Conversational agents (CAs) are gaining traction in both industry and academia, especially with the advent of generative AI and large language models. As these agents are used more broadly by members of the general public and take on a number of critical use cases and social roles, it becomes important to consider the values embedded in these systems. This consideration includes answering questions such as 'whose values get embedded in these agents?' and 'how do those values manifest in the agents being designed?' Accordingly, the aim of this paper is to present the Value-Sensitive Conversational Agent (VSCA) Framework for enabling the collaborative design (co-design) of value-sensitive CAs with relevant stakeholders. Firstly, requirements for co-designing value-sensitive CAs which were identified in previous works are summarised here. Secondly, the practical framework is presented and discussed, including its operationalisation into a design toolkit. The framework facilitates the co-design of three artefacts that elicit stakeholder values and have a technical utility to CA teams to guide CA implementation, enabling the creation of value-embodied CA prototypes. Finally, an evaluation protocol for the framework is proposed where the effects of the framework and toolkit are explored in a design workshop setting to evaluate both the process followed and the outcomes produced.

The system recognizes facial that the tools we build have an impact on people's expressions in others using the outward camera and delivers psychological wellbeing and mental health.

Affective computing (AC) is an emerging field that aspires to narrow the communicative gap between the highly emotional human and the emotionally challenged computer by developing computational systems that recognize and respond to the affective states (such as moods and emotions) of the user. One of the basic tenets behind AC is that automatically recognizing and responding to a user's affective states during interactions with a computer can enhance the quality of the interaction, thereby making the computer interface more usable, enjoyable, and effective. For example, an affect-sensitive learning environment that detects and responds to student frustration is expected to increase motivation, engagement, and learning gains. This special track will serve as a forum to unite researchers from the interdisciplinary arena that encompasses computer science, engineering, HCI, psychology, and education to exchange ideas, frameworks, methods, and tools relating to affective computing. Although the last decade has been ripe with theory and applications relevant to AC, these advances are accompanied by a new set of challenges.