inSIDE Fair Dialogues: Assessing and Maintaining Fairness in Human-Computer-Interaction

Sabine Janzen; Ralf Bleymehl; Aftab Alam; Sascha Xu; Hannah Stein

In: Demo Proceedings of Conference "Mensch und Computer 2018" (MuC2018). Mensch und Computer (MuC-2018), 2018.


For simulating human-like intelligence in dialogue systems, individual and partially conflicting motives of interlocutors have to be processed in dialogue planning. Little attention has been given to this topic in dialogue planning in contrast to dialogues that are fully aligned with anticipated user motives. When considering dialogues with congruent and incongruent interlocutor motives like sales dialogues, dialogue systems need to find a balance between competition and cooperation. As a means for balancing such mixed motives in dialogues, we introduce the concept of fairness defined as combination of fairness state and fairness maintenance process. Focusing on a dialogue between human and robot in a retailing scenario, we show the application of the SatIsficing Dialogue Engine (inSIDE) - a platform for assessing and maintaining fairness in dialogues with mixed motives.

Weitere Links

demo_submission_MUC_final.pdf (pdf, 2 MB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence