Yi-Chia Wang (Uber AI) “Improving Customer Support at Uber with Conversational AI”

When:
November 30, 2018 @ 12:00 pm – 1:15 pm
2018-11-30T12:00:00-05:00
2018-11-30T13:15:00-05:00
Where:
Hackerman Hall B17
3400 N Charles St
Baltimore, MD 21218
USA
Cost:
Free

Abstract

Goal-oriented conversational systems are becoming ubiquitous in daily life for tasks ranging from personal assistants to customer support systems. For these systems to engage users and achieve their goals, they need to 1) not just provide informative replies and guide users through the tasks but also 2) interact with them in a natural manner.  This presentation will cover how Uber applies and studies conversational AI techniques to address these two research questions and provide delightful user experiences especially regarding customer care services.  To answer the first question, I will describe COTA, a productionized system we built to improve the speed and reliability of customer support for end users through automated ticket classification and answer selection for support representatives.  After that, in order to build conversational agents which can generate more natural responses, we applied statistical modeling techniques to understand whether and how social language is related to user engagement and task completion in goal-oriented conversations, which motivated us to propose a conversational agent model capable of incoporating social language into agent responses.
Biography
Yi-Chia Wang is a Research Scientist at Uber AI, focusing on conversational AI and customer support.   Prior to this role, she received her Ph.D. from the Language Technologies Institute in School of Computer Science at Carnegie Mellon University.  She worked with the Facebook Core Data Science team for her dissertation which developed a machine learning model to understand the causes and consequences of self-disclosure on Facebook.  Her research interests and skills are to combine language processing technologies, machine learning methodologies, and social science theories to statistically analyze large-scale data and model human-human / human-bot behaviors.  She has published more than 20 peer-reviewed papers in top-tier conferences and journals such as CHI, CSCW, and KDD, and has more than 1,000 citations.  She received prestigious awards, including the CHI Honorable Mention Paper Award, the CSCW Best Paper Award, and the AIED Best Student Paper Nomination.

Johns Hopkins University

Johns Hopkins University, Whiting School of Engineering

Center for Language and Speech Processing
Hackerman 226
3400 North Charles Street, Baltimore, MD 21218-2608

Center for Language and Speech Processing