Trust-Building in AI-Human Partnerships Within Industry 5.0

Abstract The rapid advancement of artificial intelligence (AI) within Industry 4.0 has transformed manufacturing processes, shifting from traditional automation to more collaborative AI-human partnerships. While AI promises enhanced efficiency, precision, and productivity, the success of these systems relies heavily on the trust established between human operators and AI technologies. This paper explores the critical factors influencing trust in AI-human partnerships in the manufacturing sector, emphasizing the need for transparency, accountability, and ethical AI design. Drawing on a multi-disciplinary literature review and empirical studies, we identify key drivers of trust, including human preferences for system transparency, the explainability of AI decisions, and the reliability of AI systems in dynamic production environments. Furthermore, the paper examines the challenges associated with trust-building, such as overcoming fear of job displacement and managing perceived risks of AI errors. The findings contribute to the growing body of knowledge on human-centric AI design and offer practical recommendations for fostering trust to ensure successful AI-human collaboration in manufacturing settings. By transitioning from purely automated systems to collaborative partnerships, manufacturers can unlock the full potential of AI while maintaining a workforce that is confident in AI’s reliability and ethical alignment.

Authors

Institutions

Publication Details

Journal
System Safety Human - Technical Facility - Environment
Published
2024-12-01
DOI
https://doi.org/10.2478/czoto-2024-0011
Citations
5
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
3.90
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Trust-Building in AI-Human Partnerships Within Industry 5.0

Justyna Żywiołek
5 citations
System Safety Human - Technical Facility - Environment
Blockchain Technology Applications and Security
3.90
article

Trust-Building in AI-Human Partnerships Within Industry 5.0

Justyna Żywiołek
article en
5 citations

Abstract

Abstract The rapid advancement of artificial intelligence (AI) within Industry 4.0 has transformed manufacturing processes, shifting from traditional automation to more collaborative AI-human partnerships. While AI promises enhanced efficiency, precision, and productivity, the success of these systems relies heavily on the trust established between human operators and AI technologies. This paper explores the critical factors influencing trust in AI-human partnerships in the manufacturing sector, emphasizing the need for transparency, accountability, and ethical AI design. Drawing on a multi-disciplinary literature review and empirical studies, we identify key drivers of trust, including human preferences for system transparency, the explainability of AI decisions, and the reliability of AI systems in dynamic production environments. Furthermore, the paper examines the challenges associated with trust-building, such as overcoming fear of job displacement and managing perceived risks of AI errors. The findings contribute to the growing body of knowledge on human-centric AI design and offer practical recommendations for fostering trust to ensure successful AI-human collaboration in manufacturing settings. By transitioning from purely automated systems to collaborative partnerships, manufacturers can unlock the full potential of AI while maintaining a workforce that is confident in AI’s reliability and ethical alignment.

System Safety Human - Technical Facility - EnvironmentVol. 6(1)
Częstochowa University of Technology (PL)
Openalex Percentile: Top 5%
Blockchain Technology Applications and Security
3.90
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Trust-Building in AI-Human Partnerships Within Industry 5.0 — Justyna Żywiołek · System Safety Human - Technical Facility - Environment (2024) | TGRS Research Map | TGRS