A Systematic Framework for Breakthrough Thinking, Original Innovation, and Real-World Value Creation
« ENGINEERING CREATIVITY WITH AI » est un livre de Faramarz Kowsari dans le domaine intelligence artificielle. Cette page de découverte en français organise les métadonnées publiques du livre afin de rendre ses thèmes, son public, sa langue réelle de publication et ses accès officiels plus faciles à trouver.
Les métadonnées publiques rattachent ce titre à l'intelligence artificielle, aux outils d'IA modernes ou aux flux de travail fondés sur les prompts.
Langue de publication: anglais. Cette page est une orientation en français. Le livre lui-même est publié en anglais ; le titre, l'aperçu et les options d'achat sur Google Books correspondent à cette édition.
« ENGINEERING CREATIVITY WITH AI » est un livre de Faramarz Kowsari dans le domaine intelligence artificielle. Cette page de découverte en français organise les métadonnées publiques du livre afin de rendre ses thèmes, son public, sa langue réelle de publication et ses accès officiels plus faciles à trouver.
Les métadonnées publiques rattachent ce titre à l'intelligence artificielle, aux outils d'IA modernes ou aux flux de travail fondés sur les prompts.
Thèmes mis en avant
AI-assisted creativityCreativity engineeringHuman-AI creative partnershipCreative cognitionGenerative AI and noveltyAI-CE9 frameworkOpportunity discoverySolution-space mappingProblem reframingDivergent idea generationCross-domain synthesisCreative candidate evaluationMinimum viable prototypesOriginality validation
Description publique originale du livre
anglais
ENGINEERING CREATIVITY WITH AI treats creativity as an engineered search-and-validation process rather than a mysterious gift or a one-prompt trick. The book begins by separating novelty from usefulness and by asking what generative AI can actually contribute to creative work. Early chapters examine the cognitive architecture of creative thinking, the strengths and limits of generative models, the division of responsibility between human judgment and machine generation, and the habits required to escape entrenched patterns without mistaking novelty for evidence.
At the center of the book is AI-CE9, a proposed nine-stage creativity-engineering workflow. The sequence moves from discovering the real opportunity and mapping the existing solution space to reframing the problem, generating functionally diverse candidates, transferring ideas across domains, evaluating alternatives, building a minimum viable prototype, validating originality and real-world value, and iterating from evidence. AI-CE9 is presented as an integrative method to be tested, not as a scientifically proven universal law or a guarantee of breakthrough innovation.
The middle chapters expand the creative toolbox beyond ordinary brainstorming. TRIZ, SCAMPER, Systematic Inventive Thinking, morphological analysis, analogical reasoning, inversion, paradox, systems thinking and transformational creativity are used to manipulate problem structure deliberately. These methods are connected to prompt engineering, controlled divergence, multi-agent creative collaboration and constructive dissent so that AI output becomes a structured exploration space rather than a stream of plausible but unexamined suggestions.
Research-grounded creativity receives its own engineering treatment. The book explains how…
À qui s'adresse le livre ?
Le public visé est fondé sur la description publique du livre. Pour les lecteurs francophones, il faut noter que l'édition disponible est publiée en anglais.
For researchers, inventors, software engineers, designers, artists, educators, entrepreneurs, students and curious professionals who want a structured way to use AI for original thinking, prototyping and innovation while preserving human judgment, evidence standards, intellectual-property awareness and responsible decision-making.
Objectifs d'apprentissage publiés
anglais
Distinguish novelty, usefulness, validation and commercial success instead of treating them as interchangeable measures of creativity.
Use generative AI as a search and prototyping instrument while keeping human judgment responsible for evidence, ethics and final decisions.
Apply the nine stages of AI-CE9 from opportunity discovery through iteration without presenting the framework as a guaranteed recipe for invention.
Map an existing solution space before generating alternatives so an unfamiliar idea is not automatically mistaken for an original one.
Reframe problems and constraints deliberately to expose hidden assumptions and new solution directions.
Generate functionally diverse candidates through controlled divergence rather than accepting near-duplicate model outputs.
Use cross-domain analogy and transformation to transfer useful structures without copying surface features.
Evaluate candidate ideas with explicit criteria before investing in prototyping or commercialization.