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Perceived Sensemaking and Communication Effectiveness in Complex AI/ML Environments : = a Quantitative Study on Software Engineers in Multinational Companies.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Perceived Sensemaking and Communication Effectiveness in Complex AI/ML Environments :/
Reminder of title:	a Quantitative Study on Software Engineers in Multinational Companies.
Author:	Holst, Amanda L.
Description:	1 online resource (196 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-09, Section: A.
Contained By:	Dissertations Abstracts International85-09A.
Subject:	Information science. -
Online resource:	click for full text (PQDT)
ISBN:	9798381851878

Perceived Sensemaking and Communication Effectiveness in Complex AI/ML Environments : = a Quantitative Study on Software Engineers in Multinational Companies.
Holst, Amanda L.

Perceived Sensemaking and Communication Effectiveness in Complex AI/ML Environments :a Quantitative Study on Software Engineers in Multinational Companies. - 1 online resource (196 pages)

Source: Dissertations Abstracts International, Volume: 85-09, Section: A.

Thesis (Ph.D.)--Indiana Institute of Technology, 2023.

Includes bibliographical references

In the dynamic realm of AI and ML technologies, characterized by intricate data and interdisciplinary collaboration, this study investigates perceived sensemaking and communication effectiveness. This research addresses emerging challenges in AI/ML integration and the development of AI-driven software systems, aiming to bridge knowledge gaps, offer practical contributions, and serve as a valuable resource for global leaders navigating the complex AI/ML landscape. Focused on software engineers in multinational U.S. companies, the research examines perceived sensemaking and communication effectiveness during AI/ML project requirement gathering. Using a quantitative correlational approach, it uncovers a strong positive correlation between perceived sensemaking and individual communication effectiveness, emphasizing sensemaking's crucial role. While leveraging prior knowledge enhances sensemaking, challenges emerge in connecting elements, revealing a gap between data and cognitive framing. The study identifies strong positive correlations between sensemaking and high communication effectiveness. Complexity Leadership Theory underpins the research, advocating adaptability and collaboration in AI/ML settings. It suggests further exploration in sensemaking, AI/ML standards, and global leadership, emphasizing leadership development, multidisciplinary training, cultural diversity, and adaptive organizations. These findings stress the importance of Complexity Leadership and effective communication in AI/ML projects for global leaders and organizations.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798381851878Subjects--Topical Terms:

561178
Information science.
Subjects--Index Terms:

AI/ML softwareIndex Terms--Genre/Form:

554714
Electronic books.

Perceived Sensemaking and Communication Effectiveness in Complex AI/ML Environments : = a Quantitative Study on Software Engineers in Multinational Companies.
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