Research projects

ComAIs are increasingly presented as solutions to the care demands of a growing older population vis-à-vis a defunding of healthcare systems and a shortage of healthcare professionals. They are also promoted as supporting “healthy ageing”, a policy objective that aims to advance the wellbeing of older adults. In this context, technology companies and policy makers create re-gimes of anticipations that shape expectations and future imaginaries, and define what is thinkable and desirable. In these anticipation regimes, ComAIs are ascribed different “care obligations”: managing healthy ageing, providing health information and facilitating older adults’ access to health care. P9 researches the emergence and constructions of hybrid healthcare figurations through digital methods and qualitative case studies in Austria, Germany, UK and the US. The project aims to reconstruct care practices of different older populations, healthcare professionals and informal carers through ComAIs. This contributes to the RU’s research objectives to typify patterns of appropriation in social domains and explore new forms of hybrid agency.

Der Stand der Digitalisierung der öffentlichen Verwaltung wird in der gesellschaftlichen Debatte gegenwärtig kritisch diskutiert. Es dominieren Wahrnehmungen von fehlender Innovationskraft und Rückständigkeit im internationalen Vergleich. Die digitale Transformation trifft in Deutschland mit einem weiteren gesellschaftlichen Transformationsprozess von nicht zu unterschätzendem Ausmaß zusammen: dem demografischen Wandel. Denkt man die beiden gesellschaftlichen Großtrends – digitale Transformation von Staat und öffentlicher Verwaltung sowie demografischer Wandel – zusammen, so kommt der Deutschen Rentenversicherung eine zentrale Rolle zu. Für eine wachsende Zahl von Bürger:innen wird die Deutsche Rentenversicherung zu dem Ort, an dem sich Staatlichkeit materialisiert und im Alltag erfahrbar wird. Für einen Staat, der die digitale Transformation pro-aktiv gestalten will, ist die Digitalisierung der Rentenversicherung ein zentrales Gestaltungsinstrument. Digitalisierung kann zu neuen Formen der Teilhabe führen, aber auch neue Ungleichheiten hervorrufen oder bestehende verstärken. Wie soziale Akteur:innen diese Veränderungsprozesse erleben, muss innerhalb eines partizipativen Forschungsansatzes ergründet werden, der auf die gelebte Erfahrung und die lebensweltliche Expertise abzielt. Das Forschungsvorhaben zielt auf einen solchen partizipativen Forschungsansatz ab und greift hierfür eine organisatorische Besonderheit der Deutschen Rentenversicherung auf: die soziale Selbstverwaltung als partizipatives Organisationsmodell, die gesetzliche Versicherung und Zivilgesellschaft miteinander verbindet. Ausgangsthese ist, dass die soziale Selbstverwaltung mit ihrer Verknüpfung zur Zivilgesellschaft ein wichtiges Element darstellt, um die Digitalisierung der gesetzlichen Rentenversicherung niedrigschwellig und inklusiv zu gestalten. Das Forschungsvorhaben untersucht, (1) wie sich die Strukturen, Prozesse und Praktiken der sozialen Selbstverwaltung durch Digitalisierung wandeln, (2) welche Chancen und Herausforderungen damit verbundenen sind und (3) welchen Beitrag die soziale Selbstverwaltung zu einer inklusiven und bürger*innenorientierten digitalen Rentenversicherung leisten kann.

Dieses interdisziplinäre Forschungsprojekt will das die gesellschaftlichen, politischen und wirtschaftlichen Auswirkungen technologischer Innovationen, insbesondere im Bereich der Künstlichen Intelligenz (KI), beleuchten. Besonderes Augenmerk liegt dabei auf der Automatisierung des maschinellen Lernens (AutoML) und den damit einhergehenden Veränderungen, insbesondere im Bereich des Designs von ML-Systemen als auch im Kontext der Einbindung in Unternehmensprozesse und deren konkrete Anwendung durch Fachexpert:innen. Um dieses Vorhaben adäquat bearbeiten zu kommen, werden Ethik und Business Analytics and Data Science im Rahmen dieses Projekts intensiv zusammenarbeiten, um Expertisen aus unterschiedlichen Fachdiskursen einzubringen und um die im Kontext der mit AutoML verbundenen Herausforderungen möglichst breit bearbeiten zu können. AutoML, das als Demokratisierung des maschinellen Lernens propagiert wird, ermöglicht es Fachexpert:innen mit begrenztem Wissen im Bereich ML, maßgeschneiderte Modelle zu erstellen. Dies senkt die Einstiegshürde, birgt jedoch das Risiko eines mangelnden Bewusstseins für technologische Grenzen und Designentscheidungen. Die Ethik spielt eine Schlüsselrolle, da sie die Auswirkungen auf die menschliche Autonomie und Wahlfreiheit in den Fokus rückt. Die herkömmliche Regulierung und IT-Governance stoßen hier an ihre Grenzen, da AutoML-Anwendungen ohne formelle Genehmigungen genutzt werden können, was als Schatten-IT bekannt ist. Es ist hier etwa notwendig, spezielle Dokumentationsrichtlinien für KI zu entwickeln, um die Anforderungen an ML-Anwendungen (FAT - Fairness, Accountability, Transparency) auf AutoML anzuwenden. Ein zentrales Forschungsdesiderat liegt in der ethischen Bewertung von AutoML-Anwendungen, insbesondere in Bezug auf deren Einsatz durch Fachexpert:innen. Ethik hat gerade in den Anfangsphasen technologischer Entwicklungen eine wichtige Orientierungsfunktion und sollte intensiv in diese Innovationsprozesse miteinbezogen werden. Die in interdisziplinärer Zusammenarbeit zwischen den Professuren für Business Analytics and Data Science sowie Ethik und Gesellschaftslehre erarbeiteten Projektziele umfassen die Erhebung des aktuellen Standes des Einsatzes von AutoML in der steirischen Wirtschaft, die Durchführung einer Risiko- und Potentialanalyse sowie die Erstellung eines Handlungsleitfadens. Dies soll dazu beitragen, ethische Aspekte von AutoML-Anwendungen in konkreten Einsatzkontexten zu berücksichtigen und eine ethische Regulierung im Rahmen der digitalen Transformation voranzutreiben.

Advancements in the field of Artificial Intelligence (AI) and especially in Machine Learning (ML) have had an important impact on individuals, organisations, and society at large. However, access to designing AI and ML has so far been limited to specialised actors. With the help of Low-Code Development Platforms (LCDPs) application software can be created with minimal programming knowledge. This enables individuals with a non-IT background to re- and upskill towards IT development. The research group [Sm-AI-R] investigates systems based on LCDPs from six complementary research perspectives, focussing on the Smart Regulation of LCDPs.

Forensic linguistics is an emerging discipline that is used when documents of any kind become the subject of an investigation and thus concerns criminal offenses such as stalking, blackmail, hate postings and defamation. In addition, anonymous tips, letters of confession and manifestos can also be the focus of analyses. If, as is often the case in such investigations, the only lead to the perpetrator is a linguistic one, forensic linguistics can determine characteristics of unknown authors, compare them to other texts of possible suspects and create language profiles for further investigation. As these analyses have to be carried out manually by experts, their current use is limited. It is therefore particularly important to know in which situations experts should be consulted - and this is precisely where this project comes in. The “TXT - Language as a Trace” project aims to create an AI-supported analysis tool that examines texts to determine whether in-depth analyses by experts are possible and worthwhile. In addition, a preliminary assessment will be made whether a similar linguistic trace already exists in the database, which could then be subjected to further analysis by experts. As a data basis for this project, the handwritten CV collection of the Document & Handwriting Investigation Unit in the Department of Forensic Science of the Criminal Intelligence Service Austria (BK) in the Federal Ministry of the Interior (BMI) will be digitized and supplemented by further incriminated texts. Methodologically, this goal is to be achieved through the use of machine learning techniques, whereby an AI-based tool can make a time-efficient statement in these two areas whether an analysis is possible and whether comparison texts should be analyzed in greater depth.

Knowledge Risks in Industry 4.0 Supply Chains: A Legal and Technical Perspective in collaboration with Prof. Dr. Johannes Zollner from the Institute for Corporate Law and International Business Law and funded by the profile-forming area Smart Regulation

The cross-organizational exchange of data in the context of digitalization brings with it many advantages as well as new risks. The risk of unintentional disclosure of competition-critical knowledge in the context of data exchange is particularly noteworthy. The disclosed knowledge could be used by partners in the supply chain to their own advantage. However, as the knowledge advantage is a - if not the - decisive competitive advantage for many companies, especially small and medium-sized enterprises (SMEs), this risk must be considered substantial. Together with the Institute for Corporate Law and International Business Law, the protection of knowledge in cross-organizational supply chains is being investigated. The following questions are considered from both a legal and a technical perspective: What legal measures and instruments are available to minimize the risk of inappropriate use of data? To what extent can existing technical measures be applied or adapted for these data-based collaborations? And to what extent is it possible and sensible to combine legal and technical measures?

The project has a duration of 4 years and started on 01.06.2019.

Project team members:

• Thalmann, Stefan, Univ.-Prof. Priv.-Doz. Dr.
• Zeiringer, Johannes, BSc MSc

The project "Digital skills development for young people using intelligent learning software with a focus on cybersecurity and responsible data handling", or "Digital?Sicher!", is dedicated to the effects of digitalization on the development of professional skills. In particular, the safe and responsible use of information and communication technologies in cyberspace is to be researched and missing skills are to be taught. The aim is to raise awareness of this issue and increase the general level of basic digital education, particularly with regard to cyber risks.

The BANDAS Center is involved in the project, which has been running since January 2020 and is supported by the Styrian Future Fund, as a partner!

Further information on the project can be found here.

Artificial intelligence (AI) is now widely used in HR management. The areas of application range from job interviews with the help of chatbots to the suggestion of further training courses and the automated (pre)selection of applicants. There is great uncertainty among employees and HR practitioners due to the lack of transparency about the underlying models and the data basis used for decisions that are often important for employees and have far-reaching consequences (recruitment, promotion, discipline, etc.).

The planned project aims to create an information video and develop a seminar concept for the further training of works councils to enable them to competently represent the concerns of employees in these matters, so that works councils are informed about possible uses as well as existing and ongoing regulatory options for AI applications.

In close consultation with employees from affected companies and the Styrian Trade Union Federation (ÖGB Steiermark), the project team is made up of researchers from the Business Analytics and Data Science Center, Karl-Franzens University Graz and the Human Resource Management Group, Paris Lodron University Salzburg, who will determine the information needs of the works councils in order to design a tailor-made offer. The project team at the BANDAS Center includes Prof. Stefan Thalmann, Dr. Jürgen Fleiß and Christine Malin.

Under the following link you will find all information about the EU-funded ERASMUS+ project VOIL - Virtual Open Innovation Lab:

To the website of the VOIL project

At the end of June 2022, the Erasmus+ project "Collaborative development of AI capabilities in SMEs"(CoDeAI) was approved, which was submitted under the leadership of the University of Graz with partners from Germany, Greece, Portugal and Spain. Prof. Stefan Thalmann and Johannes Zeiringer took up the previous VOIL project and initiated a follow-up project together with the partners.

The project aims to build on the VOIL platform by proposing further developments and offering added value for SMEs. In the course of the VOIL project, it has become apparent that students who are future employees of SMEs need knowledge about new Artificial Intelligence (AI) technologies. AI is one of the key technologies of digital transformation that enables huge improvements in the manufacturing and service industries and is an important enabler for data-driven business models. Large companies have already built up AI capabilities and are benefiting from improved business processes and new data-driven business models. Micro, small and medium-sized enterprises (SMEs) are lagging behind as they are not able to build the necessary AI capabilities, which has a huge impact on their innovation power and thus their future prospects. As AI-powered tools become more widespread in all areas of business, SMEs must increasingly understand these relationships, make the necessary efforts and adopt these technologies. Therefore, it is important that students are already trained as potential future employees or founders of SMEs with AI capabilities. In the project, an initial case study research will be conducted to look for "European" patterns for the successful adoption of innovative technologies. The results of the case studies will be relevant for both SMEs and students.

The proposed project will be conducted transnationally with higher education partners, students and SMEs across Europe to facilitate collaboration between higher education institutions that have AI skills and SMEs that need to build AI capabilities. Therefore, we want to address the identified challenges as follows: (1) The existing VOIL platform will be extended with a training package for AI in SMEs that will provide the basic AI skills. (2) Based on a study on the use of AI in SMEs using current productivity tools designed to increase human productivity, such as AutoML, use cases and success stories will be presented, (3) based on these use cases and success stories, a benchlearning framework will be developed that takes AI skills into account, and (4) an innovation environment will be created that supports collaboration between universities, SMEs and LEs, taking into account (in addition to VOIL technologies) the specific needs of AI.

The starting date for the two-year project was October 01, 2022.

With the aim of creating a catalog of requirements for the successful use of AI in personnel selection, the project "The application of artificial intelligence (AI) in personnel selection: Requirements for the traceability of decisions and confidence building"(in short: AI in personnel selection), an interview study with Austrian HR managers, a questionnaire study on the perception of AI and a design and experiment study with a visualization prototype were conducted. The project results were recorded in the form of a research report, which has now been published by AMS Austria (funding body). You can access the project's research report via this link.

The project team comprises members of the Department of Work and Organizational Psychology and the Center for Social Research at the University of Graz, whereby the project team members at the BANDAS Center are Prof. Stefan Thalmann, Dr. Jürgen Fleiß and Christine Malin.

Im Rahmen dieses Forschungsprojekts werden die Auswirkungen und Herausforderungen der Automatisierung von maschinellem Lernen (AutoML) untersucht. AutoML ermöglicht es Fachexpert:innen ohne tiefgehende Kenntnisse in maschinellem Lernen (ML), spezifische Modelle für ihre Anwendungsfälle zu erstellen, was die Nutzung von ML in Unternehmen revolutionieren könnte. Diese Technologie wirft jedoch auch ethische Fragen auf, da AutoML von Laien bedient werden kann, was Risiken verschärft und die Kontrolle erschwert. Das Projekt erfasst den Einsatz von AutoML in der steirischen Wirtschaft, analysiert Risiken und Potenziale und entwickelt ein Bewusstseinsbildungstool (Ethik-Kompass) für eine verantwortungsvolle Nutzung.

Die Steiermark ist Vorreiterin in der Pflege von Menschen mit Demenz. Eine zeitige Früherkennung und gezieltes Training durch AI-gestützte Neurotechnologien können Betroffene, Angehörige und Pflegepersonal unterstützen. Sie setzen am Gehirn an und ermöglichen es Betroffenen länger selbstbestimmt zu leben. Beim Einsatz von Neurotechnologien ist die Wahrung der Menschenwürde zentral. Dieses interdisziplinäre Forschungsprojekt erforscht die ethischen, psychischen, rechtlichen und gesellschaftlichen Chancen und Risiken von Neurotechnologien und formuliert Empfehlungen für steirische Akteur:innen.