Increased life expectancy is an achievement of modern society in OECD countries (and recently in developing countries) thanks to technological progress in health, living places, and the quality of food. The aggregate consequence of the prolongation of the life-time span is the growth of an ageing society, as testified by several demographic studies. The study of the consequences of an ageing society on the future of social living has recently been considered by large world institutions (UN, EU), which addressed and designed programs for social and technological development taking into account the impact of the ageing society on the future of the world. Within this framework, topics such as “prolonging independent living,” “aging well,” or “social inclusion” are increasingly becoming more and more relevant. Several initiatives all over the world took care of these aspects, focusing on the problem of developing a new generation of innovative technologies to face an aging society and its growing needs. In this scenario, Artificial Intelligence (AI) methods and techniques have and will have a pivotal role, due to the advanced goals of the discipline and its inner cross-disciplinary attitude, to deliver innovative and impactful results and related technologies. The development of AI-based solutions to support longevity to cope with the changes of aging and cognitive capacities represents one of the most advanced ICT areas in the AI field. Road Security, Continuous Learning and Navigation Supports for in-and-outdoor Systems are the fields where AI may challenge its solutions and contribute to innovative technological changes.
Workshop on Artificial Intelligence for an Ageing Society (http://aixas.it/), held within the 22nd (F. Milella) for Artificial Intelligence in the Ageing Society domain. Capitalizing from these activities, the group is establishing a stable forum on the topic and organized the this workshop with the goal of collecting contributions, ideas and new scientific and technological scenarios, as well as to discuss and disseminate results on Artificial Intelligence for an Ageing Society. Artificial intelligence (AI) methods and techniques have and will have a pivotal role, due to the advanced goals of the discipline and its inner cross-disciplinary attitude, in order to deliver innovative and impacting results and related technologies. The development of new AI-based solutions to support and help older adults, as well as those close to them, to cope with the changes of ageing and cognitive decline represents one of the most advanced ICT areas in the AI field. Nevertheless, facing the problems of an ageing society requires a crossdisciplinary approach, too. For this reason, the transition from a workshop focused on Artificial Intelligence for Ambient Assisted Living, as in previous years, to a more pervasive workshop on Artificial Intelligence for an Ageing Society became urgent to better reflect the multifactorial nature of aging process and the multidisciplinary eforts needed to face with it. Each paper was reviewed by members of the Program Committee of the Workshop, and based on their recommendations, 11 documents have been selected for presentation at the AIxAS 2023 workshop, among them 8 are published as regular papers, 2 as short ones. In addition, the workshop was enriched by the valuable participation of Marco Albertini as invited speaker. We sincerely thank all the members of the AIxAS Program Committee for their efort in the review process that was fundamental for maintaining the high scientific level of the workshop. We thank the AIxIA council, who trusted us to organize AIxAS 2023, and all the researchers of the AI community who supported this event by submitting their work and actively participated to the discussion.
Francesca Gasparini, Francesca Fracasso, and Frida Milella
• Stefania Bandini (LINTAR – DISCo, University of Milano-Bicocca, Milan, Italy) • Luigia Carlucci Aiello (Sapienza University of Rome, Rome, Italy) • Gabriella Cortellessa (National Research Council of Italy, Institute of Cognitive Sciences and Technologies, CNR-ISTC, Rome, Italy)
• Francesca Gasparini (MMSP-DISCo, University of Milano-Bicocca, Italy) • Francesca Fracasso (National Research Council of Italy, Institute of Cognitive Sciences and Technologies, CNR-ISTC, Rome, Italy) • Frida Milella (LINTAR – DISCo, University of Milano-Bicocca, Milan, Italy)
The AIxAS workshop chairs would like to thank all the Program Committee members for their reviewing and dissemination help: • Flavio Soares Correa Da Silvas (University of São Paulo, Brazil) • Riccardo De Benedictis (ISTC-CNR, Roma, Italy) • Alessandro Leone (IMM-CNR, Lecce, Italy) • Andrea Orlandini (ISTC-CNR, Roma, Italy) • Adnan Syed (University of Milano-Bicocca, Italy) • Aurora Saibene (MMSP-DISCo, University of Milano-Bicocca, Italy) • Silvia Corchs (University of Insubria, Italy) • Alessandra Grossi (MMSP-DISCo, University of Milano-Bicocca, Italy) • Nunzio Alberto Borghese (Università degli studi di Milano, Italy) • Stefano Ferilli (Università di Bari, Italy) • Amedeo Cesta (ISTC-CNR, Roma, Italy) • Rocco Oliveto (Università degli Studi del Molise, Italy) • Enhancing upper limb mobility through gamified tasks and Azure Kinect: a preliminary study in post-stroke subjects.
Claudia Ferraris, Gianluca Amprimo, Luca Vismara, Alessandro Mauro and Giuseppe Pettiti • Biomarkers for Mixed Dementia: a hard bone to bite? Preliminary analyses and promising results for a debated topic.
Andrea Campagner, Lorenzo Famiglini, Beatrice Arosio, Paolo Rossi, Giorgio Annoni and Federico Cabitza • Exploratory analysis of longitudinal data of patients with dementia through unsupervised techniques.
Patrizia Ribino, Claudia Di Napoli, Giovanni Paragliola, Luca Serino, Francesca Gasparini and Davide Chicco • Privacy-Preserving Federated Learning for In-home Monitoring of Elderly with Wearable Biometric Sensors.
Mario Bochicchio and Sileshi Nibret Zeleke • An Artificial Intelligence approach to predict multidimensional poverty of older people from unlabelled data Lorenzo Olearo, Fabio D’Adda, Enza Messina, Marco Cremaschi, Stefania Bandini and Francesca Gasparini • A computational framework for speech emotion recognition in case of multisource data.
Alessandra Grossi, Giorgio Fratti and Francesca Gasparini