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Venturing into Uncharted Territory - Exploring the Psychological Implications of AI-Driven Automation for Employees.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Venturing into Uncharted Territory - Exploring the Psychological Implications of AI-Driven Automation for Employees./
Author:	Sureth, Antonia Marie.
Description:	1 online resource (305 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-03, Section: A.
Contained By:	Dissertations Abstracts International86-03A.
Subject:	Technology adoption. -
Online resource:	click for full text (PQDT)
ISBN:	9798384335894

Venturing into Uncharted Territory - Exploring the Psychological Implications of AI-Driven Automation for Employees.
Sureth, Antonia Marie.

Venturing into Uncharted Territory - Exploring the Psychological Implications of AI-Driven Automation for Employees. - 1 online resource (305 pages)

Source: Dissertations Abstracts International, Volume: 86-03, Section: A.

Thesis (Ph.D.)--Humboldt Universitaet zu Berlin (Germany), 2024.

Includes bibliographical references

The rapidly expanding capabilities of artificial intelligence (AI) drive the increasing application of AI-based systems to automate a growing range of job tasks. This fundamentally reshapes the world of work. In the short- to medium term, job tasks and working conditions, and thus jobs, are changing. In the long term, this development may also lead to structural changes in the labor market, requiring societal adaptation including the transformation of existing welfare systems. Both the short- to medium-term impact of AI-driven automation on jobs as well as the long-term impact on the labor market carry significant potential for far-reaching psychological implications for employees. However, psychological research dedicated to the impact of AI-driven automation on the world of work is scarce and a psychological perspective on these developments is largely lacking. Therefore, the aim of this dissertation was to contribute to a psychological perspective on the topic and investigate the psychological implications of AI-driven automation for employees.This dissertation comprises three projects. Projects 1 and 2 focused on the short- to mediumterm effects of AI-driven automation, exploring how AI-driven automation transforms jobs and the related psychological implications for employees. Project 3 acknowledged the possible long-term effects of AI-driven automation on the labor market, including the prospect of a potential shift in the welfare system, and examined a universal basic income (UBI) with a specific emphasis on psychological aspects.The aim of Project 1 was to explore application fields of AI-driven automation in the workplace, associated opportunities and threats, its impact on employees' job tasks, and employees' experience and behavior in response to these changes. To this end, we conducted five interview studies with a total of N= 91 experts and employees from two exemplary sectors, i.e., healthcare and financial services. Our results indicate that AI-driven automation already has a significant impact on both sectors, triggering diverse experiences and behavior among employees in response to the resulting changes. Above all, the rich set of results derived from our studies provides numerous starting points for future research and serves as fertile ground for the development of research questions in this emerging field of research.The aim of Project 2 was to develop a questionnaire to investigate the relevance of selected psychological concepts in the context of AI-driven automation, thus complementing the qualitative methodological approach of Project 1 with a quantitative approach. The questionnaire development was divided into three phases and included two preliminary studies with a total of N= 1,293 participants. Project 2 resulted in an online questionnaire in German that takes 10 to 15 minutes to complete, targets employees and self-employed persons, and assesses participants' expectations regarding the future impact of AI-driven automation on themselves in terms of 11 psychological concepts.The aim of Project 3 was to investigate socio-demographic and psychological predictors of UBI acceptance among the German working population. To this end, we used a representative sample of the German working population (N= 1,986) and conducted a hierarchical multiple linear regression with a total of 15 predictors. We found that, on average, members of the German working population supported the idea of a UBI and that being more supportive of a UBI went along with being comparably younger, of East-German origin, and being more in favor of equal living standards, as well as perceiving one's economic situation to be worse and the threat of the corona-pandemic to be higher.r. Taken together, the studies conducted in this dissertation contribute to a psychological perspective on the topic of AI, automation, and work by examining both short- to medium-term and long-term effects of AI-driven automation and the resulting psychological implications for employees.

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

Mode of access: World Wide Web

ISBN: 9798384335894Subjects--Topical Terms:

1466919
Technology adoption.
Index Terms--Genre/Form:

554714
Electronic books.

Venturing into Uncharted Territory - Exploring the Psychological Implications of AI-Driven Automation for Employees.
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520 $a The rapidly expanding capabilities of artificial intelligence (AI) drive the increasing application of AI-based systems to automate a growing range of job tasks. This fundamentally reshapes the world of work. In the short- to medium term, job tasks and working conditions, and thus jobs, are changing. In the long term, this development may also lead to structural changes in the labor market, requiring societal adaptation including the transformation of existing welfare systems. Both the short- to medium-term impact of AI-driven automation on jobs as well as the long-term impact on the labor market carry significant potential for far-reaching psychological implications for employees. However, psychological research dedicated to the impact of AI-driven automation on the world of work is scarce and a psychological perspective on these developments is largely lacking. Therefore, the aim of this dissertation was to contribute to a psychological perspective on the topic and investigate the psychological implications of AI-driven automation for employees.This dissertation comprises three projects. Projects 1 and 2 focused on the short- to mediumterm effects of AI-driven automation, exploring how AI-driven automation transforms jobs and the related psychological implications for employees. Project 3 acknowledged the possible long-term effects of AI-driven automation on the labor market, including the prospect of a potential shift in the welfare system, and examined a universal basic income (UBI) with a specific emphasis on psychological aspects.The aim of Project 1 was to explore application fields of AI-driven automation in the workplace, associated opportunities and threats, its impact on employees' job tasks, and employees' experience and behavior in response to these changes. To this end, we conducted five interview studies with a total of N= 91 experts and employees from two exemplary sectors, i.e., healthcare and financial services. Our results indicate that AI-driven automation already has a significant impact on both sectors, triggering diverse experiences and behavior among employees in response to the resulting changes. Above all, the rich set of results derived from our studies provides numerous starting points for future research and serves as fertile ground for the development of research questions in this emerging field of research.The aim of Project 2 was to develop a questionnaire to investigate the relevance of selected psychological concepts in the context of AI-driven automation, thus complementing the qualitative methodological approach of Project 1 with a quantitative approach. The questionnaire development was divided into three phases and included two preliminary studies with a total of N= 1,293 participants. Project 2 resulted in an online questionnaire in German that takes 10 to 15 minutes to complete, targets employees and self-employed persons, and assesses participants' expectations regarding the future impact of AI-driven automation on themselves in terms of 11 psychological concepts.The aim of Project 3 was to investigate socio-demographic and psychological predictors of UBI acceptance among the German working population. To this end, we used a representative sample of the German working population (N= 1,986) and conducted a hierarchical multiple linear regression with a total of 15 predictors. We found that, on average, members of the German working population supported the idea of a UBI and that being more supportive of a UBI went along with being comparably younger, of East-German origin, and being more in favor of equal living standards, as well as perceiving one's economic situation to be worse and the threat of the corona-pandemic to be higher.r. Taken together, the studies conducted in this dissertation contribute to a psychological perspective on the topic of AI, automation, and work by examining both short- to medium-term and long-term effects of AI-driven automation and the resulting psychological implications for employees.
520 $a Die rasch wachsenden Fahigkeiten Kunstlicher Intelligenz (KI) haben zur Folge, dass KIbasierte Systeme zunehmend zur Automation einer wachsenden Bandbreite von Arbeitstatigkeiten eingesetzt werden. Dieser Trend verandert die Arbeitswelt massiv. Kurz- bis mittelfristig verandern sich dadurch Arbeitstatigkeiten und -bedingungen und damit Jobs. Langfristig konnte diese Entwicklung auch zu strukturellen Arbeitsmarktveranderungen fuhren, die gesellschaftliche Anpassungen einschlieslich der Transformation bestehender Wohlfahrtssysteme erfordern wurden. Sowohl die kurz- bis mittelfristigen Auswirkungen von KI-bedingter Automation auf Jobs als auch die langfristigen Auswirkungen auf den Arbeitsmarkt bergen erhebliches Potenzial fur weitreichende psychologische Implikationen fur Beschaftigte. Psychologische Forschung, die sich mit den Auswirkungen KI-bedingter Automation auf die Arbeitswelt befasst, ist jedoch rar und eine psychologische Perspektive auf diese Entwicklungen fehlt weitestgehend. Ziel der Dissertation war es daher, zu einer psychologischen Perspektive auf das Thema beizutragen und die psychologischen Implikationen KI-bedingter Automation fur Beschaftigte zu untersuchen.Die Dissertation umfasst insgesamt drei Projekte. In den Projekten 1 und 2 lag der Fokus auf den kurz- bis mittelfristigen Auswirkungen KI-bedingter Automation. Im Rahmen dieser Projekte haben wir untersucht, wie KI-bedingte Automation Jobs verandert und welche psychologischen Implikationen diese Veranderungen fur Beschaftigte haben. Der Fokus von Projekt 3 lag auf den moglichen langfristigen Auswirkungen KI-bedingter Automation auf den Arbeitsmarkt und den damit moglicherweise einhergehenden grundsatzlichen Veranderungen des Wohlfahrtssystems. Im Rahmen dieses Projekts haben wir ein bedingungsloses Grundeinkommen (BGE) unter expliziter Berucksichtigung psychologischer Aspekte untersucht.Das Ziel von Projekt 1 war es, die Anwendungsfelder von KI-bedingter Automation am Arbeitsplatz, die damit verbundenen Chancen und Risiken, die Auswirkungen auf die Tatigkeiten von Beschaftigten sowie das Erleben und Verhalten von Beschaftigten in Reaktion auf diese Veranderungen zu untersuchen. Zu diesem Zweck haben wir funf Interviewstudien mit insgesamt N= 91 Expert:innen und Beschaftigten in zwei exemplarischen Sektoren, dem Gesundheitswesen und dem Finanzdienstleistungssektor, durchgefuhrt. Unsere Ergebnisse deuten darauf hin, dass KIbedingte Automation in beiden Sektoren bereits jetzt erhebliche Auswirkungen hat und bei Beschaftigten unterschiedlichstes Erleben und Verhalten in Reaktion auf die daraus resultierenden Veranderungen auslost. Vor allem aber bieten die reichhaltigen Ergebnisse unserer Studien zahlreiche Ansatzpunkte fur zukunftige Forschung und dienen als vielversprechende Grundlage fur die Entwicklung von Forschungsfragen in diesem sich gerade erst entwickelnden Forschungsfeld.Das Ziel von Projekt 2 war die Entwicklung eines Fragebogens, mit dem die Relevanz ausgewahlter psychologischer Konzepte im Kontext KI-bedingte Automation untersucht werden kann. Hiermit sollte der qualitative methodische Ansatz von Projekt 1 um einen quantitativen Ansatz erganzt werden. Die Fragebogenentwicklung war in drei Phasen unterteilt und umfasste zwei Vorstudien mit insgesamt N = 1 293 Teilnehmer:innen. Das Ergebnis von Projekt 2 ist ein deutschsprachiger Online-Fragebogen, dessen Beantwortung 10 bis 15 Minuten in Anspruch nimmt, der sich an Erwerbstatige richtet und die Erwartungen der Befragten hinsichtlich zukunftiger Auswirkungen KI-bedingter Automation auf sie selbst anhand von elf psychologischen Konzepten erfasst.Das Ziel von Projekt 3 war es, sozio-demografische und psychologische Pradiktoren fur die Akzeptanz eines BGE in der deutschen Erwerbsbevolkerung zu untersuchen. Zu diesem Zweck haben wir auf Basis einer reprasentativen Stichprobe der deutschen Erwerbsbevolkerung (N= 1 986) eine hierarchische multiple lineare Regression mit insgesamt 15 Pradiktoren durchgefuhrt. Unsere Ergebnisse haben gezeigt, dass Mitglieder der deutschen Erwerbsbevolkerung ein BGE im Durchschnitt befurworteten und dass eine hohere BGE-Zustimmung mit vergleichsweise jungerem Alter, ostdeutscher Herkunft und einer starkeren Befurwortung gleicher Lebensstandards fur alle einherging. Daruber hinaus ging eine hohere BGE-Zustimmung mit einer schlechteren Beurteilung der eigenen wirtschaftlichen Situation und einer hoheren wahrgenommenen Bedrohung durch die Corona-Pandemie einher.Insgesamt tragen die in dieser Dissertation durchgefuhrten Studien zu einer psychologischen Perspektive auf den Themenkomplex KI, Automation und Arbeit bei, indem sie sowohl kurz-bis mittelfristige als auch langfristige Auswirkungen von KI-bedingter Automation in den Fokus nahmen und die daraus resultierenden psychologischen Implikationen fur Beschaftigte untersuchten.
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