Jul 2026· International Conference on Conversational User Interfaces· 0 citations· 45 references
Computer Science
TL;DR
This work presents the findings of a conceptual review that describes four concepts of agency, including personal agency, social agency, institutional agency, and artificial agency, and argues for shifts from individualistic toward holistic approaches to developing agentic conversational AI systems that sustain the authors' diverse and evolving forms of human agency in everyday life.
Abstract
Conversational AI systems are increasingly presented as agentic, intended to carry out tasks on behalf of users with a degree of autonomy. While agentic conversational AI systems have the potential to improve work efficiency and quality of life, they also introduce new risks and harms. We present the findings of a conceptual review that describes four concepts of agency, including personal agency, social agency, institutional agency, and artificial agency. Based on these interrelated concepts, we present four provocations to foster discussion on the extent to which conversational AI systems are becoming agentic and in which ways these systems may support and impede human agency. In doing so, we focus attention on the performative affordances of agentic conversational AI systems and highlight the societal responsibilities involved in their design. We argue for shifts from individualistic toward holistic approaches to developing agentic conversational AI systems that sustain our diverse and evolving forms of human agency in everyday life.
Conversational User Interfaces (CUIs) are rapidly advancing, moving from single-task assistants to powerful and engaging artificial agents. As CUIs become embedded in daily life, the implications for users interacting with such systems demand closer scrutiny. While some issues are immediately identifiable (e.g. privacy risks, misinformation, AI hallucinations), others may only become visible after longer periods of use, including over-reliance, erosion of human agency, or the normalization of biased or exclusionary language. This workshop aims to gather a multidisciplinary community to reflect on pressing challenges and uncertainties and explore risk analysis and mitigation strategies in CUI design and deployment. Through presentations, discussions, and collaborative design activities, participants will examine immediate and longitudinal risks and share empirical insights. The activities will support developing interdisciplinary frameworks to understand and handle unintended consequences of CUIs. The workshop seeks to build an international network of scholars and practitioners to promote responsible and human-centred conversational AI.
Manveer Kalirai, C. Wei, Thomas Essmeyer et al.· International Conference on...· 0 citations
It is argued that intelligence alone cannot determine appropriate goals, guide action under uncertainty, or ensure beneficial human outcomes, and proposed artificial wisdom as a needed corrective for conversational systems.
Matthias Kraus· International Conference on...· 0 citations
Proactivity has become a central concept in research on conversational user interfaces and human–computer interaction. It is an evolutionary stage for conversational agents. Nevertheless, despite the growing research on this topic, the term remains conceptually underspecified and inconsistently applied. Systems that send reminders or recommend content are often labeled as proactive, even when their underlying mechanisms and intentions differ fundamentally. This provocation argues that current uses of the term proactivity in the context of conversational AI are overly broad and conceptually imprecise, which limits our ability to design, compare, and evaluate proactive conversational agents. We synthesize perspectives from human-computer interaction, sociology, and psychology to propose a principled definition and a conceptual framework for proactive conversational agents to distinguish proactive from reactive and other related system behaviors.
Matthias Kraus, Sebastian Zepf, Jan Leusmann et al.· International Conference on...· 0 citations
This article develops a conceptual account of semantic displacement in conversational AI. The central question concerns how agency is affected when systems do more than automate information retrieval and begin to supply the descriptions, classifications and normative cues through which users understand what they are doing. Drawing on philosophy of action, philosophy of language, hermeneutics, philosophy of technology and critical accounts of algorithmic mediation, this article reconstructs the relation between meaning and action as a condition of agency. Its methodological approach is conceptual and diagnostic, oriented toward clarifying a problem that becomes visible when established theories are brought together in relation to contemporary conversational systems. The article interprets these systems as operational semantic infrastructures that organize context-sensitive linguistic uptake within practical environments such as health, work, education, administration and everyday self-management. It then introduces semantic displacement as the condition in which action-relevant meanings become increasingly organized, prioritized and consolidated outside the agent’s own participatory interpretation. The argument contributes a vocabulary for distinguishing agency-enhancing semantic support from forms of semantic substitution that weaken interpretive participation. It concludes by proposing semantic sovereignty and interpretive contestability as normative ideals for human agency in AI-mediated environments. The argument specifies action as intentional conduct understood under socially available descriptions and cognition as situated interpretive sense-making rather than purely internal computation. It also clarifies three conditions under which semantic support becomes displacement: opaque semantic generation, practical stabilization and reduced interpretive contestability.
The potential for conversational user interfaces (CUIs) to collaborate and even lead human teams engaged in a collaborative activity remains an intriguing yet largely underexplored application of CUIs. Specifically, little seems to be understood about how people perceive such agents and their reasoning behind it. To begin to examine this intriguing topic, we performed a thematic analysis on open ended questions posed to participants after being led by either a human or CUI based leader on a collaborative task. Analysis revealed five key themes around how they perceived the leader they were interacting with: guidance, voice, understanding, timing and behaviour. These themes ultimately shaped how participants reasoned about whether the leader guiding them was a human, or autonomously controlled, highlighting key considerations designers should consider when creating such collaborative conversational agents.
James Simpson, Hamish Stening, Gaurav Patil et al.· International Conference on...· 0 citations
This research investigates the pragmatic differences between conversational implicatures produced by artificial intelligence systems and those generated by humans in everyday conversation. Grounded in Grice’s Cooperative Principle and its four conversational maxims—quantity, quality, relation, and manner—the study analyzes how implicatures emerge, function, and are interpreted in human–human and human–AI "chat GPT" interactions. Adopting a qualitative descriptive-analytical approach, the study examines ten conversational exchanges: five human conversations and five AI-based conversations. The analysis reveals that while artificial intelligence can simulate implicature-like meanings, these implicatures often lack intentionality, contextual sensitivity, and shared socio-cultural grounding. In contrast, human implicatures are deeply rooted in communicative intention, contextual awareness, and social norms. The findings contribute to pragmatic studies and human–AI "chat GPT" communication by highlighting the fundamental pragmatic gap between artificial and human conversational behavior.
Raghad Hawarin, Dr. Mahmod Eshreateh· Journal of Language, Literat...· 0 citations