CeSANI aims to foster research in artificial intelligence (AI) and natural intelligence, addressing the relationship between AI and natural intelligence along various avenues:

• The potential of AI to understand, support, or enhance tasks that typically require natural intelligence, such as making decisions in complex situations in a way that promotes the wellbeing of individuals and societies. This understanding is inherently interdisciplinary, including a deep knowledge of the domains of application where decisions take place. It includes predicting clinical outcomes, making treatment decisions and anticipating responses to them, analysing and interpreting audiovisual data, generating and editing audiovisual content, generating virtual digital environments, creating and interpreting cultural expressions, performing sentiment analysis, or generating and summarising natural language.

• How AI development promotes or undermines human autonomy and agency, and the interplay with cognitive biases or with the creation of new forms of inequality. These ethical and social implications determine the technical properties of systems, such as the need for robustness, transparency, and auditability, as well as a nuanced understanding of its limitations (by, for instance, oversimplifying or misrepresenting complex phenomena). Engaging diverse stakeholders can lead to AI systems that are more responsive to society's needs and values.

• Drawing inspiration from the way the human brain processes information and makes decisions, to devise computational models and algorithms that integrate psychological or sociological insights to replicate these processes.

• Understanding the cognitive and neural mechanisms underlying natural intelligence. This involves the development of computational models and algorithms that aim at replicating or explaining natural intelligence, as well as analysing data to model complex cognitive processes such as memory and attention. The collection of physiological and behavioural data, as well as immersive environments to study human behaviour in realistic yet controlled settings, provide valuable insights that are difficult to obtain from siloed research.

• Designing the infrastructure that provides the means for artificial systems to interact with natural intelligence and the physical world. Research on communication networks is critical for the development of new technologies that enable global connectivity and collaboration. This research raises issues such as robustness, resilience, efficiency or sustainability, creating opportunities for innovation directed towards the common good in areas such as smart grids, agriculture, the financial system, entertainment, or healthcare. Advancing the state of the art in web science, information retrieval, and social computing, also takes shape in CeSANI with a particular focus on embedding values (such as fairness) in technology.