CSD Faculty Candidate
— 5:00pm
Location:
In Person and Virtual - ET
-
Newell-Simon 4305 and Zoom
Speaker:
AMIR-HOSSEIN KARIMI
,
Ph.D. Candidate, Max Planck ETH Center for Learning Systems, Max Planck Institute for Intelligent Systems & ETH Zurich
https://sites.google.com/view/amirhkarimi
Towards Trustworthy Human-Machine Collaboration
Advancements in technology such as the keyboard, mouse, touch-screens, voice-based communication, and today: data-enable interfaces (e.g., ChatGPT) have enabled more natural forms of interaction between humans and machines. Despite seemingly magical experiences, many questions remain open:
- How does one recover from, or overturn, poor experiences via decisions made by AI?
- How does one assay the safety, factuality, and ethics of AI systems to foster trust in AI?
- How does one design systems that make use of the best of human and machine abilities?
I argue that the next logical step, and the solution to all these questions, is to continue the line of development above, and facilitate even more interaction, discussion, and communication between humans and intelligent agents with the ultimate goal of “intelligence augmentation” via “trustworthy human-machine collaboration.” In this talk, I will describe efforts made to address these questions, as well as plans for future research.
—
Amir-Hossein Karimi is a final-year PhD candidate at the Max Planck ETH Center for Learning Systems, working under the guidance of Prof. Dr. Bernhard Schölkopf and Prof. Dr. Isabel Valera. His research interests lie at the intersection of causal inference, explainable machine learning, and program synthesis, with a focus on the problem of algorithmic recourse. Amir's contributions to the field have been recognized through spotlight and oral presentations at top conferences such as NeurIPS, ICML, AAAI, AISTATS, ACM-FAccT, and ACM-AIES. He has also authored a book chapter and a survey paper in the ACM Computing Surveys. Supported by the NSERC, CLS, and Google PhD fellowships, Amir's research agenda aims to address the need for systems that make use of the best of both human and machine capabilities towards building trustworthy systems for human-machine collaboration.
Faculty Host: Iliano Cervesato
In Person and Zoom Participation. See announcement.