and organizations. This course may be useful for helping you stay up-to-date on the latest technological trends that you can recommend to your clients.

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Market Research Analyst

A Market Research Analyst analyzes market data and trends. This course may be useful for gaining a better understanding of how AI is affecting markets.

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Teacher

A Teacher educates students in a particular subject. This course may be useful for providing you with the background that you need to teach the economics of AI to your pupils.

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Journalist

A Journalist writes and reports on current events and issues. This course may be useful for gaining a better understanding of AI's economic implications.

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Sales Manager

A Sales Manager leads and manages a team of sales representatives. This course may be useful for gaining a better understanding of AI's impact on the sales process.

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Operations Manager

An Operations Manager plans and oversees the day-to-day operations of a business. This course may be useful for gaining a better understanding of the challenges posed by AI.

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