A Guidebook for Scoping Scenario Options in Cyber and Beyond Garvey, Bruce. creator author. aut http://id.loc.gov/vocabulary/relators/aut Svendsen, Adam D. M. author. aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) text sz 2024 1st ed. 2024. monographic eng

electronic

electronic resource

access XXXII, 340 p. 69 illus., 58 illus. in color. online resource. This book brings together a diverse range of findings on current and emerging business concerns when the authors were developing a series of 12 working Analytic Research Consortium (ARC) White Papers. It presents several, differently configured scenarios, drawing on cyber as an example; the use and further optimization of estimative/probabilistic language; communicating analytical insights and other findings concerning ‘(un)certainty’ to decision-maker end-users; and mitigating risk. It also evaluates in detail today’s rapidly evolving Gen-AI systems and technologies, e.g. those underlying OpenAI’s ChatGPT and Google’s Bard/Gemini. This includes their respective value concerning scenario development and other business-relevant methods, tools and techniques, e.g. ‘Red Teaming’. The topics discussed are assessed using the multi-methodologies of, firstly, ‘Intelligence Engineering’ (IE) and, secondly, ‘Strategic Options Analysis’ (SOA). The latter half of the book introduces an alternative scenario planning process, including use of new computer-software and AI tools. In addition to Gen-AI, we identify that the emerging discipline of Causal AI may work better for foresight and scenario activities. The book is a valuable read for a diverse readership from the public and private sectors, spanning government, the military, law enforcement, education, industry, commerce, retail, and enterprises of all sizes. Also, students at business schools and high-level decision-makers, including politicians, military commanders, and C-Suite leaders in various fields, will benefit from it. Generating Cyber Intelligence (CYBINT) scenarios & solutions to address uncertainty for decision-advantage: Using Intelligence Engineering & Strategic Options Analysis -- A Macro Cyber Scenario Case Study using Intelligence Engineering & Strategic Options Analysis Methods -- Examining the Landscape of Unauthorised Cyber Access (with reference to POSTnote #684) -- Intelligence Engineering-led set-up of generic Strategic Options Analysis Problem to Solution Spaces: Cyber example demonstration -- More than Semantics? Communication of (Un)certainty via ‘Estimative/Probabilistic Language’ -- Estimative/Probabilistic Language - Part II: Expanding the Range of Scenario Options -- Scoping ‘Digital Twins’ in intelligence & strategic foresight projects -- Generative-AI Pilot for Problem Spaces: Can ChatGPT help develop Scenarios? -- An Outline for an Interrogative/Prompt Library to help improve output quality from Generative-AI Datasets -- Prompt-engineering testing ChatGPT4 & Bard for assessing Generative-AI efficacy to support decision-making -- Can Generative-AI (ChatGPT and Bard) Be Used as Red Team Avatars in Developing Foresight Scenarios? -- Realising Foresight Intelligence (FORINT) - Advancing an Intelligence-derived Foresight Framework -- The Role of the Scenario and its Reassessment -- Advancing a New Methodological Process -- Process implications – Current software enhancements, including increasing levels of AI. by Bruce Garvey, Adam D. M. Svendsen. Operations research Artificial intelligence Knowledge management Business information services Technological innovations Production management Operations Research and Decision Theory Artificial Intelligence Knowledge Management IT in Business Innovation and Technology Management Operations Management T57.6-.97 9783031661150 https://doi.org/10.1007/978-3-031-66115-0 https://doi.org/10.1007/978-3-031-66115-0 241025 20251030113244.0 978-3-031-66115-0