[TMP-113] Socially Aware Interactions

Contact person: Frank Dignum (dignum@cs.umu.se)

Internal Partners:

1. Umeå University (UMU), Frank Dignum
2. Instituto Superior Técnico (IST), Rui Prada, Maria Inês Lobo, and Diogo Rato

 

In order for systems to function effectively in cooperation with humans and other AI systems they have to be aware of their social context. Especially in their interactions they should take into account the social aspects of their context, but also can use their social context to manage the interactions. Using the social context in the deliberation about the interaction steps will allow for an effective and focused dialogue that is geared towards a specific goal that is accepted by all parties in the interactions. In this project we started with the Dialogue Trainer system that allows for authoring very simple but directed dialogues to train (medical) students to have effective conversations with patients. Based on this tool, in which social context is taken into account only through the authors of the dialogue, we designed a system that will actually deliberate about the social context.

Results Summary

The MP addresses the following limitations of scripted dialogue training systems:

• Dialogue is not self-made: players are unable to learn relevant communication skills
• Dialogue is predetermined: agent does not need to adapt to changes in the context
• Dialogue tree is very large: editor may have difficulty managing the dialogue

Therefore, this project’s goal is the creation of a flexible dialogue system, in which a socially aware conversational agent will deliberate and provide context-appropriate responses to users, based on defined social practices, identities, values, or norms. Scenarios in this dialogue system should be easy to author as well.

The main result is a Python prototype of a dialogue system with an architecture based on Cognitive Social Frames and Social Practices, whose dialogue scenarios are easy to edit in a widely used tool called Twine. We also submitted a workshop paper.

Tangible Outcomes

1. Socially Aware Interactions: From Dialogue Trees to Natural Language Dialogue Systems. I. Lobo, D. Rato, R. Prada, F. Dignum In: , et al. Chatbot Research and Design. CONVERSATIONS 2021. Lecture Notes in Computer Science(), vol 13171. Springer, Cham. https://link.springer.com/chapter/10.1007/978-3-030-94890-0_8
2. Prototype of dialogue system – ines.lobo@tecnico.ulisboa.pt https://github.com/GAIPS/socially-aware-interactions
3. Video presentation summarizing the project