First International Workshop on Hybrid Artificial Intelligence and Enterprise Modelling for Intelligent Information Systems

The combination of symbolic AI (based on logic and reasoning) and sub-symbolic AI (based on statistical methods) is an emerging research direction in Artificial Intelligence, which is denoted with the term Hybrid Artificial Intelligence, and holds the promise of creating powerful intelligent information systems (ISS) for various application domains.

However, creating ISS that benefit businesses is highly challenging. Stakeholders with different and complementary skillsets from business, the targeted domain, IT and AI must work together closely to achieve optimal results. The quick achievement of a common understanding among the various stakeholders is therefore crucial.

The first HybridAIMS international workshop, led by Dr. Emanuele Laurenzi and supported by Prof. Dr. Hans Friedrich Witschel (both FHNW School of Business) and Peter Haase (Metaphacts), looked at Enterprise Modelling as an approach that enhances communication and understanding among the various stakeholders, thus facilitating the human-in-the-loop in the development of IIS.

The workshop took place in conjunction with the renowned international conference CAiSE: 35th International Conference on Advanced Information Systems Engineering in Zaragoza, Spain, and featured inputs from industry and research experts. These covered various research and technological approaches, from the implementation of neuro-symbolic AI at Bosch to enriching enterprise architecture models with healthcare ontologies for machine-interpretability purposes. In addition to the three keynotes and six paper presentations, the final World Café session provided participants with the opportunity to discuss existing and future challenges in the field.

We would like to thank the organisers and contributors and look forward to future workshops and research activities.

Further Information

HybridAIMS website

Workshop proceedings (Springer Link)

Workshop abstract (PDF)