Call for Visions

The pervasive integration of established representational tools with Artificial Intelligence (AI) systems in creative, analytical, and interpretative processes marks a paradigmatic shift. The ∀ISION_E project aims to systematically investigate this transformation, focusing on the concept of extended intelligences, a hybrid cognitive ecosystem where human agency and computational capabilities co-evolve symbiotically. This framework moves beyond the traditional dichotomy between tool and user, fostering a deeply collaborative paradigm.

This transition presents the scientific community with a dual responsibility: on one hand, to boldly explore future potential and envision new methodological horizons; on the other, to critically re-examine disciplinary memory, revaluing archives not merely as repositories of knowledge but as dynamic, active systems. The project seeks to develop reliable frameworks that, through AI, enable advanced semantic interrogation of archival content, unlocking its potential for contemporary research.

The integration of AI into creative and analytical practices inevitably raises critical epistemological, ethical, and deontological questions. Among the most pressing are: the redefinition of authorship in human-machine co-creation; the imperative of algorithmic transparency to ensure verifiability; and the establishment of new criteria for validating knowledge generated or interpreted through such systems.

Addressing these complex issues requires interdisciplinarity as a core methodological principle. No single field —whether Design and Representation, Computer Science, Philosophy, Cognitive Science, or Tech Ethics — can independently provide the conceptual and operational tools needed to fully address these challenges. Only through structured dialogue and critical synthesis across disciplines can a robust theoretical and operational framework emerge, one that governs this new paradigm rather than passively undergoing it.

Within this framework, ∀ISION_E launches a Call for Visions. This initiative aims not merely to collect academic contributions, but to invite reflections that, while maintaining rigorous scientific standards, contribute to a pluralistic and forward-looking vision.

To structure the scientific discourse, contributors are invited to frame their submissions according to one of the following thematic tracks. Proposed works may explore the theoretical, methodological, ethical, and operational implications of extended intelligences within the field of Representation and related disciplines.

1. AI for Representation and Design

Keywords:
Human-Machine Co-Creation - Active collaboration between designers and AI in generating ideas and solutions
Generative Design - Use of algorithms to automatically produce and optimize design solutions
Computational Aesthetics - Visual and formal languages emerging from algorithmic processes
AI-Driven Morphological Analysis – Form studies supported by artificial intelligence systems
Algorithmic Prototyping – Rapid creation of prototypes through AI-based automated processes

This track explores AI as a true creative partner, capable of supporting and expanding human imagination. The focus is on AI systems that do not merely execute commands but actively contribute to the generation of new ideas, forms, and visual languages. Submissions are invited that investigate methodologies for the creation, hybridization, and morphological/formal analysis of images and three-dimensional models, where AI becomes a tool for exploration and experimentation. Of particular interest are applications of predictive systems and co-design processes that establish a design dialogue between human and machine. Beyond practical applications, critical reflections on the emerging aesthetics of these processes are also encouraged—examining how collaboration with AI may redefine both design methodologies and aesthetic paradigms.

2. AI for Heritage Conservation and Enhancement

Keywords:
AI for Digital Heritage Innovation – Application of AI to the analysis and management of digital cultural heritage.

Semantic Enrichment – Automated enhancement of models and museum archives through intelligent metadata.

Predictive Conservation – Use of algorithms for diagnosis and prevention of artwork degradation.

Interactive Documentation – AI systems for dynamic museological narratives and documentation.
AI-Driven Accessibility – AI-based tools for expanding physical and digital access to collections.

This track aims to investigate the potential of Artificial Intelligence in the conservation, documentation, and enhancement of cultural heritage, with particular attention to the role of institutions dedicated to its protection and promotion, such as museums, archives, and libraries. Emphasis is placed on collaborative interpretation processes between human and artificial intelligence, where analytical and predictive capabilities of machines are integrated with the critical expertise of heritage professionals, generating new forms of shared knowledge. AI is understood not only as a technical support tool but as an agent capable of contributing to the semantic enrichment of digital models and archives, making them more accessible, searchable, and interconnected. Topics include interactive documentation systems that support innovative and dynamic storytelling; advanced diagnostics for preventive conservation and restoration; and the design of new access modalities for both physical and fully digital collections.

3. AI for Education and Learning

Keywords:
AI-Mediated Learning – Educational processes supported and personalized by artificial intelligence
Adaptive Learning Systems – Platforms that tailor content and learning paths based on student data
NLP-Based Education – Use of natural language processing for personalized educational interactions
Gamification AI – AI-driven game dynamics to enhance student engagement
Immersive Learning Environments – AI-enhanced virtual and augmented environments for interactive learning

This track explores the transformative impact of Artificial Intelligence on educational paradigms, focusing on the changes it introduces in teaching and learning processes. Special attention is given to models of personalized and interactive learning, in which AI acts as a mediator capable of adapting content, methods, and timing to individual student profiles and needs. Natural Language Processing (NLP) systems play a key role in enabling fluid and personalized interactions, alongside gamified approaches and immersive environments that foster active engagement. In addition to methodological innovation, the track encourages the development of rigorous approaches for validating and assessing learning outcomes in hybrid contexts—where technological and pedagogical dimensions intersect, reshaping contemporary education.

The Call for Visions seeks to gather original scientific contributions that, while adhering to a unified format, may span a wide range of theoretical and applied investigations.
Equal consideration will be given to works focused on the development and critical analysis of theories and methodologies, as well as to research centered on the description and evaluation of tools and concrete applications. The aim is to collect a plurality of perspectives that reflect both conceptual exploration and practical experimentation.

Submissions are therefore encouraged to include — but are not limited to — the following:

• the formulation of new theories and the proposal of innovative methodological frameworks

• critical analyses of ethical and social issues

• forward-looking reflections outlining future scenarios for the discipline

• the presentation of hardware/software implementations, prototypes, and innovative tools

• the discussion of specific case studies

• the documentation of educational practices and experimental teaching experiences

All contributions accepted through the review process will be published in an ISBN-registered volume and distributed under an Open Access license, ensuring maximum dissemination at no cost to the authors. In addition, the accepted works will be integrated into the ∀ISION_E Digital Atlas, a dynamic visualization tool designed to map and navigate the conceptual connections and thematic synergies among the various submitted visions.

Authors of selected contributions will be invited to present and discuss their work during the project's Interdisciplinary Conference. On this occasion, all accepted submissions will also be made accessible through an innovative conversational assistant powered by Retrieval-Augmented Generation (RAG) technology, providing an advanced and interactive exploration experience.

Call for Visions Opens: September 11, 2025

Abstract Submission Platform Open: October 20, 2025

Abstract Submission Deadline: November 14, 2025

Notification of abstract acceptance to authors: December 7, 2026

Deadline for submission of contributions: February 6, 2026

Communication of double-blind peer-review results: March 20, 2026

Interdisciplinary Conference ∀ISION_E: May-June, 2026