Workshop on Character Computing (C2)

Scope

This year's edition of the Workshop on Character Computing (C²) (9th Edition) focuses on the computational modeling, inference, and use of human character in intelligent systems, with a strong emphasis on Responsible and Trustworthy AI.

Character Computing studies how relatively stable traits (e.g., personality, values, cognitive styles) and dynamic states (e.g., emotions, motivation, stress, mental load), together with social, cultural, and contextual factors, can be computationally represented and operationalized to enable meaningful, human-centered personalization.

As AI systems increasingly shape access to opportunities, services, and information, character-aware systems introduce both powerful benefits and non-trivial risks. This edition explicitly addresses how Character Computing must evolve to remain ethically grounded, technically robust, and socially acceptable in the age of Generative AI, Large Language Models, and AI regulation (e.g., EU AI Act).

The workshop welcomes work that advances Character Computing while critically examining:

fairness, bias, and discrimination risks,
misuse and adversarial exploitation of character traits,
transparency, explainability, and accountability,
privacy-preserving and regulation-aware character modeling.

For background, see the Character Computing book (Springer) and the Wikipedia entry.

Aims and Topics of Interest

C² provides a forum to advance the theory, engineering, and governance of Character Computing systems. We particularly encourage work that bridges technical innovation with responsible deployment.

Submissions may address one or more of the following four complementary pillars:

1. Character Sensing, Profiling, and Representation

Multimodal character inference (text, speech, behavior, physiological, interaction data)
Uncertainty-aware and longitudinal character modeling
Privacy-preserving profiling (federated learning, differential privacy, secure computation)
Knowledge-driven and hybrid (symbolic–statistical) representations

2. Character-Aware and Adaptive AI Systems

Personalization, adaptation, and decision-making informed by character models
Character-aware recommender systems and assistants
Human–AI interaction shaped by personality, values, and cognitive traits
Evaluation frameworks for character-aware adaptation

3. Artificial and Synthetic Characters

Artificial personas, avatars, and agents with coherent character
Generative AI and LLM-driven character simulation
Consistency, controllability, and alignment of artificial characters
Ethical boundaries in simulating human traits and identities

4. Responsible Character Computing

Bias, discrimination, and harm amplification through character-based AI
Explainability and interpretability of character-aware decisions
Regulation-aware design (EU AI Act, risk categorization, compliance-by-design)
Human oversight, contestability, and accountability mechanisms
Character Computing for social good, mental well-being, education, and accessibility

Topics

Generative AI and LLMs for character-aware systems
Personality, affect, motivation, and value modeling
User modeling and adaptive personalization
Affective Computing and Personality Computing
Explainability, transparency, and interpretability in character-based AI
Bias, fairness, and discrimination risks in personalization
Responsible AI and AI for Social Good
Ethics and governance of character-aware systems
Knowledge representation, ontologies, and reasoning for character modeling
Machine Learning and Deep Learning for human traits
Privacy, security, and adversarial risks in character inference
Persuasive technologies and behavioral influence
Cognitive science, cognitive robotics, and human factors
Virtual, augmented, and mixed reality with character-aware agents
NLP, dialogue systems, and conversational personalization
Cybersecurity, human vulnerability modeling, and social engineering

Submission and Workshop Formats

We welcome full papers, short or position papers, work-in-progress papers, demos, and applied or industry case studies.
All submissions will undergo peer review. Accepted papers will appear in the PAAMS workshop proceedings, published and indexed by Springer.
C² will be held in a hybrid format, enabling both in-person and remote participation.
Details on important dates, submission instructions, and registration will be announced via the conference website.