8 May
2025
8 May
'25
1:37 p.m.
* Apologies for multiple copies. Please forward this to anybody who might be interested;
thanks! *
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Call for Papers
COL-SAI: 1st International Workshop on COllaboration and Learning through Symbiotic
Artificial Intelligence
Co-located with the 16th Biannual Conference of the Italian SIGCHI Chapter -
"Technologies and Methodologies of Human-Computer Interaction in the Third
Millenium" (CHITALY 2025)
Salerno, Italy
6 – 10 October 2025
Workshop website: https://sites.google.com/unisa.it/col-sai/home-page
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Important Dates
Submission deadline: June 16th 2025
Notification: June 30th 2025
Camera-ready: TBD
Registration due: TBD
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Objectives
This workshop aims to explore how humans and AI systems can effectively collaborate, learn
from each other, and co-adapt symbiotically. Through discussions and the exchange of
perspectives, the workshop has the goal of investigating the key components of the
interaction between the two parties. Participants will gain deeper insights into the
implications of integrating AI into various aspects of daily life, facilitating
problem-solving activities such as learning, decision-making, and co-creation.
The workshop will be structured as follows: after an initial introduction by the
organizers concerning the topics and objectives, there will be presentations for each
contribution (10 minutes circa), followed by questions from the other participants. At the
end of the session, there will be a participatory activity, through which we will be able
to exchange ideas, comments, and reflections concerning the best practices and challenges
of Symbiotic Artificial Intelligence for Collaborative Learning Environments.
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Topics
The topics that will be addressed in the workshop are the following:
The impact of a symbiotic human-AI relationship in collaborative environments.
Human-Computer Interaction methodologies and techniques to foster symbiosis between humans
and AI.
Using AI in human learning processes to assist humans cognitively.
Using AI for education and skill development.
Methodologies and techniques for transferring knowledge between humans and AI through
feedback mechanisms.
Ethical considerations in human-AI collaborative environments (bias mitigation, fairness,
non-discrimination, etc).
AI adaptability for personalized interaction experience based on individuals'
requirements.
The role of trustworthiness in human-AI collaboration for critical activities.
Design and evaluation of systems that foster and support human-AI collaboration.
Case studies of AI in real-world applications (medicine, healthcare, education, etc).
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Submissions and Evaluation Criteria
Contributions for the workshop must be submitted through EasyChair using the following
link https://easychair.org/conferences/?conf=colsai2025, following the LaTeX or Microsoft
Word template, available at: https://ceur-ws.org/Vol-XXX/CEURART.zip. For more
information, visit the CEUR website.
We accept two types of submissions:
Full paper: at least 10 "standard" pages* and an appropriate number of
references.
Position paper: between 5-9 "standard" pages*.
*(1 standard page = 2500 characters)
Each submission will be subjected to a single-blind peer review process, and two reviewers
from the Program Committee (PC) will assess each contribution in terms of relevance to the
workshop’s topics and its quality.
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Workshop Organizers
Miriana Calvano – University of Bari, Italy (miriana.calvano(a)uniba.it
<mailto:miriana.calvano@uniba.it>)
Andrea Cantone – University of Salerno, Italy (acantone(a)unisa.it
<mailto:acantone@unisa.it>)
Antonio Curci – University of Bari, Italy (antonio.curci(a)uniba.it
<mailto:antonio.curci@uniba.it>)
Francesca Pia Perillo – University of Salerno, Italy (fperillo(a)unisa.it
<mailto:fperillo@unisa.it>)
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This workshop is supported by the co-funding of the European Union - Next Generation EU:
NRRP Initiative, Mission 4, Component 2, Investment 1.3 – Partnerships extended to
universities, research centers, companies and research D.D. MUR n. 341 del 15.03.2022 –
Next Generation EU (PE0000013 – “Future Artificial Intelligence Research – FAIR” - CUP:
H97G22000210007, Spoke 6, WP 6.1).