The construction of computational causal models for complex systems has typically been completed manually by domain experts and is a time-consuming, cumbersome process. Operational design is a method of structured team discourse used by military planners for rapidly envisioning complex systems and relationships; however, the products are typically static diagrams on whiteboards or slides. DARPAs Causal Exploration program seeks to leverage artificial intelligence (AI) assistance and causal analytics to enable rapid system modeling and analysis. We introduce Causeworks, an application in which operators “sketch” complex systems, leverage AI tools and expert knowledge to transform the sketches into computational causal models, and then apply analytics to understand how to influence the system. We walk through human–machine collaborative model building using Causeworks and discuss feedback and lessons learned about how to flexibly apply causal modeling and thinking for expert planners that are novice modelers.
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This work was supported by the Defense Advanced Research Projects Agency (DARPA) under Contract Number FA8650-17-C-7720. The views, opinions, and findings contained in this report are those of the authors and should not be construed as an official Department of Defense position, policy, or decision. This work has been approved for Public Release, Distribution Unlimited. The authors wish to thank all Causal Exploration collaborators for their contributions and specially thank Program Managers Steve Jameson and Joshua Elliot for their inspiring vision and leadership.
This work was supported by the Defense Advanced Research Projects Agency (DARPA) under Contract Number FA8650-17-C-7720. The views, opinions, and findings contained in this report are those of the authors and should not be construed as an official Department of Defense position, policy, or decision. This work has been approved for public release, distribution unlimited.
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This article is part of the topical collection “Computer Vision, Imaging and Computer Graphics Theory and Applications” guest edited by Jose Braz, A. Augusto Sousa, Alexis Paljic, Christophe Hurter and Giovanni Maria Farinella.
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Kapler, T., Gray, D., Vasquez, H. et al. Causeworks: a Mixed Initiative Framework for Causal Modeling. SN COMPUT. SCI. 4, 54 (2023). https://doi.org/10.1007/s42979-022-01452-y