The Hybrid Intelligence Manifesto:A Multi-Level Socio-Technical Framework for Keeping Human Judgement Economically Valuable
Year: 2026
Type: preprint
Abstract: The rapid emergence of increasingly agentic AI systems poses a structural challenge to the future of meaningful human work. As AI expands from task automation to autonomous goal pursuit, preserving human agency can no longer rely on ethical guidelines alone. This manifesto advances Hybrid Intelligence (HI) as a multi-level socio-technical transformation model aimed at keeping human judgment economically indispensable, by developing human–AI workflows that outperform pure automation across a broad range of applications. Headline results in which AI alone beats AI-assisted professionals test automation against unscaffolded oversight rather than against hybrid intelligence; the decisive comparison has yet to be run, and this collection builds the apparatus to run it. Drawing on more than fifty interdisciplinary roundtables and two foresight workshops, we, the HI Manifesto consortium of major European HI research centers and 60 scholars and AI practitioners, articulate an urgent mission: to design interfaces, governance frameworks, institutional policies, and market mechanisms such that human value creation scales through competitive human–AI collaboration rather than displacement. This does not require humans to approve every AI output; it requires that human contextual judgment be structurally embedded in value-creating workflows, irreducible to symbolic oversight, and that such workflows constitute the majority rather than a fringe of the future economy. We reinterpret complementarity as a dynamic frontier between prediction and judgment that shifts as contextual knowledge becomes machine-operational and that must be actively managed through deliberate workflow design. On this foundation we contribute: (1) a durable, knowledge- structure-grounded definition of complementarity with operational classification tests; (2) prescriptive multi-level HI definitions distilled from ten consensus criteria and constructed as exclusion instruments against HI-washing, with qualified terms spanning interface, practice, organization, and society; (3) a six- level interface classification from autonomous AI to collaborative HI; (4) a five-dimensional use-case maturity matrix applied to iconic and partner cases, revealing distinct HI business-model patterns; and (5) a foresight analysis of four AI futures identifying the transition's drivers and its valley of death. Four companion papers and a cross-cutting interaction framework (FERC) operationalize the interface, organizational, macroeconomic, and educational levels, including first field results showing the framework is buildable by ordinary commercial teams. We conjecture that granular hybrid workflows can reduce dependence on frontier-scale compute, with competitiveness, sustainability, and sovereignty as the dividend, and we close by extending the program into a constellation of Hybrid Intelligence Missions with concrete institutional calls to action. HI thus emerges not as a tool choice but as a syste
Authors: Friis Sherson, Jacob, Rafner, Janet, Bang, Jesper Broberg, Berditchevskaia, Aleksandra, Bjerring, Jens Christian, Chompunuch, Sudapa, Daga, Enrico, Dellermann, Dominik, Domanti, Umberto, Emruli, Blerim, von Harmelen, Frank, Gonzalez, Maceo, Gordon, Adam, Green, Adam, Hansen, Rigmor Lyck, Holm, Anna B., Jonker, Catholijn, Järvelä, Sanna, Kenett, Yoed N., Kjeldsen, Frederik Brosbøl, Knudsen, Mette P., Largacha-Martinez, Carlos, Lebuda, Izabela, Linnet, Rasmus, Lodefalk, Magnus, Mao, Yaoli, Marler, Janet, Meyer-Vitali, André, Natalis, Chiara, Olsen, Morten Røndal, Rahimi, Seyedahmad, Reicherts, Leon, Reiter-Palmon, Roni, Sauermann, Henry, Sent, Danielle, Schmid, Thomas, Söllner, Matthias, Elpelt, Jonas, Tan, Stephanie, Thylkjær, Casper, Tiddi, Ilaria, Tudoran, Ana Alina, Wagner, Marcus, Bozorgtabar, Behzad, Catalan, Carlos Rafael, Kajtazi, Miranda, Norkin, Svetlana, Gkoumas, Christos, Vistisen, Peter, Staegemann, Daniel, Wiewiura, Joachim, Filipova, Mariana, Lindström, Adam Dahlgren, Ivcevic, Zorana, on Felten, Nick v, Zhang, Zelun Tony, Tankelevitcha, Lev, Vinchon, Florent, Szöllösi, Bianka, Molina-Abril, Ginés
Institutions: University of Southern Denmark, Nesta, Aarhus University, Bangkok University, Samsung (South Korea), Lund University, The Open University, Yale University, Georgetown University, University of Oulu, Technion – Israel Institute of Technology, University of Wrocław, Örebro University, University at Albany, State University of New York, Technical University of Munich, Tilburg University, Frankfurt Institute for Advanced Studies, Eindhoven University of Technology, University of St.Gallen, Georgia Institute of Technology, University of Nebraska at Omaha, European School of Management and Technology, Free University of Bozen-Bolzano, German Research Centre for Artificial Intelligence, Martin Luther University Halle-Wittenberg, University of Kassel, Vrije Universiteit Amsterdam, Delft University of Technology, University of Augsburg, Goethe University Frankfurt, Université Paris Cité, Université Gustave Eiffel, Laboratoire de Psychologie et d’Ergonomie Appliquées
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7202007207