mlsanityData to 7 Oct 2026

Co-evolutionary hybrid intelligence

arXiv 2112.04751 ↗First posted 9 Dec 2021cs.AIcited by 4

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Abstract (arXiv)

Artificial intelligence is one of the drivers of modern technological development. The current approach to the development of intelligent systems is data-centric. It has several limitations: it is fundamentally impossible to collect data for modeling complex objects and processes; training neural networks requires huge computational and energy resources; solutions are not explainable. The article discusses an alternative approach to the development of artificial intelligence systems based on human-machine hybridization and their co-evolution.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 3 of its 11 references that are in the map. First posted on arXiv 9 Dec 2021.

Builds on

3 of 11 references.

References · 3

  1. 2019Understanding artificial intelligence ethics and safetycited by 68
  2. 2018Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolutioncited by 66
  3. 2019There is no Artificial General Intelligencecited by 2

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Cited by year

Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 1.

4 papers.

  1. 2022Cognitive Architecture for Co-Evolutionary Hybrid Intelligencecited by 3
  2. 2023AI in HCI Design and User Experiencecited by 0
  3. 2024CrowdTransfer: Enabling Crowd Knowledge Transfer in AIoT Communitycited by 0
  4. 2025Mapping Human-Agent Co-Learning and Co-Adaptation: A Scoping Reviewcited by 0