From Loop to Partnership: A Framework for Understanding the Evolving Paradigms of Human-AI Collaboration

From Loop to Partnership: A Framework for Understanding the Evolving Paradigms of Human-AI Collaboration | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 29 August 2025 V1 Latest version Share on From Loop to Partnership: A Framework for Understanding the Evolving Paradigms of Human-AI Collaboration Authors : Sagar Patil 0009-0003-7494-4063 [email protected] , Suneel Sharma , and Mehregan Mahdavi Authors Info & Affiliations https://doi.org/10.22541/au.175647875.57157328/v1 144 views 65 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract The term ‘Human-in-the-Loop’ (HIL), once a clarifying concept for AI systems reliant on human input, now obscures more than it reveals. Its monolithic application to a vast and expanding range of human-AI interactions has led to a conceptual fragmentation that impedes scientific progress and responsible systems’ development. This research confronts this ambiguity by proposing a new, tripartite framework that offers a more granular and robust typology for understanding human-AI collaboration. This framework is the result of a systematic literature review designed to synthesize a fragmented, interdisciplinary body of research. We first establish a foundational dichotomy based on the locus of control and introduce a tripartite framework consisting of: HIL (AI-led), where AI is autonomous, and humans provide input for improvement (e.g., data labeling for self-driving cars); AI2L (Human-led), where humans are in control, and AI augments their capabilities (e.g., AI-powered diagnostic tools for doctors); And Hybrid Intelligence (HI), a more advanced paradigm focused on symbiotic, co-creative partnerships between humans and AI, often enabled by generative AI (e.g., generative design, collaborative software engineering). It demonstrates that the choice of the human-AI collaboration paradigm is strongly influenced by the domain’s primary objectives: efficiency for HIL, accountability for AI2L, and creativity/innovation for HI. It also establishes that ethical considerations must move beyond simple human oversight (”human in the loop”) to a more robust and systemic approach called ”participatory governance,” which involves diverse stakeholders throughout the AI’s lifecycle to ensure fairness and accountability. This resolves a central paradox in human-AI studies, re-conceptualizes the landscape of collaboration, and establishes a new foundation for the design and governance of socio-technical systems. Supplementary Material File (from loop to partnership_ a framework for understanding the evolving paradigms of human-ai collaboration-9(1).docx) Download 5.95 MB Information & Authors Information Version history V1 Version 1 29 August 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords ai-in-the-loop (ai2l) human-centered ai human-in-the-loop (hil) human–ai collaboration human–computer interaction (hci) hybrid intelligence (hi) Authors Affiliations Sagar Patil 0009-0003-7494-4063 [email protected] SP Jain School of Global Management - Mumbai Campus View all articles by this author Suneel Sharma SP Jain School of Global Management - Mumbai Campus View all articles by this author Mehregan Mahdavi SP Jain School of Global Management - Mumbai Campus View all articles by this author Metrics & Citations Metrics Article Usage 144 views 65 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Sagar Patil, Suneel Sharma, Mehregan Mahdavi. From Loop to Partnership: A Framework for Understanding the Evolving Paradigms of Human-AI Collaboration. Authorea . 29 August 2025. DOI: https://doi.org/10.22541/au.175647875.57157328/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. 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