Hybrid Intelligence Springerlink

Bonisiwe Shabane

-Nov 29, 2025, 8:32 PM

This chapter offers a comprehensive overview of hybrid intelligence, through which humans collaborate with artificial intelligence (AI) systems to enhance human and AI capabilities while ensuring that human values, needs, and authority remain central. In line with the principles of Human-Centered AI (HCAI), hybrid intelligence leverages the complementary strengths of humans and AI to create systems that augment, rather than replace, human decision-making and creativity. The chapter discusses how hybrid intelligence prioritizes human oversight, controllability, authority, and ethical considerations, ensuring that AI serves to enhance human well-being and aligns with societal values. It also addresses recent technological advancements, including foundation models, which have highlighted the importance of hybrid intelligence in fields such as healthcare, decision support, and innovation. Alongside these developments, the chapter emphasizes critical ethical and social challenges, such as fairness, accountability, trust, and privacy, within an HCAI framework. The chapter concludes by highlighting future research directions that integrate technical, social, and ethical perspectives to create sustainable, human-centered hybrid intelligence systems that prioritize human agency oversight as well as ethical design.

This is a preview of subscription content, log in via an institution to check access. Abhivardhan. (2025). Data Governance. In W. Xu (Ed.), Handbook of Human-Centered Artificial Intelligence (pp.

1–61). Springer. Allen, R. T., & Choudhury, P. (2022). Algorithm-augmented work and domain experience: The countervailing forces of ability and aversion.

Organization Science, 33(1), 149–169. https://doi.org/10.1287/orsc.2021.1554 Almatrafi, O., Johri, A., & Lee, H. (2024). A systematic review of AI Literacy conceptualization, constructs, and implementation and assessment efforts (2019–2023). Computers and Education Open, 6, 100173.

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 495))

Included in the following conference series: The purpose—Hybrid Intelligence is a cooperative collaboration between Human and Artificial Intelligence in solving intelligence tasks. The concept of Hybrid Intelligence originates from the ideas of William Ross Ashby, Joseph Carl Robnett Licklider, and Douglas Carl Engelbart. Fuzzy set theory, introduced by Lofti Zadeh, is a natural tool for describing and modelling Hybrid Intelligence. Fundamental problems of Hybrid Intelligence—modelling human perception and operating with perception-based information have been discussed in the report. Two application scenarios—personalization of human interaction with the digital world and evaluation and monitoring of complex processes have been discussed and illustrated, too.

Design/methodology/approach—The results are based on system analysis, fuzzy logic, some mathematical and psychology theories, and facts. Findings—Hybrid Intelligence is a pragmatic aspect of intelligence technologies, and this concept could reply to the crisis of modern Artificial Intelligence. Originality/value—Hybrid Intelligence is a new formal model which could be a theoretical base for the implementation of the concepts like “automation of knowledge work” (McKinney), “augmenting human performance” (NSF), “human–machine symbiosis” (DARPA), etc., which... Research/Practical/Social/Environment implications—Hybrid Intelligence can help people comfortable and effectively interact with the digital world. It can be a base for developing systems for evaluating and monitoring complex societal and environmental processes for their better understanding, management, and optimization. Research limitations—The Hybrid Intelligence approach can augment a regular human performance in solving routine intelligence tasks but cannot substitute a genius.

This is a preview of subscription content, log in via an institution to check access. Tax calculation will be finalised at checkout A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions. This is a preview of subscription content, log in via an institution to check access. Price excludes VAT (USA) Tax calculation will be finalised during checkout.

For further work on this topic see Dellermann et al. (2019). https://deepmind.com (accessed 19 Mar 2019). https://ai.google/research/teams/brain/pair (accessed 19 Mar 2019).

People Also Search

This Chapter Offers A Comprehensive Overview Of Hybrid Intelligence, Through

This Is A Preview Of Subscription Content, Log In Via