Foresight and governance of complexity in the era of AI

Abstract Today’s challenges address a multitude of interconnected agents, resulting in complex systems whose evolution is difficult to predict. Policy makers are asking scientists to identify future scenarios and provide different solutions. The European Union has recognised in foresight a strategic process to support decisions. We show that foresight, governance and lobby are intertwined, and we assign an increased relevance to foresight when dealing with the uncertainty of the evolution of the socio-economic systems. To tackle the complexity in governance and decision processes, we describe an operational methodology named CLEVER to facilitate the problem setting and identification of the most appropriate mode of governance. It can be also adopted to analyse scenarios and their dynamics. CLEVER is based on a logical scheme, thus not dependent on the rapid evolution of tools empowering the information retrieval and future orienteering. We also reflect on the role of AI as an emergent technology, already having an impact on many of the involved processes.