Artificial Intelligence (AI) is transforming humans’ activities through continuous collaboration in domains where AI-supported decisions affect humans and societies. In this context, the focus should shift toward the development of Symbiotic AI (SAI) systems that support humans rather than replace them. This contribution presents a set of Success Criteria (SC) that can be used to evaluate such SAI systems by determining whether the requirements of symbiosis are met. The paper also includes a preliminary validation of the criteria through a pilot user study.

The rapid spread of Large Language Models (LLMs) is influencing many contexts, shaping the way in which humans conduct activities. LLMs can represent a promising instrument in the medical field to support physicians in creating therapy. This contribution aims at presenting the employment of LLMs for creating exercises addressed to speech therapies investigating whether these can be an effective tool to support physician in this activity. This contribution presents the experimental setup of tests conducted with LLMs along with an overview of the obtained results showing the potential and limitations of this technology.

Eating disorders are disturbances in people’s eating behaviours that can influence their social and private lives, with consequences related to mental and physical health. Therefore, they must be timely and appropriately treated by professionals and, in this context, the employment of technology can improve the efficiency of treatments allowing remote assistance, continuous monitor, and less stress than the traditional medical approach.

Artificial Intelligence (AI) is significantly impacting foreseeing fields offering a better-automated decision making process and autonomous systems. Therefore, it is important to design high-quality AI systems that focus on the users’ priorities and avoid potential unethical and undesired behaviours. In the current scenario, Human-Computer Interaction (HCI) and AI are not separate fields but they contaminate each other and, consequently, the symbiosis between humans and AI system is fostered. Ensuring that AI development benefits humans, while providing an high-level automation, remains a primary concern. For this reason, the human-centered design approach should be adopted to create systems that being trustworthy, safe, reliable, and governance compliant are able to enhance the user’s cognitive abilities and protect they from potential risks. In this context, it is fundamental to identify guidelines to follow while designing high-quality Symbiotic AI (SAI) systems and metrics for their appropriate evaluation. Assessing the empirical validity of the proposed solution is of crucial importance and the planning and execution of a user study is one of the main aspects of this work. The research project concerns the design of SAI systems, more specifically the definition of best practices and metrics to adopt while creating and evaluating these systems. This contribution presents the preliminary results obtained during the initial part of the research. The main opportunities and challenges in this new research field are also discussed.