Artificial intelligence, human intelligence and hybrid intelligence based on mutual augmentation

There is little consensus on what artificial intelligence (AI) systems may or may not embrace. Although this may point to multiplicity of interpretations and backgrounds, a lack of conceptual clarity could thwart the development of common ground around the concept among researchers, practitioners an...

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Bibliographic Details
Published in:Big data & society Vol. 9; no. 2
Main Authors: Jarrahi, Mohammad Hossein, Lutz, Christoph, Newlands, Gemma
Format: Journal Article
Language:English
Published: London, England SAGE Publications 01.07.2022
Sage Publications Ltd
SAGE Publishing
Subjects:
Artificial intelligence
Augmentation
Augmented reality
Common ground
Humans
Hybrid systems
Systems
Tacit knowledge
human intelligence
hybrid intelligence
human-augmented AI
human–AI interaction
augmented human intelligence
Artificial intelligence
ISSN:2053-9517, 2053-9517
Online Access:Get full text
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Summary:There is little consensus on what artificial intelligence (AI) systems may or may not embrace. Although this may point to multiplicity of interpretations and backgrounds, a lack of conceptual clarity could thwart the development of common ground around the concept among researchers, practitioners and users of AI and pave the way for misinterpretation and abuse of the concept. This article argues that one of the effective ways to delineate the concept of AI is to compare and contrast it with human intelligence. In doing so, the article broaches the unique capabilities of humans and AI in relation to one another (human and machine tacit knowledge), as well as two types of AI systems: one that goes beyond human intelligence and one that is necessarily and inherently tied to it. It finally highlights how humans and AI can augment their capabilities and intelligence through synergistic human–AI interactions (i.e., human-augmented AI and augmented human intelligence), resulting in hybrid intelligence, and concludes with a future-looking research agenda.
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ISSN:2053-9517
2053-9517
DOI:10.1177/20539517221142824