mlsanityData to 7 Oct 2026

The Innovation Paradox: Concept Space Expansion with Diminishing Originality and the Promise of Creative AI

arXiv 2303.13300 ↗First posted 23 Mar 2023cs.SI cs.AIcited by 2

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Abstract (arXiv)

Innovation, typically spurred by reusing, recombining, and synthesizing existing concepts, is expected to result in an exponential growth of the concept space over time. However, our statistical analysis of TechNet, which is a comprehensive technology semantic network encompassing over four million concepts derived from patent texts, reveals a linear rather than exponential expansion of the overall technological concept space. Moreover, there is a notable decline in the originality of newly created concepts. These trends can be attributed to the constraints of human cognitive abilities to innovate beyond an ever-growing space of prior art, among other factors. Integrating creative artificial intelligence (CAI) into the innovation process holds the potential to overcome these limitations and alter the observed trends in the future.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 18 of its 72 references that are in the map. First posted on arXiv 23 Mar 2023.

Builds on

18 of 72 references.

References · 18

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,462
  3. 2022Generative Transformers for Design Concept Generationcited by 21
  4. 2021Engineering Knowledge Graph from Patent Databasecited by 18
  5. 2021Generative Pre-Trained Transformer for Design Concept Generation: An Explorationcited by 17
  6. 2021Natural Language Processing in-and-for Design Researchcited by 15
  7. 2019TechNet: Technology Semantic Network Based on Patent Datacited by 14
  8. 2022Biologically Inspired Design Concept Generation Using Generative Pre-Trained Transformerscited by 13
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  11. 2021Enhancing user creativity: Semantic measures for idea generationcited by 8
  12. 2021Patent Data for Engineering Design: A Critical Review and Future Directionscited by 5
6 more
  1. 2022Generative Design Ideation: A Natural Language Generation Approachcited by 5
  2. 2022Design Representation as Semantic Networkscited by 4
  3. 2018Creative Exploration Using Topic Based Bisociative Networkscited by 3
  4. 2020Technological improvement rate estimates for all technologies: Use of patent data and an extended domain descriptioncited by 3
  5. 2021Technology Fitness Landscape for Design Innovation: A Deep Neural Embedding Approach Based on Patent Datacited by 1
  6. 2022Generative Pre-Trained Transformers for Biologically Inspired Designcited by 1

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Cited by year

Citing papers per year: 2024: 1; 2025: 1.

2 papers.

  1. 2024Large Language Model for Patent Concept Generationcited by 4
  2. 2025The Variance Paradox: How AI Reduces Diversity but Increases Noveltycited by 1