A Systematic Framework for Breakthrough Thinking, Original Innovation, and Real-World Value Creation
“ENGINEERING CREATIVITY WITH AI” é um livro de Faramarz Kowsari na área de inteligência artificial. Esta página de descoberta em português do Brasil organiza os metadados públicos para tornar mais fáceis de encontrar os temas, o público, o idioma real de publicação e os caminhos oficiais de leitura ou compra.
Os metadados públicos situam este título em inteligência artificial, ferramentas modernas de IA ou fluxos de trabalho baseados em prompts.
Idioma de publicação: inglês. Esta é uma página de orientação em português do Brasil. O livro é publicado em inglês; título, prévia e opções de compra no Google Books correspondem a essa edição.
“ENGINEERING CREATIVITY WITH AI” é um livro de Faramarz Kowsari na área de inteligência artificial. Esta página de descoberta em português do Brasil organiza os metadados públicos para tornar mais fáceis de encontrar os temas, o público, o idioma real de publicação e os caminhos oficiais de leitura ou compra.
Os metadados públicos situam este título em inteligência artificial, ferramentas modernas de IA ou fluxos de trabalho baseados em prompts.
Temas em destaque
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
Descrição pública original do livro
inglês
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…
Para quem é este livro?
O público-alvo é baseado na descrição pública do livro. Para leitores brasileiros, é importante observar que a edição disponível está publicada em inglês.
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.
Objetivos de aprendizagem publicados
inglês
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.