IEEE VIS 2024 Content: TalkToRanker: A Conversational Interface for Ranking-based Decision-Making

TalkToRanker: A Conversational Interface for Ranking-based Decision-Making

Conor Fitzpatrick - New Jersey Institute of Technology, Newark, United States

Jun Yuan - New Jersey Institute of Technology, Newark, United States

Aritra Dasgupta - New Jersey Institute of Technology, Newark, United States

Room: Bayshore I

2024-10-13T12:30:00ZGMT-0600Change your timezone on the schedule page
2024-10-13T12:30:00Z
Full Video
Abstract

Algorithmic rankers have proven to be very useful in many real-world socio-technical systems, as they assist greatly in making decisions (e.g., who to hire, who to admit). Our conversational interface, TalkToRanker, aims to empower non-expert information consumers to engage with algorithmic rankers via multi-modal conversations involving text and visualizations. We leverage explainable AI methods and the generative power of large language models (LLMs) for facilitating such conversations. We demonstrate the capabilities of TalkToRanker via interactive scenarios from the perspective of an admissions officer.