Exploring the Convergence of AI, Machine Learning, and Deep Learning: A Canadian Perspective Through Citation Networks

Fatemeh Naghavi Olya, Andrea Schiffauerova and Ashkan Ebadi ()
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Fatemeh Naghavi Olya: Concordia University, CIISE
Andrea Schiffauerova: Concordia University, CIISE
Ashkan Ebadi: Concordia University, CIISE

A chapter in Technology Management for Intelligent, Open and Responsible Organizations and Ecosystems, 2026, pp 330-338 from Springer

Abstract: Abstract The convergence of ideas, methods, and discoveries from various scientific disciplines and technological fields has led to the emergence of new technologies. This study analyses the convergence of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) with other technologies from 2000 to 2023, using published papers and citations. We explore how AI’s rapid development has fostered new technical subfields, focusing on Canada’s AI ecosystem. By examining the emergence, growth, and decline of these converged technologies, we aim to identify key contributing factors to highlight trends in technological advancement, inform strategic investments, and predict future innovations within Canada’s dynamic AI landscape.

Keywords: Knowledge Convergence; Artificial Intelligence; Machine Learning; Deep Learning; Canada (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-032-23282-3_40

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DOI: 10.1007/978-3-032-23282-3_40

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