Related papers: Embracing Companion Technologies
The dominant metaphor of LLMs-as-minds leads to misleading conceptions of machine agency and is limited in its ability to help both users and developers build the right degree of trust and understanding for outputs from LLMs. It makes it…
While human-AI collaboration systems have increasingly been built to increase efficiency or support creativity, little work has examined how the design of interactions shapes the social connection between human and artificial agent. We…
When deployed, AI agents will encounter problems that are beyond their autonomous problem-solving capabilities. Leveraging human assistance can help agents overcome their inherent limitations and robustly cope with unfamiliar situations. We…
My research centers on the development of context-adaptive AI systems to improve end-user adoption through the integration of technical methods. I deploy these AI systems across various interaction modalities, including user interfaces and…
AI assistants are increasingly integrated into older adults' daily lives, offering new opportunities for social support and accessibility while raising important questions about privacy, autonomy, and trust. As these systems become embedded…
The science of Human-Computer Interaction (HCI) is populated by isolated empirical findings, often tied to specific technologies, designs, and tasks. This situation probably lies in observing the wrong object of study, that is to say,…
Agentic systems, in which diverse agents cooperate to tackle challenging problems, are exploding in popularity in the AI community. However, existing agentic frameworks take a relatively narrow view of agents, apply a centralized model, and…
Modern conversational agents such as Alexa and Google Assistant represent significant progress in speech recognition, natural language processing, and speech synthesis. But as these agents have grown more realistic, concerns have been…
As generative AI technologies rapidly advance, AI agents are gaining the ability not only to collect data and perform tasks but also to respond to environments and evolve over time. This shift opens new possibilities for reimagining digital…
Interactive intelligent systems, i.e., interactive systems that employ AI technologies, are currently present in many parts of our social, public and political life. An issue reoccurring often in the development of these systems is the…
Metaphors have been used during therapy sessions to facilitate the communication of inner feelings between clients and therapists. Can we create a digital metaphorical chatting space for daily use within close relationships? As the first…
Modern technology driven information systems are part of our daily lives. However, this deep integration poses new challenges to the human computer interaction (HCI) professionals. With the rapid growth of mobile and cloud computing and the…
This paper reports on a study conducted as part of the EU EMPATHIC project, whose goal is to develop an empathic virtual coach capable of enhancing seniors' well-being, focusing on user requirements and expectations with respect to…
Over the last couple of years, AI Agents have gained significant traction due to substantial progress in the capabilities of underlying General Purpose AI (GPAI) models, enhanced scaffolding techniques, and the promise to drive societal…
Human-like Agents with diverse and dynamic personalities could serve as an essential design probe in the process of user-centered design, thereby enabling designers to enhance the user experience of interactive applications. In this…
Physical agents that can autonomously generate engaging, life-like behaviour will lead to more responsive and interesting robots and other autonomous systems. Although many advances have been made for one-to-one interactions in well…
With the increased adoption of artificial intelligence (AI) in industry and society, effective human-AI interaction systems are becoming increasingly important. A central challenge in the interaction of humans with AI is the estimation of…
In this paper, we analyze the performance of an agent developed according to a well-accepted appraisal theory of human emotion with respect to how it modulates play in the context of a social dilemma. We ask if the agent will be capable of…
Active Inference is a closed-loop computational theoretical basis for understanding behaviour, based on agents with internal probabilistic generative models that encode their beliefs about how hidden states in their environment cause their…
With the growing use of artificial intelligence in classrooms and online learning, it has become important to understand how students actually interact with AI tools and how such interactions match with traditional ways of learning. In this…