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국회도서관 홈으로 정보검색 소장정보 검색

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동의어 포함

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Title page 1

Contents 5

Abstract 4

About the authors 4

Introduction 9

1. Background 10

AI and Automation in Healthcare: Promise and Implementation Gaps 10

Nursing Work and the Coordination Burden 10

Institutional Logics of Technology Investment 11

Technology Development Processes and the Question of Whose Voice Counts 12

Nursing Work in South Korea 12

2. Methods: Site, Participants, and the Social Organization of Ward Work 14

Interviews 14

Observations 15

Research Site and Context 16

The Ward as Multi-Actor Space 18

Nursing as Intermediary Work 18

Participatory Design Workshops 19

Analysis 19

3. Findings Part 1. Envisioning Ideal AI: What Nurses Want 21

AI Reducing Workload and Saving Time 21

AI Addressing Interpersonal Issues 23

AI for Fair Work Distribution 25

AI for Improving Productivity and Efficiency 26

AI in Managing Economic Disparities among Hospitals 27

4. Findings Part 2. Automating Care: Success, Failure, and the Gap Between Technology and Need 28

Pattern One: When Automation Works 28

Eliminating Drudgery and Unpaid Preparation Time 28

The Conditions of Success 29

Pattern Two: When AI Fails 30

Gap between Contextual and Model-based Predictions 30

Gap between Lab and Real-world Settings 31

Pattern Three: The Persistent Gap 32

What Nurses Asked For 32

Why Patient Education Automation Didn't Happen 33

5. Discussion 34

The Role of a Labour Union in AI Adoption 34

Central Values Prioritized in AI Adoption 34

Technological Advancement and Resource Gap 35

Decision-making Process 36

Automation and Nursing 37

Conclusion 38

References 39

Tables 8

Table 1. Participant information: participants from Mirae Hospital (MH), Certified Nursing Assistant 14

Table 2. Participant information: participants from Korean Health Workers Union (KHWU) 15

Figures 7

Figure 1. Results from collaborative mapping during individual interviews 17

Figure 2. Technologies observed at the field site: Magic Cart logistics robot (left) and BPOC device (circled) for patient verification,... 17

Figure 3. Example ideas created by participants during the design workshops 19