A major challenge in designing conversational agents is to handle unknown concepts in user utterances.
This is particularly difficult for general-purpose task-oriented agents, as the unknown concepts and
the tasks can be outside of the agent’s existing domain of knowledge. In this work, we propose a
new multi-modal mixed-initiative approach towards this problem. Our agent Pumice guides the user
to recursively explain unknown concepts through conversations, and to ground these concepts by
demonstrating on the graphical user interfaces (GUIs) of existing third-party mobile apps. Pumice
also supports the generalization of learned concepts to other different contexts and task domains.
more »
« less
Hey Google, Do You Have a Personality? Designing Personality and Personas for Conversational Agents
Conversational agents designed to interact through natural language are often imbued with human-like personalities. At times, the agent might also have a distinct persona with traits such as gender, age, or a backstory. Designing such personality or persona for conversational agents has become a common design practice. In this work, we review the emerging literature on designing agent persona or personality, and reflect on these approaches, along with the personas that are created for common conversational agents. We discuss open questions with regards to three aspects: meeting user needs, the ethics of deception, and reinforcing social stereotypes through conversational agents. We hope this work can provoke researchers and practitioners to critically reflect on their approach for designing personality or persona of conversational agents.
more »
« less
- NSF-PAR ID:
- 10354963
- Date Published:
- Journal Name:
- CUI 2021 - 3rd Conference on Conversational User Interfaces
- Page Range / eLocation ID:
- 1 to 4
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)This work investigates how social agents can be designed to create a sense of ownership over them within a group of users. Social agents, such as conversational agents and chatbots, currently interact with people in impersonal, isolated, and often one-on-one interactions: one user and one agent. This is likely to change as agents become more socially sophisticated and integrated in social fabrics. Previous research has indicated that understanding who owns an agent can assist in creating expectations and understanding who an agent is accountable to within a group. We present findings from a three week case-study in which we implemented a chatbot that was successful in creating a sense of collective ownership within a community. We discuss the design choices that led to this outcome and implications for social agent design.more » « less
-
null (Ed.)We summarize our past five years of work on designing, building, and studying Sugilite, an interactive task learning agent that can learn new tasks and relevant associated concepts interactively from the user’s natural language instructions and demonstrations leveraging the graphical user interfaces (GUIs) of third-party mobile apps. Through its multi-modal and mixed-initiative approaches for Human- AI interaction, Sugilite made important contributions in improving the usability, applicability, generalizability, flexibility, robustness, and shareability of interactive task learning agents. Sugilite also represents a new human-AI interaction paradigm for interactive task learning, where it uses existing app GUIs as a medium for users to communicate their intents with an AI agent instead of the interfaces for users to interact with the underlying computing services. In this chapter, we describe the Sugilite system, explain the design and implementation of its key features, and show a prototype in the form of a conversational assistant on Android.more » « less
-
Li, Yang ; Hilliges, Otmar (Ed.)We summarize our past five years of work on designing, building, and studying Sugilite, an interactive task learning agent that can learn new tasks and relevant associated concepts interactively from the user’s natural language instructions and demonstrations leveraging the graphical user interfaces (GUIs) of third-party mobile apps. Through its multi-modal and mixed-initiative approaches for Human-AI interaction, Sugilite made important contributions in improving the usability, applicability, generalizability, flexibility, robustness, and shareability of interactive task learning agents. Sugilite also represents a new human-AI interaction paradigm for interactive task learning, where it uses existing app GUIs as a medium for users to communicate their intents with an AI agent instead of the interfaces for users to interact with the underlying computing services. In this chapter, we describe the Sugilite system, explain the design and implementation of its key features, and show a prototype in the form of a conversational assistant on Android.more » « less
-
It has long been observed that humans in interaction tend to adapt their behavior to become more similar to their interlocutors. Yet the reasons why such entrainment arises in some conversations and not others remain poorly understood. Early work suggests an influence of different personality traits on the degree of entrainment speakers engage in. However, some of these results have never been replicated to test their generalizability. Moreover, a recent finding draws into question whether these and other effects are strong enough to create differences between speakers that persist across multiple conversations. We investigate a variety of personality traits for their influence on a local form of acoustic-prosodic entrainment in two kinds of spontaneous conversation. To our knowledge, this is the first attempt to detect such effects across several interactions per subject and the first attempt to replicate some influential early work in a more natural context. We find virtually no impact of personality, suggesting that prior results might not generalize to a more natural context or entrainment on other linguistic variables.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3469595.3469607
