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I was interviewed by ZDF for the heute news program about the influence of artificial intelligence on the job market. My key points in the interview were:
A (very short) excerpt from the (German) interview can be found here (from 3:28).  After several months of exciting interdisciplinary work, our TOSCA project (“Tokenizing Sustainability – Carbon Credits, Accountability, and ESG in Supply Chains”) within ZEVEDI – Centre for Responsible Digitality has culminated in a publication: Blockchain and Climate Action – Enhancing ESG and Carbon Markets through Financial Technology The book explores how blockchain and tokenization can strengthen transparency, trust, and accountability in voluntary carbon markets, a field that’s becoming increasingly relevant as industries digitize their sustainability efforts. It brings together perspectives from law, economics, and information systems to show how digital infrastructures can support more credible ESG practices and sustainable value chains. I’m very grateful to all co-authors, partners, and the ZEVEDI community for this great collaboration, and proud that the book is open access for everyone interested in the topic.  As part of the project “KrypToFi – Tokenization & Practical Knowledge for SMEs and Startups,” I was interviewed and asked questions. The conversation focused on the potential of tokenization and blockchain technologies for companies – far beyond the financial sector. We talked about which specific areas of application are opening up in fields such as supply chain management and digital identity, what organizations should pay attention to in practical implementation, and what cultural changes the introduction of such technologies entails – especially in terms of leadership, trust, and governance. With the adoption of Regulation (EU) 2024/1689 (the ‘AI Act’), European legislators have firstly created a binding legal framework for the risk-appropriate use of artificial intelligence (AI). In addition to technical and organizational requirements, Art. 4 of the Regulation contains an explicit obligation to ensure a sufficient level of AI literacy among those involved in the development, operation and use of AI systems. The obligation applies to providers and deployers of such systems and must be fulfilled “to their best extent”. Our recently published whitepaper provides a systematic analysis and practical operationalization of the AI literacy requirements standardized by Article 4 AI Act. The aim is to provide guidance, particularly for small and medium-sized enterprises (SMEs), on the structured implementation of the regulatory requirements. To this end, the legal basis is thoroughly examined and translated into an integrated competence model that distinguishes between individual (micro-) and organizational (macro-) dimensions. The focus is on a two-stage process model for identifying and developing AI literacy: a bottom-up analysis of individual abilities is systematically combined with a top-down comparison of organizational requirements. In addition, a morphological box for classifying AI-relevant role profiles is introduced, which enables a structured assignment competence requirements and measures. This work thus contributes to the normative, methodological and practical foundation of the obligation to ensure competence in the field of AI established by Article 4 AI Act. It is intended as a guide for corporate and public actors who not only want to meet regulatory requirements but also want to translate them into strategically sound competence development.  The global talent shortage has become a universal challenge, prompting practitioners and researchers to explore digital innovations as potential solutions for acquiring the right talents. However, the role of emerging technologies like generative artificial intelligence (AI) in human resources (HR) remains largely uncharted territory. Our recently accepted article investigates generative AI's transformative potential to augment recruiters' daily operations. Through a qualitative interview study, we derive and illuminate the opportunities of generative AI within the recruitment domain, shedding light on its promising opportunities but also addressing inherent challenges. The findings of this study propose a theoretical model of generative AI in recruitment and how it empowers recruiters in their daily tasks to recruit tomorrow's talents. I am happy that our paper “Hiring Tomorrow’s Talents: How Generative Artificial Intelligence Transforms Human Resources Recruitment” has been accepted for presentation at the Hawaii International Conference on System Sciences (HICSS) in January 2026.  Centralized social media (CSM) are criticized for issues such as data exploitation, content manipulation, and unilateral governance. In response, decentralized social media (DSM) platforms, such as federated and blockchain-based, have emerged, promising greater user autonomy, privacy, and participatory governance. However, the extent to which DSM address or merely reconfigure CSM’s problems remains unclear. Our recently accepted study conducts a scoping literature review to analyze challenges across three dimensions: platform ownership, technical infrastructure, and user agency. Using qualitative coding, we synthesize critical issues and find that decentralization redistributes, rather than resolves, social media’s core challenges. While DSM reduce corporate dominance, they introduce new governance complexities, infrastructural barriers, and issues related to user agency such as extremism and misinformation. We conclude that DSM shift the locus of control and responsibility, requiring innovative governance to realize their potential. I am happy that our paper “One Solution to Fix Them All: Does Decentralization Fix the Problems of Social Media?” has been accepted for presentation at the 46th International Conference on Information Systems (ICIS 2025) in Nashville, Tennessee.  Although artificial intelligence (AI) is expected to significantly alter strategic decision making (DM) on an organizational level, only a few scientific articles examine the evolution of AI within the organizational DM (ODM) process. Most contributions lack empirical insights to allow predictions of the development of DM under the influence of AI or show outdated perspectives on the capabilities of AI in ODM. Our new paper addresses this gap by conducting a multi-vocal literature review (MLR) and a quantitative analysis of patents on AI-based decision support systems (DSS). Overall, the findings advance current research on AI in ODM by providing an overview of existing theoretical contributions and predicting a trend toward an increasing augmentation of human intelligence by AI throughout the ODM process. This enables managers to take strategic action and adapt organizational structures and managerial tasks based on our prediction of the future evolution of AI within the ODM process. I am happy that our paper “The Evolution of the Organizational Decision Making Process: A Predictive Analysis of the Impact of Artificial Intelligence” has been accepted for presentation at the 46th International Conference on Information Systems (ICIS 2025) in Nashville, Tennessee.  Let's imagine: Europe develops artificial intelligence without handing over sensitive data, without dependence on US clouds, and without building expensive new data centers. What still sounds like a vision today is technically possible with the SplitNFed approach: a concept for data-sovereign, distributed AI training that uses existing IT infrastructure instead of replacing it. In our new white paper, we show how companies can use SplitNFed to protect their data, make better use of existing IT infrastructure, and train AI securely and collaboratively, even with limited computing resources—all in a sovereign, efficient, and scalable manner. Click here for the (German) white paper: https://lnkd.in/e7FNUqHe  |
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