Enhancing Search and Discovery: The Synergistic Collaboration Between Humans and AI

This article explores the synergistic collaboration between humans and artificial intelligence in search and discovery across multiple domains. It examines the theoretical frameworks that underpin effective human-AI partnerships, highlighting how the complementary strengths of human intuition and AI computational power create systems that outperform either of the two working independently. The article systematically analyzes applications in healthcare, where collaborative frameworks enhance diagnosis, drug discovery, and personalized medicine. It further investigates manufacturing implementations, demonstrating significant improvements in predictive maintenance, supply chain optimization, and process innovation. The article concludes by identifying key technical challenges for future development, including explainability, interface design, domain adaptation, and ethical governance, while presenting emerging solutions that maximize the potential of human-AI collaboration in advancing scientific discovery and organizational performance.

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Publication Details

Journal
European Journal of Computer Science and Information Technology
Published
2025-03-15
DOI
https://doi.org/10.37745/ejcsit.2013/vol13n10112123
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28
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article

Enhancing Search and Discovery: The Synergistic Collaboration Between Humans and AI

Neena Singh
1 citations
European Journal of Computer Science and Information Technology
Big Data and Business Intelligence
2.28
article

Enhancing Search and Discovery: The Synergistic Collaboration Between Humans and AI

Neena Singh
article en
1 citations

Abstract

This article explores the synergistic collaboration between humans and artificial intelligence in search and discovery across multiple domains. It examines the theoretical frameworks that underpin effective human-AI partnerships, highlighting how the complementary strengths of human intuition and AI computational power create systems that outperform either of the two working independently. The article systematically analyzes applications in healthcare, where collaborative frameworks enhance diagnosis, drug discovery, and personalized medicine. It further investigates manufacturing implementations, demonstrating significant improvements in predictive maintenance, supply chain optimization, and process innovation. The article concludes by identifying key technical challenges for future development, including explainability, interface design, domain adaptation, and ethical governance, while presenting emerging solutions that maximize the potential of human-AI collaboration in advancing scientific discovery and organizational performance.

European Journal of Computer Science and Information TechnologyVol. 13(10)
George Mason University (US)
Openalex Percentile: Top 13%
Big Data and Business Intelligence
2.28
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Enhancing Search and Discovery: The Synergistic Collaboration Between Humans and AI — Neena Singh · European Journal of Computer Science and Information Technology (2025) | TGRS Research Map | TGRS