A Double-Edged Sword : Conceptual and Empirical Insights into the Interaction of Medical Stakeholders with Artificial Intelligence Explanations.

Format:

Book

Author/Creator:

Aslan, Aycan.

Language:

English

Subjects (All):

Artificial intelligence.

Human-computer interaction.

Physical Description:

1 online resource (203 pages)

Edition:

1st ed.

Place of Publication:

Göttingen : Cuvillier Verlag, 2025.

Summary:

This dissertation critically examines the integration of Explainable Artificial Intelligence (XAI) in medical applications, highlighting its double-edged nature. It explores the benefits and risks of AI explanations for medical stakeholders, focusing on fostering trust, transparency, and adoption while addressing challenges such as increased cognitive load and privacy concerns. The research comprises conceptual and empirical studies that investigate how explanations influence medical experts and patients. A procedural model is proposed to guide the integration of explanations across different interaction phases, offering strategies to balance transparency, cognitive load, and privacy concerns in clinical scenarios. The work contributes to Human-AI interaction literature and provides actionable insights for developing trustworthy AI systems in healthcare settings. Generated by AI.

Contents:

Acknowledgements

Abstract

Table of Contents

List of Figures

List of Tables

List of Abbreviations

A. Foundations

I. Introduction

I.1 Motivation

I.2 Research Gap and Research Questions

I.3 Structure of this Thesis

I.4 Research Positioning and Design

I.4.1 Research Paradigms and Positioning

I.4.2 Research Design

I.5 Anticipated Contributions and Implications

II. Research Background

II.1 Artificial Intelligence and its Use-Cases for Medical Applications

II.1.1 What Artificial Intelligence is and its Potential

II.1.2 Medical Stakeholders and their Interaction with Artificial Intelligence

II.2 Explainable Artificial Intelligence

II.2.1 The Issue of Opaque Artificial Intelligence

II.2.2 The Rise of Explainable Artificial Intelligence as a Response

II.2.3 Current State of the Literature on the Effect of Explanations

II.3 AI-Advised Decision-Making and Decision Augmentation

B. Studies on the Effect of Explanations on Medical Stakeholder

I. A Conceptual Framework for Understanding the Unique Informational Content of Explanations

1. Study 1: Conceptualizing how Explanations are Perceived in the Context of AI-Advised Decision-Making

1.1 Introduction

1.2 Literature Review and Conceptual Foundations

1.2.1 AI-Advised Decision-Making and its Elements Generated by AI.

Notes:

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

ISBN:

3-689-52653-1

OCLC:

1523375993