AI Impact on Business
Objectives
Artificial Intelligence (AI) applications are present in virtually all aspects of our personal and professional lives. Businesses are increasing leveraging this class of technologies not only to provide value to the end consumer, but also to increase efficiency and reduce costs by automating and streamlining existing processes. This course aims at providing students with the knowledge and tools to make sense of AI in business contexts and how it can be used to transform existing business processes. This course will also focus on the interplay between AI and human judgment and on the short- and long-term implications of using these technologies in a wide range of contexts.
General characterization
Code
2663
Credits
3.5
Responsible teacher
Rodrigo Crisóstomo Pereira Belo
Hours
Weekly - Available soon
Total - Available soon
Teaching language
English
Prerequisites
n/a
Bibliography
Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction machines: the simple economics of artificial intelligence. Harvard Business Press.
Provost, F. and Fawcett, T. (2013). Data Science for Business: What you need to know about data mining and data-analytic thinking. O'Reilly Media.
Teaching method
Classes will be taught in a mixed style. Some sessions will follow a seminar-style format in which the conceptual material will be introduced and connected with real-world cases. Other sessions will be based on interactive discussions and practical examples.
Evaluation method
Class Participation (15%)
Group Assignment (35%)
Final Exam (50%)
Subject matter
Introduction & Course Mechanics. What is AI? . Opportunities and Limitations of AI in Business.
Evaluating Predictive Model:
Mechanics of Prediction Models . ROC curve. Expected Value Framework.
Scoping AI Projects:
Optimal decisions based on model performance. Scoping AI Projects.
Humans in the loop:
Integrating Human Judgment. How humans react to AI predictions? . Fairness.
Impact of AI in Society:
Impact AI in Society: Beyond business borders. Simple Economics of AI.
Course Wrap-up. Final Presentations.