I Don’t Always Do What I Am Told: The Case for Task Incongruence-Aware Systems for Technology-Supported Reflection on Social Interactions

Abstract

Technology-supported Self-Reflection (TSR) systems aim to facilitate learning through self-reflection. In the social domain, these systems often nudge individuals to perform better towards a certain outcome in a targeted task. Typically, this idea of support assumes that users pursue specific goals, which system creators anticipate will govern users’ behavior in targeted tasks. However, how goals shape behaviors in social interactions is complex: individuals’ goals can be highly idiosyncratic and multifaceted, sometimes contradictory to their best interest, and they are often not explicitly formulated in advance. We believe that viewing this complex landscape through the lens of a simple task formulation imposes limitations on the type of support these systems can provide. In this paper, we take a first step towards investigating the incongruence between assumed task goals and observed users’ behaviors and decisions in a partner selection setting, where participants need to select a partner for a cooperation task, and the apparent task goal can co-exist with other personal or relationship-oriented goals. First, we identify task-incongruent decisions, showing that even in a highly structured and incentivized setting, some choices deviate from the assumed task goal. Second, using a Large Language Model (LLM) to analyze conversational behavior, we explore topic-based and interactional indicators of task incongruence. Although the behavioral evidence is mixed, these findings still illustrate that what appears to be a reasonably assumed goal by the system may not be what users end up pursuing. In designing TSR systems, we believe that it is crucial to have capabilities for Task-Incongruence Awareness (TIA), enabling meaningful reflections on how users’ consciously or unconsciously self-ascribed goals are aligned with their behaviors and decisions.