Artificial Intelligence & Digital Transformation Living Lab

Abstract

Although Artificial Intelligence is tackling an increasing number of tasks and becoming increasingly effective, human understanding of these models, and therefore trust, remains limited.

In this talk, Klaudia Balcer will present how XAI helps to create good quality and explainable models through successive stages of a data science project, focusing on model development and post-hoc explanations. Topics from classical game theory, such as SHAP, and gradient-based methods, such as GradCAM, to modern techniques of explaining models for temporal data or graph neural networks, such as GNNExplainer, will be covered. Klaudia Balcer will discuss the usefulness of these methods from the perspective of the developer, manager, as well as end user, and in various domains, such as medicine, finance, or e-commerce.

Lecturer

Klaudia Balcer is a research and teaching assistant at the Computational Intelligence Research Group (since 2024) at the Institute of Computer Science and a PhD student at the Doctoral School of the University of Wrocław (since 2023). Her research interests focus on methods combining deep and stochastic learning in the context of recommender systems. She is a coauthor of a few research papers, including considering an extension of the Gaussian Hidden Markov Model with embedded hidden states (ICONIP 2023) and explaining Session-based Recommender Systems with Grammatical Evolution (GECCO 2024). She is also active in academic teaching, conference talks, commercial and research projects, as well as international scientific collaboration.

Date: 12 June 2025

Time: 14:00 (CEST)

Format: Hybrid

Registration is required

Abstract

In music, the term artificial intelligence might seem to evoke only the automatic generation of music by a computer. But what is really behind this concept?

How does the scientific community of computer music understand the issue of AI in music? And can we not see these new techniques as a springboard for artistic creativity? In this talk, we will use concrete examples to show you how AI works in music. In particular, we will cover two different tasks: automatic musical transcription (sheet music reading) and timbre transfer (controlling one virtual instrument with another).

Lecturer

Jérémy Cohen is a research fellow at the French National Centre for Scientific Research (CNRS). He works since 2022 at the CREATIS laboratory in Villeurbanne (France). Using applied mathematics, he studies source separation problems for various applications in medical imaging, remote sensing and computer music. He completed his thesis in 2016 in Grenoble at Gipsa-lab and joined IRISA in Rennes in 2018 after two years of research at the University of Mons in Belgium. He is also an elected member of the national scientific research committee of the Institut Sciences Informatiques.

Date: 25 June 2025

Time: 14:00 (CEST)

Format: Hybrid

Registration is required

Abstract

This talk aims to raise awareness about key cybersecurity challenges and the role of artificial intelligence (AI). Through simple examples, we will explore how AI is both a powerful tool for defending systems and a new threat vector, especially with AI-generated phishing and fake websites. The goal is to spark curiosity and highlight the importance of staying informed in an evolving threat landscape.

Lecturer

Mohamed-Lamine Messai is an associate professor at Lumière University Lyon 2 and a member of the SID research team at the ERIC laboratory (University of Lyon 1 & University of Lyon 2). He holds a PhD in computer science and conducts research in cybersecurity, focusing on secure data collection, key management in resource-constrained networks like IoT, and graph-based data analytics for threat detection.

Date: (TBC) June 2025

Lecturer: Profesor Giorgio Satta (University of Padua)

Date: (TBC) June 2025

Lecturer: Profesor Antonio Rodà (University of Padua)

These general lectures will provide an interdisciplinary introduction to key themes in artificial intelligence and digital transformation. They will explore the broader implications of AI in various fields, including technological advancements, ethical considerations, and societal impact. These three sessions will set the stage for the in-depth seminars by offering a foundational understanding of the challenges and opportunities in AI-driven innovation.

About the lecturer:

João Pinheiro Neto is a physicist with experience in computational social science. He focuses on comparing different social media platforms, trying to understand what makes them tick. He believes that data-driven toy models can help design social media platforms that are better and more resilient to manipulation by bad actors. He also believes that timely research can influence decision-making and ultimately pressure platforms into design decisions that do more than blindly chase engagement metrics.

His approach involves large-scale data collection, as well as analysis and modelling using techniques from physics, statistics, and machine learning.  In particular, he currently focuses on large language models as both objects of research (their impact on social media) and as tools for simulating and analyzing social media content.

The rapid advancement of digitalisation and artificial intelligence (AI) is reshaping global trade and business operations. This seminar shall explore the transformative role of AI-driven ideas, innovative capabilities, and digital platforms in international business. We will examine how businesses, particularly SMEs, can harness AI to enhance competitiveness, overcome infrastructural limitations, and expand into global markets. While AI offers significant opportunities, challenges such as data privacy concerns, ethical implications, and digital divides must also be addressed. Through interactive discussions and real-world case studies from Europe and beyond, participants will gain insights into both the opportunities and challenges of AI and digitalisation in an increasingly interconnected world.

About the lecturer:

Dr Adeniyi Olarewaju is a lecturer at Maynooth University Business School, Ireland, specialising in International Business, Strategy, and Entrepreneurship. He serves as the Programme Director for the BBA Business and Languages Degrees and has taught at institutions across Ireland, France, Austria, Mexico, and Nigeria.

An advocate for experiential learning, he integrates case studies, business simulations, and international collaborations (COIL) into his teaching. His research focuses on SME internationalisation, global business strategies, and institutional influences on entrepreneurship, with publications in high-ranking academic journals.

Beyond academia, he has industry experience in healthcare economics and investment research, contributing to portfolio management and digital transformation. He has secured international research funding and is a member of AIB, BAM, and IAM.

Dive into the world of data science without writing a single line of code! This seminar is designed for beginners and professionals alike who want to harness the power of data science in their own fields of expertise. The goal of this seminar is to gain a solid understanding of data science concepts and methodologies, develop practical skills in data analysis and visualisation, and apply data science techniques to solve real-world problems.

Key Topics:

• Introduction to Data Science: What data science is and isn’t, and its relation to artificial intelligence.
• Steps of a Data Science Project: Understanding the workflow of data science projects.
• Data Collection and Cleaning: Techniques for gathering and preparing data.
• Exploratory Data Analysis and Visualisation: Analysing and visualising data to uncover insights.
• Case Studies and Applications: Real-world examples of data science in action.

About the lecturer:

Rocío Romero Zaliz is a researcher at the University of Granada, specialising in computational biology, data science, and computational intelligence. She is affiliated with the Data Science and Computational Intelligence Research Institute (DaSCI) at the University of Granada and serves as the Assistant Director of Research, Transfer, and Teaching at the Centre for Research in Information and Communication Technologies (CITIC-UGR). Her research interests include artificial intelligence applications in medicine and health, as well as the development of metaheuristics and data science methodologies. She authored a book titled “Con-ciencia de datos,” about data science, which makes complex concepts accessible to a broad audience.

This seminar will explore the transformative impact of GenAI on the educational landscape, focusing on an exploration of emerging attitudes and practices regarding integrating GenAI into teaching, learning and assessment environments. The seminar will particularly drill down into key areas of concern for policy-makers, educators and senior administrators. These include:

• Re-evaluating the student-educator trust dynamic,
• Reviewing policy and practice in light of developing assessment challenges to security and validity,
• Identifying and establishing sustainable ethical practices at institutional and national level and;
• Educator Agency in the age of GenAI.

The seminar will highlight examples of approaches to creating supports and guidance for educators at a national level, including the work of the National Academic Integrity Network. The accessibility of GenAI tools has led to rapid adoption of their use in some sectors of education and an almost equally rapid denouncement of their value in other quarters. This has resulted in a fragmentation of trust and trusting relationships between students and educators. While GenAI holds the potential to transform the role of the educator and what teacher agency looks like going forward, it also necessitates the need to prepare for new ethical landscapes and practical assessment challenges. Drawing on recent and current research in the area of Work Integrated Learning, specifically School Placement, the seminar will share initial findings regarding attitudes of student teachers, pupils and teacher educators towards the use of GenAI in teaching, planning and assessment practices. Participants will be given the opportunity to explore the primary immediate or future benefits and/or disadvantages of GenAI for students and educators and consider the gaps that exists between different roles in education regarding the perceptions and understanding of GenAI.

About the lecturer:

Elva Casey is the Director of School Placement in the Froebel Department of Primary and Early Childhood Education, Maynooth University. She previously held the positions of College Registrar and Programme Director at Hibernia College. Her doctoral studies are on the use of partnership models and collaborative practices in School Placement. She has presented at national and international conferences on the areas of Communities of Practice in Higher Level Institutions, ethical and sustainable assessment practices and Work Integrated Learning and the integration of GenAI into teaching, learning and assessment. Elva has extensive senior governance experience including the development of policies and procedures for higher education institutions on the use of GenAI. She has successfully led the institutional response to Quality and Qualifications Ireland institutional and programme level reviews. Research interests and publications include collaborative practices, Work Integrated Learning, academic integrity and the ethical use of GenAI in educational planning and practice.

7 July, 14:00 – 16:00

Ageing in Data (AiD) is a research project housed in the ACT Lab at Concordia University in Montreal. It brings together an interdisciplinary network of scholars from ten countries, community-based activists and organisations. We research how age studies intersect with communications, media studies and critical data studies, and explore how an era of unprecedented digital data-gathering impacts and governs how we grow old in our communities. Our shared commitment to social justice brings us to articulate an impactful, innovative, multi-methodological and collaborative agenda with communities of older adults that respond to pressing societal needs.

The AiD team have devised five interrelated clusters to investigate ageing in data:

• ageing, statistics and public policies
• data ethics, data harms and data justice
• datafied care and sensor-ing age
• digital technology practices, impositions and appropriations
• intersectional ageing and community-driven data

Date: 17:00 – 18:00, 08.07.2024 |  Online

Agata Ferretti, AI Alliance Lead for Europe at IBM Research, is an ethicist and AI governance expert. She has contributed to critical discussions on AI ethics, big data research, and digital health governance. Her work addresses data protection, biomedical AI, and the role of institutional review boards (IRBs) in big data ethics.

About the AI Alliance

The AI Alliance is focused on fostering an open community and enabling developers and researchers to accelerate responsible innovation in AI while ensuring scientific rigour, trust, safety, security, diversity and economic competitiveness.

The AI Alliance brings together a critical mass of compute, data, tools, and talent to accelerate and advocate for open innovation in AI. The main focus areas of the alliance include: Skills & Education, Trust & Safety, Applications & Tools, Hardware Enablement, Foundation Models, and Advocacy.

About IBM

IBM is the world’s largest industrial research organization, with 19 research facilities across a dozen countries. IBM’s mission is to drive innovation that makes the world work better. Committed to business ethics, environmental sustainability, and responsible technology, IBM strives to create global impact while supporting the communities where it operates.

Date: TBD |  University of Graz

Data spaces are transforming the way we share information in large-scale projects. This federated technology enables organisations to exchange data securely and sovereignly, adhering to predefined legal frameworks and establishing clear usage conditions through digital contracts between data providers and consumers. Once the parties agree on the terms by signing a digital contract, data can be transferred directly from the provider’s repository to the consumer’s repository, maintaining sovereignty and control over its usage.

Data spaces rely on standardized protocols that ensure interoperability and trust, and data connectors that facilitates secure data transactions. This data-ecosystem not only optimizes data access across strategic sectors but also drives advancements in machine learning. By enabling access to larger volumes of data, data spaces facilitates the training of ML models and improve the accuracy of their results.

In this talk, Dr. Iacono will explore the key technologies behind data spaces and present a real-world application in precision agriculture, where this technology is used for localized frost prediction, optimizing decision-making in the agricultural sector.

About Know Center

The Know Center is a leading European innovation and research hub specialising in trusted AI and Data Science. Based in Graz, it bridges the gap between cutting-edge research and real-world applications, ensuring that the latest advancements in AI and data science translate into concrete competitive advantages for businesses across industry, energy, and healthcare.

Committed to technological sovereignty and responsible AI, the Know Center plays a crucial role in helping Europe secure control over strategic data while fostering an open and innovation-driven market. By developing state-of-the-art technologies and pioneering research, the centre provides the foundation for tackling the major challenges of the future, benefiting both science and society.

Date: TBD |  Online

Fabian Liessmann is a pharmacist with a robust foundation in pharmaceuticals and biotechnology. Over the past five years, he has dedicated himself to pursuing a PhD in computational chemistry and pharmacy, specialising in the identification of small molecule ligands and peptide binders. His research has focused on uncovering binding modes and optimising them using advanced computational approaches. With a passion for drug discovery, Fabian is at the forefront of combining chemistry, biology, and AI to develop innovative solutions in the pharmaceutical field.

For his presentation, Dr Liessmann will introduce AI-Driven Therapeutics, a startup focused on leveraging AI for protein design and drug discovery. Their work revolves around applying advanced reasoning models to biochemical challenges, aiming to accelerate the development of new therapeutics. But protein design is not only limited to medicinal applications but can help design new proteins, e.g. plastic-degrading, provide novel biomaterials and improve the activity of various enzymes. In the talk, Dr. Liessmann will discuss how AI-powered reasoning can improve molecular design, highlight some of our key findings, explore the broader impact of AI in biomedical research and provide a live demo (hopefully).

About AI-Driven Therapeutics:

AI-Driven Therapeutics specialises in AI-powered protein engineering, developing autonomous systems that efficiently explore vast protein sequence spaces to generate and evaluate novel candidates for various design tasks.

By integrating deep learning, computational techniques, and domain expertise, the program accelerates the drug discovery process, reducing costs and improving the likelihood of identifying effective therapeutics.

The initiative also offers customized AI solutions for pharmaceutical and biotech companies, ranging from research project collaborations to a token-based AI platform, enabling clients to leverage cutting-edge AI tools for protein design and engineering.

Date: 11:00 – 12:00, 12.07.2025 |  Online

This talk draws together ecological psychology insights stemming from James J. Gibson’s concept of affordances and sociological insights from Anthony Giddens’s ideas of reflexivity and the double hermeneutic, to help frame how researchers can examine the intersection of AI advancements and society. Affordance theory, as interpreted in the Information Systems and STS literatures, treats action possibilities as relational: they emerge where agents’ goals and capabilities intersect with the perceived material features (and sometimes the political values) of an environment. Giddens’s double hermeneutic highlights a recursive, systemic feedback loop: as social scientists interpret the world, those interpretations circulate back into everyday practice and reshape the very phenomena under study. These insights, coupled with reflexive monitoring of agency (at the micro level) and institutional reflexivity (at the macro level), provide a temporal lens on how structures and agency co-evolve. By exploring recent empirical evidence on AI development and adoption through these lenses, this talk emphasises how humans and AI systems mutually shape one another across successive design–use cycles as well as how such examinations can reveal future avenues for scholarly research and discussion.

About the lecturer:

Dr Shane McLoughlin is Assistant Professor of Management Information Systems at National University of Ireland (NUI) Maynooth and currently serves as co-director of the undergraduate Placement Program at the MU Business School. Shane is an MU Teaching and Learning Fellow, exploring the responsible use of Generative AI in student assessment for effective learning outcomes. He holds a PhD from the discipline of ‘Information Science’ where he examined how technology mediates and augments social aspects to Human Information Behaviour. More recently, he has researched and taught within the discipline of ‘Management Information Systems’, contributing socio-technical insights into the development, adoption and scaling of disruptive and emerging technologies with a special focus on social innovation. Shane has contributed publications to a variety of MIS related outlets and in 2022, received the Kauffman Best Paper Award at the International Conference on Information Systems (ICIS). He has also provided consultancy to the Council of Europe (COE) and European Union’s (EU) Youth Partnership on issues of social inclusion and digitalisation, which included acting as Rapporteur for their 2018 conference, ‘Connecting the Dots’, as well as authoring several related publications.

Download programme

The full programme is still being finalised. More updates will follow soon!
For questions or more information, contact: lea.pesec@uni-graz.at

The thinkathon workshop, “AI in the Hot Seat: Exploring (un)Trust, Transparency, and Inclusivity,” brought together over 20 academics at the University of Graz to critically examine the challenges and opportunities of AI systems. Organised in collaboration with the Arqus European University Alliance and the Interdisciplinary Digital Lab (IDea_Lab), the event fostered interdisciplinary discussions on AI trustworthiness, ethics, and societal impact.

Key Highlights

• Session 1: Dystopian Future – When AI Goes Wrong

Explored ethical risks, human oversight, and accountability in AI development through thought experiments on potential failures.

• Session 2: Thematic Group Discussions

Participants analysed key AI challenges in trust, bias, fairness, ethics, human-AI collaboration, and socioeconomic impact, proposing strategies for responsible AI deployment.

Key Outcomes

• Identified risks and strategies to enhance AI trustworthiness and transparency
• Developed recommendations for bias assessment and mitigation
• Explored ethical frameworks for responsible AI development
• Examined AI’s socioeconomic impact and policy implications
• Strengthened interdisciplinary collaborations in AI research

This interactive workshop reinforced the academic community’s commitment to shaping ethical and inclusive AI.

The Arqus Hackathons, organised in October and November 2024, exemplified the collaborative spirit of the Living Labs. Participants from five universities developed solutions addressing AI literacy, societal engagement, and sustainability. The winning project, Human Library in a Virtual World, showcased an inclusive and innovative approach to digital storytelling, overcoming physical and geographical barriers. Inspired by the Hacking Innovative Pedagogies (HIP) project, the hackathon also promoted the use of virtual tools for creative problem-solving and interdisciplinary learning.

Each Hackathon provided a set of challenges which have been defined in collaboration with the representatives of the different participating universities. Participants got a chance to view the challenges, propose refinements or propose their challenges after this, they chose their favourite challenge to be working with. The following challenges have been proposed for the hackathons:

• Challenge 1: Basic AI Literacy for Faculty
• Challenge 2: Developing Basic Online Collaboration Skills
• Challenge 3: Adapting to Digital Transformation and E-learning
• Challenge 4: Eco-Friendly Campus Practices
• Challenge 5: Improving Student Mental Health and Well-being
• Challenge 6: Ensuring Accessibility and Inclusivity
• Challenge 7: Digital Tools for Administrative Efficiency
• Challenge 8: Addressing Sustainable Development and Environmental Impact
• Challenge 9: Sustainability in Curriculum
• Challenge 10: Enhancing Societal Engagement and Relevance

Each hackathon spanned over four weeks, structured as follows:

• Week 1: Kick-off Event
  • A one-hour synchronous online event (video recorded for later viewing)
  • Introduction to the event, challenge selection and team formation
• Weeks 2-3: Hackathon
  • Teams work in a virtual environment “Spot” on their chosen challenge
  • Preparation of presentations showcasing their innovative ideas
• Week 4: Closing & Awards
  • A one-hour synchronous online event (video recorded for later viewing)
  • Final solution presentations, evaluation and decision by a jury
  • The judges evaluated the projects based on creativity, feasibility, societal relevance, sustainability and alignment with these themes. The winning team’s solution stood out for its innovative approach, its focus on inclusivity and its commitment to sustainable practices.

The winning project, Human library in a virtual world, was developed by students from the University of Graz, the University of Minho, and the University of Padua, who reimagined the traditional human library concept by moving it to a virtual space. This transition aimed to enhance inclusivity by overcoming geographical, physical and other limitations, making the human library accessible to a broader audience. The project fostered meaningful connections and knowledge-sharing through digital storytelling, offering a forward-thinking approach with significant societal potential. The project also aligned with the Hackathon’s key themes, addressing the challenges of artificial intelligence and digital transformation, climate change and sustainability, and European identity and heritage.

The hackathons have also been supported through Moodle as a platform to house all information and resources for participants and a virtual world “Spot” that was used for the actual time spent working on the hackathon challenge.

The Hackathon’s format was inspired by the Hacking Innovative Pedagogies (HIP) project, led by the University of Graz. This project developed resources, such as the virtual Makerspace used in the Hackathon, to support innovative teaching and learning. For more information about the HIP project, visit: https://hip-project.uni-graz.at/en/about-the-project/

The hackathon was organized by the Artificial Intelligence & Digital Transformation Living Lab, professor Otrel-Cass, and Andrea Holzer, in collaboration with COLIBRI.

The AI&DT Living Lab organises accessible, non-technical lectures to demystify AI concepts for a broad audience, ensuring that people from all backgrounds can gain insights into its principles, challenges, and potential. Topics range from the historical development of AI to its ethical challenges, practical applications in education, and value alignment.

These sessions, held both online and in-person, aim to build AI literacy and promote informed societal discourse.

The second edition of the lecture series starts in June 2025. Read more about it here.

The third edition planned for the winter semester 2025/26. The first edition successfully engaged 280 participants, including students, postdocs, academic and administrative staff, and external stakeholders.

Overview of the first edition:

The first edition of the A Journey Through Artificial Intelligence (JAI) lecture series was a major success, bringing together experts, students, researchers, and professionals, and stakeholders to explore key AI topics.

Topics Covered:

Session 1: Artificial Intelligence – The Long and Winding Road

• Lecturer: José L. Verdegay (University of Granada)
• Location: University of Granada (Salón de Grados) & Online

Session 2: How Do Machines Learn?

• Lecturer: Juan Gómez-Romero (University of Granada)
• Location: University of Granada (Salón de Grados) & Online
• Watch here

Session 3: AI & Education

• Lecturer: Piotr Malak (University of Wrocław)
• Location: Online
• Watch here

Session 4: AI Alignment and Value Forks

• Lecturer: Markus Kneer (University of Graz)
• Location: University of Graz (IDea_Lab) & Online
• Watch here

Key Highlights:

4 Calls for Participation → 280 applications received and accepted

4 Expert-Led Lectures → Covering AI history, machine learning, ethics, and education

Broad Engagement → 280 participants, including:

• 110 students (BA, MA, PhD)
• 7 postdocs
• 109 academic staff members
• 42 administrative staff members
• 12 external stakeholders (industry professionals, policymakers, alumni)

Impact & Outcomes:

• AI Literacy & Knowledge Dissemination – Participants gained insights into AI’s development, applications, and ethical implications.
• Interdisciplinary & International Reach – Attendees from multiple universities, research centres, and organisations worldwide.
• Research & Collaboration – Sessions sparked discussions on AI methodologies, ethics, and potential projects (e.g., Arqus Innovation Fund proposals).
• Open Access Resources – All lectures recorded and made available as Open Educational Resources (OERs) for future learning.