Subthemes for HI

We provide three subthemes to inspire participants with innovative research ideas for Hybrid Intelligence (HI).

However, we wholeheartedly welcome different themes and approaches as well. As long as they contribute to advancing the research and understanding of HI, we encourage and support any creative and groundbreaking ideas that participants might bring forward. Our goal is to foster a diverse and rich exchange of perspectives that can drive the field of hybrid intelligence forward in new and exciting directions.

1. Cognition Understanding in human and AI

The first area involves an in-depth examination of cognitive learning processes, encompassing both human and AI systems.

This exploration seeks to identify foundational models, highlight differences, and uncover commonalities between the two types of cognitive systems, thereby enriching our understanding of how both human and artificial intelligences learn and evolve.

2. Behavioural Engagement and Interactions in HI

The second area addresses the recognition and understanding of behaviors, particularly in the context of engagement and interaction within social, working, healthcare and educational environments.

This involves studying how both humans and AI systems interpret and respond to social cues, aiming to enhance the effectiveness of their interactions.

3. Emotion and Motivation to HI

The third area focuses on the roles of emotion and motivation in influencing behavior and decision-making processes in both humans and AI.

This exploration is crucial for developing more intuitive and responsive AI systems that can better understand and adapt to human emotions and motivational states.

Topics for HI

The potential topics for study within hybrid intelligence are broad and include several critical applications designed to improve human capabilities and societal conditions.

1. Hybrid Intelligence for Well-being

Tailoring health interventions, monitoring and promoting overall health and well-being to enhance quality of life.

2. Hybrid Intelligence in Learning and Teaching

Developing and promoting key competencies, such as self-regulation and socio-emotional skills, within the contexts of learning and teaching through hybrid intelligence.

3. Hybrid Intelligence for emotional interpretation

Improving responses and understanding of emotions from both human and AI sides through collaborative human-AI efforts.