CIIR Talk Series: Uncertainty in Information Retrieval?
Title: Uncertainty in Information Retrieval?
Abstract: Search engines have become our main gateway to massive globally distributed repositories of human knowledge and cultural artifacts. Like all software systems, they may encode (purposefully or incidentally) the beliefs and biases of those who design and maintain them. To aggravate the situation, most modern search engines are trained on the basis of large-scale historic interaction patterns that may introduce additional unintentional (and difficult to detect) system behavior. In this talk, we will discuss the need for uncertainty estimation techniques in IR that can help searchers and search engineers uncover hidden biases as well as general system mechanics. I will showcase efficient uncertainty modeling techniques and their downstream applications to search result fairness and debiasing.
Bio: Carsten Eickhoff is a Professor of E-Health and Computer Science at the University of Tubingen, where his lab specializes in the development of information retrieval and natural language processing techniques with the goal of improving patient safety, individual health, and quality of medical care. Prior to joining Tubingen, he was the Manning Assistant Professor of Medical and Computer Science at Brown University. He received degrees from the University of Edinburgh and TU Delft, and was a postdoctoral fellow at ETH Zurich and Harvard University. Carsten has authored more than 100 articles in computer science conferences (e.g., ICLR, ACL, SIGIR, WWW, KDD) and clinical journals (e.g., Nature Digital Medicine, The Lancet - Respiratory Medicine, Radiology, European Heart Journal). His research has been supported by the Swiss National Science Foundation, NSF, DARPA, IARPA, Google, Amazon, Microsoft and others. Aside from his academic endeavors, he is a founder and board member of several deep technology startups in the health sector that strive to translate technological innovation to improved safety and quality of life for patients.
To attend this talk via Zoom, click here. To obtain the passcode for this series, please see the event advertisement on the seminars email list or reach out to Alex Taubman. For any questions about this event with the Center for Intelligent Information Retrieval, please contact Jean Joyce.