I4S 1/2026: Applied AI Ethics in the WorkplaceA shared responsibility — from radiology and speech therapy to assembly
11.02.2026 - von Valentin Langholf
 , Antonia Weirich
, Uta Wilkens
, Bernd Kuhlenkötter
, I4S Editorial Office |
|
The application of AI ethics in the workplace is everyone’s responsibility. It requires responsibility on the part of companies as a whole and conscious action on the part of a large number of individuals—whether developers or users, managers or employees. This issue of Industry 4.0 Science is dedicated to the interplay of individual responsibility and organizational leadership in a broader social and regulatory context. The topics range from competence development for the ethical use of AI to issues of governance and employee representation. The findings come from various fields, including radiology, speech therapy, assembly, and quality control.
All articles at a glance
- Pre-Stages of GenAI Governance via Managerial Communication
Exploratory findings from SMEs in the Ruhr area - Human-Centered AI in Companies with Employee Representation
Using the HUMAINE model for a company-specific works agreement - Guidelines for the Fair Use of Generative AI
Practical examples from production management and social welfare - Ethical AI in the Workplace Through Value-Based Labels?
Lessons learned from applying the VCIO framework to an AI-based assistant - Ideating Ethical AI Business Models
A dual card approach for the ethical development of AI business models - Operationalizing Ethical AI with tachAId
Validating an interactive advisory tool in two manufacturing use cases - Applied AI for Human-Centric Assembly Workplace Design
An ethics-informed approach - XAI for Predicting and Nudging Worker Decision-Making
Feasibility and perceived ethical issues - JOCAT (Job Change Acceptance Toolbox)
A change management approach for implementing AI systems ethically and sustainably - Co-Determination Dialogues
A tool for human-centered AI implementation - AI Skills for Responsible Use
Realistic learning environments, critical thinking, and role design in teams - Digital Competence Lab (DCL) for Speech Therapy
Designing a learning platform to advance digital skills - AI Implementation in Industrial Quality Control
A design science approach bridging technical and human factors - Data Quality and Domain Expertise for Resilient AI Deployment
Integrating anomaly and label error detection in industry - Multi-Stakeholder AI Ethics in Radiology
Implications for integrated technology and workplace design - Adapting AI Work Systems for Human-Centeredness
A methodical approach for exploring the design space in transdisciplinary teams - Improving Documentation Quality and Creating Time for Core Activities
Success factors for implementing AI-based documentation systems in nursing care
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