Teaching

[B9145] Topics in Trustworthy AI

Ph.D. 2020, 2023.

As ML systems increasingly affect high-stakes decisions, it is critical that they maintain a reliable level of performance under operation. However, traditional modeling assumptions rarely hold in practice due to noisy inputs, shifts in environment, omitted variables, and even adversarial attacks. The standard machine learning paradigm that optimize average performance is brittle to even small distributional shifts, exhibiting poor performance on minority groups and tail inputs. Even performance of heavily engineered state-of-the-art models degrades significantly on domains that are slightly different from what the model was trained on. Lack of understanding of their failure modes highlights the need for models that reliably work, and rigorous safety tests to evaluate them.

This course surveys a range of emerging topics on reliability and robustness in machine learning. Most of the topics discussed in this class are active research areas, and relevant reading materials will draw upon recent literature (to be posted on the website). The goal of this class is to foster discussion on new research questions. This will encompass theoretical and methodological developments, modeling considerations, novel application areas, and other concerns rising out of practice.

[B8101] Business Analytics II: Foundations of AI

MBA and M.S. 2020-24.

Business analytics refers to the ways in which enterprises such as businesses, non-profits, and governments use data to gain insights and make better decisions. Business analytics is applied in operations, marketing, finance, and strategic planning among other functions. Modern data collection methods—arising in bioinformatics, mobile platforms, and previously unanalyzable data like text and images—are leading an explosive growth in the volume of data available for decision making. The ability to use data effectively to drive rapid, precise, and profitable decisions has been a critical strategic advantage for companies as diverse as Walmart, Google, Capital One, and Disney. Many startups are based on the application of AI & analytics to large databases. With the increasing availability of broad and deep sources of information—so-called “Big Data”—business analytics are becoming an even more critical capability for enterprises of all types and all sizes.

AI is beginning to impact every dimension of business and society. In many industries, you will need to be literate in AI to be a successful business leader. The Business Analytics sequence is designed to prepare you to play an active role in shaping the future of AI and business. You will develop a critical understanding of modern analytics methodology, studying its foundations, potential applications, and—perhaps most importantly—limitations.