Call for contributions
Artificial Intelligence (AI) is rapidly establishing itself as one of the most transformative technologies of the 21st century, redefining the boundaries of innovation and opening new perspectives in response to global challenges. Its impact extends across key sectors such as industry, healthcare, education, environment, and finance. AI acts as a powerful catalyst, capable of optimizing processes, stimulating creativity, and offering sustainable solutions to the complex problems of our time.
However, this technological revolution also brings significant scientific, ethical, societal, and environmental challenges that demand thorough reflection and interdisciplinary collaboration.
The conference Artificial Intelligence for Digital and Sustainable Transition (AIDIST’2026) is part of the fifth edition of the International Citizen Forum on Education and Interdisciplinary Research (FCIERI). It aims to explore how AI can contribute to a profound and balanced transformation of our societies, while addressing the critical issues linked to its deployment.
The central question guiding the conference is as follows:
How can AI become the driving force of a digital and sustainable revolution, combining innovation, scientific progress, and ethical and environmental responsibility?
To answer this question, contributions to the conference will be organized around five interrelated tracks, each addressing a key dimension of AI’s impact on society.
Axes principaux
This track explores how AI technologies can contribute to ecological resilience and to building a more environmentally conscious society by optimizing the use of natural resources, reducing the environmental impact of human activities, and promoting more sustainable economic models.
The contributions within this theme will highlight concrete advances in AI applied to areas such as renewable energy management, biodiversity preservation, greenhouse gas emission reduction, and climate change mitigation.
This track is intended for AI researchers and practitioners, with a focus on scientific and technical contributions that address the challenges of sustainable development. Submissions may include, for example, intelligent resource management systems, real-time ecosystem monitoring models, or tools to raise awareness of ecological issues.
- AI and the sustainable management of natural resources
- AI for energy and ecological transition
- AI for biodiversity and ecosystem preservation
- AI for sustainable agriculture and responsible food systems
- Smart and sustainable cities
- AI for combating climate change
- AI for circular economy and sustainable innovation
- AI for environmental awareness and education
- Green AI: towards sustainable and low-impact artificial intelligence
Artificial Intelligence is playing an increasingly prominent role in the healthcare sector—whether in patient care, the management of medical resources, or even in diagnostic processes. Thanks to machine learning algorithms and advanced AI models, it is now possible to analyze vast amounts of biomedical data, detect diseases at an early stage, and tailor treatments based on genetic profiles, clinical data, and environmental information—particularly through the use of connected devices.
AI also helps optimize hospital workflows, automate the detection of anomalies in medical imaging, and support researchers in the discovery of new drugs. As a catalyst for the digital and sustainable revolution, AI promotes more accessible, efficient, and responsible medicine, offering innovative solutions to the pressing challenges faced by healthcare systems.
However, these advances also raise major concerns around ethics, data protection, and algorithmic transparency.
This track of the AIDIST’2026 conference will explore the concrete applications of AI in healthcare, its opportunities and limitations, and will shed light on future prospects in this rapidly evolving field.
- AI for diagnosis and medical decision-making
- AI in preventive, predictive, and personalized medicine
- AI in medical imaging
- AI for patient journey management
- AI in drug discovery
- Chatbots, NLP, and health-related interfaces
- AI in healthcare: ethical, regulatory, and societal challenges
- AI and public health
- AI in biomedical and bioinformatics research
- AI and smart medical devices
Artificial Intelligence is profoundly reshaping social interactions, political dynamics, and ethical challenges in our increasingly digitized societies. This track explores how AI influences citizenship, human relationships, and democratic systems, while highlighting the scientific and technical challenges involved in ensuring its ethical and responsible development.
The contributions under this theme will examine how AI can serve as a lever for informed citizenship and a fairer society. They will address critical issues related to AI applications in areas such as digital democracy, the fight against misinformation, intelligent surveillance, and the protection of individual freedoms.
A cornerstone of this track is Explainable AI (XAI), which aims to make algorithms transparent, fair, and accountable. Scientific contributions will demonstrate how AI techniques—such as natural language processing (NLP), sentiment analysis, and behavior modeling—can be used to strengthen public trust, ensure compliance with legal standards, and promote ethical decision-making.
Special attention will be given to generative AI, whose widespread adoption represents a major technological shift impacting all areas of society (education, research, employment, creativity, the environment, etc.). The technical and ethical challenges are numerous and include algorithmic bias, data protection, and the reliability of information.
Contributions may include case studies, algorithmic models, or frameworks designed to enhance the transparency, fairness, and accountability of AI systems in various contexts such as social media, elections, or personal data governance.
- AI and Digital Humanities (Historical, Cultural, Social Data, etc.)
- Democracy and Politics in the Age of AI
- Intelligent Surveillance, Protection of Freedoms and Personal Data
- Explainable AI (XAI) and Ethics
- AI and Social Media
- AI for Education and Research
- AI Governance and Regulationt
AI is profoundly transforming the manufacturing landscape throughout the product lifecycle by accelerating operational excellence from design to maintenance, including production and logistics. It also enables improved services by providing innovative solutions to complex challenges and optimizing processes. This axis focuses on the integration of AI in strategic areas, such as equipment design, manufacturing and maintenance, supply chain monitoring, transportation, incident prediction, and banking automation. Advances in AI are rethinking traditional economic and industrial models, creating new opportunities for businesses, financial institutions, and regulators. This axis highlights cutting-edge technologies such as machine learning, IoT (Internet of Things), CPS (Cyber Physical Systems), and blockchain by exploring their impact, innovation potential, and associated ethical challenges. Cybersecurity is a major challenge to consider. Cyberattacks exploiting vulnerabilities in new AI models pose a significant threat that can disrupt the proper functioning of these new solutions and affect users’ private data. Providing secure solutions and including real-time detection capabilities for vulnerabilities and potential intrusions is an absolute necessity to reassure users and successfully navigate this digital transition in industry and services.
- AI and Operational Excellence
- AI for Tomorrow’s Design and Engineering
- AI in Industrial Production and Manufacturing
- AI for Advanced Equipment Maintenance and Management
- AI in Transportation and Logistics
- AI in Finance and Banking
- AI and Blockchain in Finance
- Impact of AI on Customer Experience
- Ethics and Regulation of AI in Industry and Services
- AI in Public Services
- AI and Cybersecurity
- AI and IoT (Internet of Things)
- AI and CPS (Cyber Physical System)
Artificial Intelligence relies on fundamental advances in mathematics, computer science, and cognitive science, which shape its applications and evolution. This theme explores the theoretical developments, formal models, and innovative methodologies underlying AI systems, while examining their practical implications and limitations. Expected contributions in this theme will cover both conceptual advances (e.g., new learning paradigms, causal reasoning, and formal computational logics) and methodological challenges (robustness, generalization, interpretability). Particular attention will be paid to interdisciplinary approaches, the formalization of algorithmic biases, and critical evaluation methods for AI systems.
This theme encourages seminal work, epistemological analyses, and unifying frameworks, while remaining open to technical innovations (LLMs, optimization, multimodal processing, etc.) as long as they are accompanied by substantial theoretical reflection.
- Machine Learning Theory
- AI for Optimization
- Knowledge Representation and Processing
- AI and Reasoning
- Explainable AI (XAI) and Interpretability
- Multimodal Processing (NLP, Vision, Audio)
- Foundations of LLMs and Generative Models
- Complex Data Processing
- AI Agentics
- AI and Big Data
- AI and Computer Security
- AI and Software Engineering
- AI and Various Applications
Le Forum mondial sur l’éducation, tenu en mai 2015 à Incheon sous l’égide de l’UNESCO et ses partenaires, s’est conclu par la Déclaration d’Incheon pour l’Éducation 2030, un engagement historique de transformer la vie grâce à une nouvelle vision de l’éducation et à des actions courageuses et innovantes pour la réaliser. Le Cadre d’action Éducation 2030, qui établit cette nouvelle vision de l’éducation pour les 15 années à venir, a été adopté par plus de 180 états membres de l’UNESCO. Quatre ans plus tard, à la 9e Réunion mondiale de la Consultation collective des ONG pour Éducation 2030 (CCONG-Éducation 2030), qui s’est tenue en Tunisie en 2019, les organisations participantes ont affirmé que le monde est confronté à une crise éducative, causée par un manque de volonté politique, une faible priorisation de l’éducation et un financement insuffisant. De plus, elles ont constaté une tendance croissante à la commercialisation de l’éducation, ce qui contribue à creuser davantage les inégalités. Les systèmes éducatifs mondiaux ne semblaient pas respecter l’engagement pris dans le programme Éducation 2030. Le ministre de l’Éducation de la Tunisie d’alors avait, à la même occasion, souligné que la plupart des pays n’avancent pas suffisamment pour atteindre les objectifs fixés pour 2030. Il a appelé à une reconnaissance de l’importance stratégique de l’éducation pour toutes les nations et a encouragé la société civile à jouer un rôle majeur dans la mobilisation pour y parvenir.