Inhaltstyp: Article

The digital transformation of healthcare results in lasting changes in speech therapy. Smart technologies and artificial intelligence (AI) are creating new opportunities to ensure therapy quality, address care bottlenecks, and actively involve patients in exercise processes. At the same time, these developments are expanding the role of speech therapists, who increasingly use digital systems as supportive tools in addition to their core therapeutic tasks. Based on a feasibility study of the AI-supported application ISi-Speech-Sprechen in a real-world setting of complex Parkinson's therapy (PKT), this article outlines the key challenges associated with implementing smart technologies.

Artificial intelligence (AI) offers significant potential to enhance industrial quality control, yet successful implementation requires careful consideration of ethical and human factors. This article examines how automated surface inspection systems can be deployed to augment human capabilities while ensuring ethical integration into workflows. Through design science research, twelve stakeholders from six organizations across three continents are interviewed and twelve sociotechnical design requirements are derived. These are organized into pre-implementation and implementation/operation phases, addressing human agency, employee participation, and responsible knowledge management. Key findings include the critical importance of meaningful employee participation during pre-implementation, and maintaining human agency through experiential learning, building on existing expertise. This research contributes to ethical AI workplace implementation by providing guidelines that preserve human ...

AI systems challenge conventional change management due to their dynamic, opaque, and ethically sensitive nature. This article applies insights from established change models to AI-specific challenges, illustrated by a real-world use case. The resulting propositions are substantiated by six expert interviews, which integrate practical perspectives. Together, they inform the development of the Job Change Acceptance Toolbox (JOCAT), a modular, practice-oriented resource designed to support the implementation of human-centered, ethical, and sustainable AI-related change processes.

Artificial intelligence (AI) can enhance smart assembly by predicting human motion and adapting workplace design. Using probabilistic models such as Gaussian Mixture Models (GMMs), AI systems anticipate operator actions to improve coordination with robots. However, these predictive systems raise ethical concerns related to safety, fairness, and privacy under the EU AI Act, which classifies them as high-risk. This paper presents a conceptual method integrating probabilistic motion modeling with ethical evaluation via Z-Inspection®. An industrial case study using the Smart Work Assistant (SWA) demonstrates how multimodal sensing (motion, gaze) and interpretable models enable anticipatory assistance. The approach moves from ethics evaluation to ethics-informed work design, yielding transferable principles and a configurable assessment matrix that supports compliance-by-design in collaborative assembly.

As part of the regional competence center humAIne, funded by the Federal Ministry of Research, Technology, and Space (BMFTR), a process was developed using co-determination dialogues to establish a common understanding of the challenges involved in the introduction of artificial intelligence (AI) between management, employees, and interest groups. Experiences from project partner companies such as Doncasters Precision Castings in Bochum GmbH (DPC) exemplify how co-determination dialogues not only help to develop legally binding regulations for manageable, operationally anchored, sustainable AI use but also initiate continuous qualification processes for all stakeholder groups in accordance with Articles 4 and 5 of the EU AI Act.

The introduction of artificial intelligence (AI) in companies poses new challenges for regulation and co-determination. Binding requirements have been in force since the 2025 EU AI Act, which must be linked nationally with the Works Constitution Act (BetrVG). The regional competence center humAine has developed a model works agreement on AI (MBV KI) in accordance with Section 77 BetrVG, which strengthens co-determination rights in companies and implements European regulations in a practical way. Flanked by co-determination dialogues, the MBV KI enables company-specific adaptation for responsible and human-centered AI use. Using selected parts of the MBV KI as examples, this article shows how a framework works agreement on AI can be designed and discusses its transferability to companies without a works council. The MBV KI presented here contributes to the sustainable, socially secure design of the digital transformation.

The governance of generative artificial intelligence (GenAI) usage is often described as a formalized reporting system. This neglects the early-stage mechanisms of coping with ethical challenges during the GenAI implementation period. Exploratory empirical findings from the Ruhr area reveal that managerial communicative practices serve as a substitute for missing institutional structures, particularly at an early stage of GenAI implementation in SMEs.

The AI Ethics Label represents a promising approach to promoting ethical AI and appropriate trust in AI systems. However, its practical application reveals some challenges due to its conservative assessment approach, limited context sensitivity, lack of benchmarks, and interpretation aids. Improvements are needed to unlock its full potential.

AI assistance can be seen as a welcome aid in radiology, a highly complex environment characterized by round-the-clock time pressure and quality expectations. However, it must meet high ethical standards from the perspective of both users and patients. It is a challenge to incorporate this human-centered approach into the development and introduction of AI applications.