This special session seeks to foster interdisciplinary research and to specifically address the integration of human-centric adaptive computational intelligence (CI) into business processes and decision-making. Dynamic business environments require adaptive systems that can evolve over time while remaining grounded in human logic (reasoning). Such systems should facilitate human participation and extraction of knowledge in an explainable and understandable manner. Emerging computational intelligence approaches should allow interactive machine learning in a collaboration with users able to interact with their data by logic aggregation requirements expressed linguistically.

The main goal is to investigate how human-centric CI techniques can be leveraged to ensure more transparent and reliable CI systems. We invite contributions that explore how these techniques can serve as the driver for adaptivity, allow users to steer the evolution of the model through linguistic requirements and qualitative feedback, adapt their parameters and learn from data, include interpretable and explainable models, complement automated business processes, ensure the resulting AI agents are trustworthy and aligned with expert knowledge, etc.