Aligning Artificial Intelligence with Organizational Contexts : An Investigation of Natural Language Processing in Clinical Healthcare / Marvin Böhmker.

Format:

Book

Author/Creator:

Böhmker, Marvin, author.

Language:

English

Subjects (All):

Artificial intelligence.

Physical Description:

1 online resource (217 pages)

Edition:

First edition.

Place of Publication:

Göttingen : Cuvillier Verlag, [2025]

Summary:

Künstliche Intelligenz (KI) bietet enormes Potenzial, um Herausforderungen wie Fachkräftemangel und eine wachsende Zahl älterer Patientinnen und Patienten zu bewältigen. Gleichzeitig jedoch stellt die soziotechnische Einbettung von KI in Organisationen eine komplexe Aufgabe dar, deren Misslingen zu Wissensverlust oder Unzufriedenheit im Team führen kann. In dieser Dissertation werden die entscheidenden Komponenten dieses KI-Alignments systematisch untersucht. Vier Studien davon zwei auf allgemeiner Ebene und zwei mit Fokus auf Natural Language Processing (NLP) im klinischen Bereich beleuchten, wie KI und organisatorische Anforderungen bestmöglich aufeinander abgestimmt werden können. Dabei entsteht ein Rahmenwerk, das sowohl Forschenden als auch Praktikerinnen und Praktikern hilft, KI-Lösungen gezielt zu planen, zu integrieren und kontinuierlich zu verbessern. Zugleich eröffnet die Arbeit neue Perspektiven für Forschung und Anwendung, vor allem durch die Betrachtung von KI in spezifischen Kontexten und durch die gezielte Identifikation bisher unbeachteter Aspekte.Artificial Intelligence (AI) offers enormous potential for tackling challenges such as staffing shortages and a growing elderly population with increasing healthcare needs. However, effectively embedding AI in organizations is a complex sociotechnical endeavor; if misaligned, it can lead to knowledge loss or employee dissatisfaction. This dissertation systematically examines the key components of AI alignment. Four studiestwo at a general level and two focused on Natural Language Processing (NLP) in clinical settingsexplore how AI can best be harmonized with organizational requirements. The resulting framework supports researchers and practitioners alike in planning, integrating, and continuously refining AI solutions. Moreover, this work opens new horizons in research and practice by examining AI in specific contexts and identifying aspects that have received little attention thus far.

Contents:

Intro

Table of Contents

List of Figures

List of Tables

List of Abbreviations

A. Foundations

I. Introduction

I.1 Motivation

I.2 Research Gap and Resulting Research Questions

I.3 Structure of this Thesis

I.4 Research Positioning and Design

I.5 Anticipated Contributions

II. Research Background

II.1 Artificial Intelligence in Organizational Contexts

II.2 Natural Language Processing in Healthcare

II.3 Medical Documentation Processes - The Case of"AuMEDa"

B. Studies on Artificial Intelligence in OrganizationalContexts

I. Structuring of Human-AI Collaboration in OrganizationalContexts

1. Study 1: Preparing for Generative AI Teammates: ALiterature Review of Human-AI Teaming in Organizations

1.1 Introduction

1.2 Research Background

1.3 Research Design

1.4 Findings

1.5 Discussion

1.6 Appendix Study 1

II. Aligning Natural Language Processing Systems withClinical Healthcare

1. Study 2: Natural Language Processing for Medical Texts- A Taxonomy to Inform Integration Decisions intoClinical Practice

1.4 Taxonomy to Inform Integration Decisions of NLP-Systems inHealthcare

1.5 Application of the Taxonomy

1.6 Discussion

1.7 Conclusion

1.8 Appendix Study 2

2. Study 3: Just what the Doctor ordered - Towards DesignPrinciples for NLP-based Systems in Healthcare

2.1 Introduction

2.2 Research Background

2.3 Research Design

2.4 Understanding the Design of NLP-based Systems in Healthcare

2.5 Discussion and Conclusion

III. Investigating the Impact of Alignment on Human-AICollaboration Performance

1. Study 4: Humans Supervising Artificial Intelligence -Investigation of Designs to Optimize Error Detection

1.2 Research Background.

1.3 Research Model and Hypotheses Development

1.4 Experimental Design

1.5 Experiment 1: Prior Information

1.6 Experiment 2: Visual Guidance

1.7 Discussion

1.8 Conclusion

1.9 Appendix Study 4

C. Contributions

I. Findings and Synthesis

I.1 Findings of the Research on the Status Quo of Human-AI Collaboration

I.2 Findings of the Research on Natural LanguageProcessing for Clinical Healthcare

I.3 Findings of the Research on Designing and EvaluatingHuman-AI Collaboration

I.4 Synthesis of Findings

II. Limitations, Future Research and Implications

II.1 Limitations

II.2 Future Research

II.3 Implications for Research and Practice

III. Concluding Remarks

References

Appendix.

Notes:

Includes bibliographical references.

Description based on publisher supplied metadata and other sources.

Description based on print version record.

ISBN:

3-689-52785-6