mlsanityData to 14 Oct 2026

Revisiting Citizen Science Through the Lens of Hybrid Intelligence

arXiv 2104.14961 ↗First posted 30 Apr 2021cs.HC cs.AI cs.CYcited by 2

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Abstract (arXiv)

Artificial Intelligence (AI) can augment and sometimes even replace human cognition. Inspired by efforts to value human agency alongside productivity, we discuss the benefits of solving Citizen Science (CS) tasks with Hybrid Intelligence (HI), a synergetic mixture of human and artificial intelligence. Currently there is no clear framework or methodology on how to create such an effective mixture. Due to the unique participant-centered set of values and the abundance of tasks drawing upon both human common sense and complex 21st century skills, we believe that the field of CS offers an invaluable testbed for the development of HI and human-centered AI of the 21st century, while benefiting CS as well. In order to investigate this potential, we first relate CS to adjacent computational disciplines. Then, we demonstrate that CS projects can be grouped according to their potential for HI-enhancement by examining two key dimensions: the level of digitization and the amount of knowledge or experience required for participation. Finally, we propose a framework for types of human-AI interaction in CS based on established criteria of HI. This "HI lens" provides the CS community with an overview of several ways to utilize the combination of AI and human intelligence in their projects. It also allows the AI community to gain ideas on how developing AI in CS projects can further their own field.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 11 of its 108 references that are in the map. First posted on arXiv 30 Apr 2021.

Builds on

11 of 108 references.

References · 11

  1. 2017Deep reinforcement learning from human preferencescited by 3,912
  2. 2018Deep Learning: A Critical Appraisalcited by 217
  3. 2020The Next Decade in AI: Four Steps Towards Robust Artificial Intelligencecited by 195
  4. 2020Learning to Complement Humanscited by 124
  5. 2018Discovering physical concepts with neural networkscited by 117
  6. 2018Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failurecited by 49
  7. 2019Galaxy Zoo: Probabilistic Morphology through Bayesian CNNs and Active Learningcited by 22
  8. 2020Assessing Game Balance with AlphaZero: Exploring Alternative Rule Sets in Chesscited by 15
  9. 2020Conceptualization and Framework of Hybrid Intelligence Systemscited by 3
  10. 2020Human computation requires and enables a new approach to ethical reviewcited by 2
  11. 2017Remote optimization of an ultra-cold atoms experiment by experts and citizen scientistscited by 1

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