Overview

The Human-Centered Artificial Intelligence for Affective Computing (Affective HCAI) workshop explores the intersection of affective computing and human-centered AI, with a focus on designing systems that support, rather than replace, human cognition and decision-making. As affective computing technologies increasingly rely on sensitive personal data and influence human perception and behavior, they raise critical challenges related to privacy, fairness, cultural bias, and ethical responsibility.

This workshop brings together researchers across affective computing, human-AI interaction, and social computing to examine the socio-technical foundations of responsible Affective HCAI systems. Topics include privacy-preserving design, bias and cultural responsiveness, participatory and community-centered approaches, and methods for evaluating system impact across diverse populations. The workshop focuses on understanding the conditions under which Affective HCAI systems are perceived as supportive versus surveillant, as well as establishing principled approaches to data collection, retention, and ownership of affective and cognitive data. It also examines the risks associated with deploying these systems across cultural contexts for which they were not originally designed, and highlights the role of participatory and community-centered co-design in surfacing hidden biases and incorporating diverse cultural norms into system development.

Advancing ethical Affective HCAI requires participatory approaches that center the needs, rights, and lived experiences of diverse stakeholders. This workshop is particularly interested in approaches for designing systems that preserve meaningful human agency and autonomy when providing affect- or cognition-based support. It further seeks to examine the ethical boundaries of continuously sensing and interpreting internal human states, as well as methods for identifying and mitigating unintended influences of AI on users’ cognitive and affective processes. Additionally, the workshop highlights the responsibilities of designers in anticipating, evaluating, and mitigating potential harms, especially in contexts involving vulnerable or historically marginalized populations.

The Affective HCAI workshop will also explore how to design systems that support appropriate reliance, maintain human agency, and provide transparent, contestable explanations. By integrating technical advances with ethical and human-centered design principles, the workshop aims to advance Affective HCAI systems that are equitable, culturally grounded, and aligned with human values.

During the workshop, we hope to collaboratively identify and co-design key principles for Responsible Innovation in Affective HCAI, with the long-term goal of synthesizing these discussions into a community-driven publication.

Call for Papers

We welcome submissions addressing the following topics, including but not limited to:

1. Responsible innovation in the design of Affective HCAI systems 

• • Co-design and value-centered design

  • Centering ethics and privacy as core design principles

  • Prioritizing human agency and autonomy in system design

2. Socio-technical foundations of Affective HCAI systems 

• • Human-in-the-loop for real-time multimodal modeling of affect and cognition

  • Cost-benefit analysis for affective and cognitive inference

  • Intervention design and evaluations of human-centered control policies

  • Personalization vs. generalization

  • Explainable systems

3. Ethics, privacy, and governance 

• • Privacy risks of continuous affect monitoring

  • Data governance for sensitive emotional and cognitive data

  • Human agency when interacting with AC systems

  • Power dynamics in Affective AI-mediated interactions

  • Regulatory and societal implications of AC

4. Affective HCAI systems in social and group contexts 

• • Support in group decision-making or conflict resolution

  • Affective HCAI’s role in classroom collaboration or teaming

  • Collective trust in such systems

5. Culturally grounded affect modeling and representation 

• • Culturally variable expression and interpretation of affect 

  • Risks of cultural bias in affect recognition systems

  • Design of culturally responsive Affective HCAI systems

6. Applications across domains 

• • Affective HCAI systems for education, health, business

7. Technical and human-centered evaluation of Affective HCAI approaches 

• • Evaluation methods for fairness across socio-demographic and cultural groups

  • Sense-making of system feedback by different types of users, addressing cultural differences

8. Multicultural deployment and context adaptation 

• Adapting models and interaction policies across legal, cultural, and organizational settings

• Analyzing trade-offs between portability, localization, and validity in heterogeneous contexts

Submission Guidelines & Important Dates

We invite submissions in the two following formats:

• 7-page archival paper, published in the ACII 2026 Companion Proceedings in accordance with the ACII paper submission guidelines

  • • Submission Deadline: May 30, 2026 June 14

    • Notification of Acceptance: July 3, 2026

    • Camera-Ready Deadline: July 24, 2026

• 1-2 page unpublished position paper, which may may present preliminary findings, emerging ideas, or perspectives intended to stimulate discussion and foster early-stage collaboration within the community

  • • Submission Deadline: July 1, 2026

    • Notification of Acceptance: July 27, 2026

Contributions may be theoretical, empirical, or design-oriented. All submissions will undergo a peer-review process by the PC members and the organizing committee.

Papers need to be submitted to EasyChair.

Organizing Committee

Program Committee

• • Nadia Berthouze, University College London

  • Mariah Bradford, Colorado State University

  • Chelsea Chandler, University of Colorado Boulder

  • Tiantian Feng, University of Southern California 

  • Peter Foltz, University of Colorado Boulder

  • Tanaya Guha, University of Glasgow 

  • Leanne Hirshfield, University of Colorado Boulder

  • Sanjeev Nahulanthran, Monash University 

  • Minna Nygren, University College London

  • James Tavernor, University of Michigan

  • Jacob Whitehill, Worcester Polytechnic Institute