ABSTRACT. With growing evidence of big data-driven algorithmic governance in sustainable smart manufacturing, there is an essential demand for comprehending robotic process and cognitive automation technologies. In this research, prior findings were cumulated indicating that artificial intelligence integrates cutting-edge performance for automating cognitive work. We carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout January and April 2021, with search terms including “cognitive automation tools and technologies,” “cognitive automation algorithms,” “cognitive robotic systems,” and “artificial cognitive control systems.” As we analyzed research published between 2011 and 2021, only 214 papers met the eligibility criteria. By eliminating controversial or unclear findings (insufficient/irrelevant data), results unsubstantiated by replication, too imprecise or undetailed content, and studies having quite similar titles, we decided on 21, mainly empirical, sources. Subsequent analyses should develop on cognitively automated manufacturing systems and artificial cognitive control architectures.

Keywords: cognitive automation; algorithmic governance; smart manufacturing

How to cite: Rogers, S., and Zvarikova, K. (2021). “Big Data-driven Algorithmic Governance in Sustainable Smart Manufacturing: Robotic Process and Cognitive Automation Technologies,” Analysis and Metaphysics 20: 130–144. doi: 10.22381/am2020219.

Received 26 May 2021 • Received in revised form 21 December 2021
Accepted 27 December 2021 • Available online 30 December 2021

Sarah Rogers
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Cognitive Labor Institute,
New York City, NY, USA
(corresponding author)
Katarina Zvarikova
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Faculty of Operation and Economics
of Transport and Communications,
Department of Economics,
University of Zilina, Zilina, Slovak Republic

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