Bio: Malihe Alikhani is an Assistant Professor at the Khoury School of Computer Science, Northeastern University. She earned her Ph.D. in computer science with a graduate certificate in cognitive science from Rutgers University in 2020. Her research interests center on using representations of communicative structure, machine learning, and cognitive science to design equitable and inclusive language technologies. This involves developing systems that can communicate and collaborate with diverse populations, especially those from underserved communities, for critical applications such as education, health, and social justice. Her work has received best paper awards at ACL 2021, UAI2022, INLG2021, and UMAP2022 and has been supported by DARPA, NIH, Google, and Amazon.

Abstract: With continued progress in scaling deep learning systems, there has been an increased interest in dialogue systems, also known as “Conversational AI”. In this talk, I will provide a short review of the past 20 years of data-driven system development through the lens of 5 major initiatives I was involved in.

I will focus on the sub-task of response generation, for which I will highlight lessons learnt and ongoing challenges, including: increasing faithfulness and factuality for task-based systems, safety critical issues for open-domain chatbots, and the often overlooked problem of anthropomorphic persona design. Throughout my talk I will ask more general questions of whether we should `blame’ the data, the model, the evaluation, or the design.

Bio: Verena is a Senior Staff Research Scientist at Google DeepMind, where she works on Safer Conversational AI. She is also honorary professor at Heriot-Watt University in Edinburgh and a co-founder of the Conversational AI company ALANA AI. Verena holds a PhD from Saarland University in Germany and a MSc from the University of Edinburgh, where she also spent time as a postdoctoral researcher.

She has 20 years of experience in developing and researching data-driven conversational systems. In the early 2000s she developed a series of breakthrough innovations that laid the groundwork for statistical dialogue control using Reinforcement Learning. More recently, Verena and her team pioneered work on identifying and addressing safety risks in neural conversational systems, which was awarded with a Leverhulme Senior Research Fellowship by the Royal Society.

Bio: David Traum is a principal scientist at ICT and a research faculty member at the Department of Computer Science at USC. At ICT, Traum leads the Natural Language Dialogue Group, which consists of seven Ph.D.s, four students, and four other researchers.

The group engages in research in all aspects of natural language dialogue, including dialogue management, spoken and natural language understanding and generation and dialogue evaluation. In addition, the group collaborates with others at ICT and elsewhere on integrated virtual humans, and transitioning natural language dialogue capability for use in training and other interactive applications.

Traum’s research focuses on dialogue communication between human and artificial agents. He has engaged in theoretical, implementational and empirical approaches to the problem, studying human-human natural language and multi-modal dialogue, as well as building a number of dialogue systems to communicate with human users.

He has pioneered several research thrusts in computational dialogue modeling, including computational models of grounding (how common ground is established through conversation), the information state approach to dialogue, multiparty dialogue, and non-cooperative dialogue.

Traum is author of over 200 technical articles, is a founding editor of the Journal Dialogue and Discourse, has chaired and served on many conference program committees, and is currently the president emeritus of SIGDIAL, the international special interest group in discourse and dialogue. He earned his Ph.D. in computer science at University of Rochester in 1994.