HAII5.0: Embracing Human-Aware AI in Industry 5.0

This workshop will take place at ECAI 2024, on Saturday 19 October 2024 in Santiago de Compostela. Workshop proceedings are available open access at CEUR-WS at https://ceur-ws.org/Vol-3765/.

Invited Speakers

Jerzy Stefanowski, is a full professor at Poznan University of Technology Institute of Computing Science, and leads the university’s Machine Learning Lab. He is a Member of the Polish Academy of Sciences since 2021, and the Vice-President of the Polish Artificial Intelligence Society.

He will give a talk on “Interaction with humans while explaining black box machine learning models — cases of using prototypes, counterfactuals, rules and other forms.”

Kerstin Bach, is a full professor in Artificial Intelligence at the Department of Computer Science at NTNU. She is currently research director of the Norwegian Research Center for AI Innovation (NorwAI), deputy head of the Data and Artificial Intelligence group, and core team member of the Norwegian Open AI Lab. She was awarded a Dr. rer. nat. (summa cum laude) in Computer Science from the University of Hildesheim, Germany in 2012. Kerstin’s main research interests are data-driven decision support systems as well as knowledge-intensive Case-Based Reasoning. She is the chair of the German Society for Computer Science’s Special Interest Group on Knowledge Management, and a board member of the Norwegian AI society.

Final Workshop Programme

Time Slot	Presentations
9:00 – 9:10	Welcome & Opening Session
9:10–10:10	Invited talk: Jerzy Stefanowski
10:10-10:30	* eXplainable Random Forest, Shlomit Gur, Guy Amit (IBM Research)
10:30–11:00	Coffee break
11:00–12:30	* SHAP-Driven Explainability in Survival Analysis for Predictive Maintenance Applications, Monireh Kargar, Zahra Kharazian, Ioanna Miliou, Tony Lindgren (Stockholm University) * Understanding the Impact of Unexpected Cobot Movements on Human Stress Levels: A Time Series Classification Task, Lior Shilon (SCE), Vladyslav Shevtsov (SCE), Nadia Schillreff (OVGU), Anne Rother (OVGU), Shlomo Mark (SCE), Myra Spiliopoulou (OVGU) * Invariant Feature Selection for Battery State of Health Estimation in Heterogeneous Hybrid Electric Buses, Yuantao Fan, Mohammed Ghaith Altarabichi, Peyman Mashhadi, Sepideh Pashami, Slawomir Nowaczyk (Halmstad University) * Human-Aware design for transferring knowledge during human-AI co-learning, Dimitrios Koutrintzes, Christos Spatharis, Maria Dagioglou (Demokritos)
12:30–14:00	Lunch break
14:00–15:00	Invited talk: Kerstin Bach
15:10–15:30	* Towards differentiating between failures and domain shifts in industrial data streams Natalia Wojak-Strzelecka (ArcelorMittal), Szymon Bobek (JU), Grzegorz Nalepa (JU), Jerzy Stefanowski (PUT)
15:30–16:00	Coffee break
16:00–17:00	* Evaluating Multi-task Curriculum Learning for Forecasting Energy Consumption in Electric Heavy-duty Vehicles, Yuantao Fan (Halmstad University), Zhenkan Wang (Volvo Group), Sepideh Pashami (Halmstad University), Slawomir Nowaczyk (Halmstad University) * LanViKD: Cross-Modal Language-Vision Knowledge Distillation for Egocentric Action Recognition, Yizheng Sun, Hao Li, Chenghua Lin, Riza Batista-Navarro (University of Manchester) * Augmenting train maintenance technicians with automated incident diagnostic suggestions, Georges Tod (SNCB)
17:00–17:30	Summary & Closing Session

Important dates

Paper submission opens: Wednesday, 17 April 2024
Paper submission deadline (extended): ~~Thursday, 6 June 2024~~ Sunday, 23 June 2024
Acceptance notifications: ~~Monday, 15 July 2024~~ Wednesday, 31 July 2024
Camera-ready submission deadline: Wednesday, 7 August
Workshop schedule published: Tuesday, 13 August 2024
ECAI early registration deadline: Monday, 19 August 2024
The workshop: Saturday, 19 October 2024

In addition to regular paper submissions, we will consider accepting interesting papers rejected from the main conference. Potential authors should submit a request for their rejected paper to be considered by 10 July 2024, and can expect a decision by 25 July 2024.

Submission guidelines

Workshop papers will be published in CEUR Workshop Proceedings. We suggest using this Overleaf template. Detailed formatting instructions can be found here. There is no strict page limit, but we recommend submissions to be in the 12-15 pages range.

Submission site.

Programm committee

Abhishek Shukla, Principal Software Engineer, Dell Technologies, USA
Chi-Ching Hsu, ETH Zurich, Switzerland
Christian Beyer, Otto-von-Guericke University, Germany
Florent Forest, EPFL, Switzerland
Han Sun, EPFL, Switzerland
Hao Dong, ETH Zurich, Switzerland
Marco Ragni, TU Chemnitz, Germany
Maria Riveiro, Professor, Jönköping University, Sweden
Myra Spiliopoulou, Otto-von-Guericke-University Magdeburg, Germany
Olga Fink, EPFL, Switzerland
Slawomir Nowaczyk, Halmstad University, Sweden
Stephan Husung, TU Ilmenau, Germany
Thorsteinn Rögnvaldsson, Professor, Halmstad University, Sweden
Zheng Zhou, Xi’an Jiaotong University, China

Workshop organisers

Slawomir Nowaczyk, CAISR, Halmstad University, Sweden, slawomir.nowaczyk@hh.se
Myra Spiliopoulou, Otto von Guericke University, Germany, myra@ovgu.de
Marco Ragni, Chemnitz University of Technology, Germany, marco.ragni@hsw.tu-chemnitz.de
Olga Fink, EPFL, Switzerland, olga.fink@epfl.ch

Contact the workshop at haii5-workshop@googlegroups.com

Workshop description

The workshop on Embracing Human-aware AI in Industry 5.0” is designed to delve into the evolving landscape of artificial intelligence in the industrial sector, placing emphasis on how AI should reflect and respond to human activities and demands. As industries worldwide transition into the realms of Industry 5.0, integrating AI technologies becomes not just an asset but a necessity. This shift heralds unprecedented opportunities and challenges, where the interplay between human workers and advanced AI systems takes centre stage. Our workshop aims to explore this critical intersection, focusing on how AI should be designed, implemented, validated and managed in a human-aware way. Human-aware AI calls for novel solutions that allow humans and machines to collaborate seamlessly within the complexities of the real world, driving sustainability, resiliency, and benefits to people and society. In business branches like commerce, the need for human-aware AI is already taken for granted. Industry, including product design, manufacturing, aftermarket, maintenance and all forms of industrial engineering, seems to lag behind since the focus for many years has been pure automation. By delving into these topics with a human-aware lens, this workshop will significantly contribute to the ECAI conference, offering scientific discussions that align well with its themes and goals.

The workshop invites original work in the area and will feature a series of presentations from the contributing participants, two keynote talks, open discussions, and interactive panel sessions led by experts in the field of AI for Industry 5.0. We solicit submissions on a wide array of topics, ranging from ethical considerations and human-AI collaboration to AI-driven process optimisation, decision support systems, integration of domain and expert knowledge in AI algorithms and the future of work on the industrial floor. The workshop intends to foster a multidisciplinary dialogue on how AI can be human-aware and effectively integrated into various industrial processes by bringing together academicians, industry professionals, and AI practitioners. Particular emphasis will be placed on practical applications, challenges, and the latest research findings in the field. Our objective is to provide a comprehensive platform for participants to gain insights into the current trends, potential benefits, and challenges associated with the deployment of AI in the industry in collaboration with and supporting (not replacing) humans – even on a cognitive level. The workshop is expected to spark innovative ideas, encourage collaborations, and contribute significantly to advancing human-aware AI in the industrial sector. Through this workshop, we aspire to shape the future of the industry where AI not only enhances efficiency and productivity but also aligns seamlessly with human needs and values.

The workshop will consist of two invited talks, technical presentations of contributed papers (primarily oral; however, we are open to the possibility of organising a poster session in case of a large number of high-quality submissions), and a panel discussion to summarise the discussions. Papers presented at the workshop shall be submitted to CEUR-WS.org for online publication.

List of relevant topic areas

Human-centered AI Design in manufacturing
AI for situation awareness in manufacturing
AI for situation awareness in human-robot teams
Recognising human uncertainty
Decision support systems
Integration of domain and expert knowledge in AI algorithms
Predicting human movement
Promoting safety in human-robot interaction
Collaborative AI and Human Modeling
Predictive AI in Human Interaction
Ethical Considerations in AI Deployment
Human-AI Collaboration
AI in Decision-Making Processes
Ergonomics and AI
AI for Predictive Maintenance
Explainable Predictive Maintenance (XPM)
AI-Driven Process Optimization
Training and Education for Industrial AI
AI in Quality Control
AI and the Future of Work
Explainable AI (XAI) in Industry
Human Factors in AI System Design
Collaborative Robotics and Automation
Challenges in Implementing AI in Industry

Information about the organisers

Slawomir Nowaczyk

Sławomir Nowaczyk is a full professor in Machine Learning at the Center for Applied Intelligent Systems Research, Halmstad University, Sweden and a Research Leader for the School of Information Technology. He has a PhD degree from the Lund University of Technology. During the last decade, his research focused on knowledge representation, data mining and self-organising systems, especially in large and distributed industrial data streams, including unsupervised modelling. He was involved, often in leading roles, with over ten different industrial partners in over twenty research projects related to predictive maintenance, diagnostics and self-monitoring. He is a board member of the Swedish AI Society, served as a reviewer for 30 journals and 70 conferences, and has extensive experience in organising events, for example, the Scandinavian Conference on Artificial Intelligence 2015 in Halmstad; Transparent, Explainable and Affective AI in Medical Systems workshop at AIME 2019; three editions of IoT Streams for Predictive Maintenance tutorials and workshops at ECML 2019, 2020 and 2022; Summer School on Data-Driven Predictive Maintenance for Industry 4.0 and a related special session at DSAA’2021; XAI for Predictive Maintenance tutorial at KDD 2023; and XAI^3 Workshop at ECAI 2023 – which included editing 2-volume Springer proceedings “ECAI 2023 International Workshops,” for eight workshops. Sławomir was also an invited speaker, delivering the talk “Bridging Two Worlds - Navigating Research Frontier and Real-World Relevance” at the 12th International Conference on Prestigious Applications of Intelligent Systems, PAIS 2023, co-located with ECAI 2023.

Myra Spiliopoulou

Myra Spiliopoulou is a full professor and chair of Business Information Systems at the Faculty of Computer Science, Otto-von-Guericke-University Magdeburg, Germany. Her main research is on mining temporal complex data and extracting predictive patterns from evolving objects. One of the core application areas for her research and a constant source of inspiration is health: her work encompasses methods and findings from observational medical data, from clinical studies, from digital health solutions, and from experiments on understanding the process of human and animal learning. She is involved as (senior) reviewer in major conferences on data mining and knowledge discovery, as Action Editor in the Data Mining and Knowledge Discovery Journal of Springer Nature, as Special Editor for survey papers in the International Journal of Data Science and Analytics (JDSA) and as Editorial Board Member for the Artificial Intelligence in Medicine Journal. In 2016, 2019 and 2023, she served as a PC Chair of the IEEE Int. Symposium on Computer-Based Medical Systems (CBMS). In 2023, she served as a senior reviewer for KDD 2023 and ECML PKDD 2023. In 2024, she serves as one of the Journal Track Chairs for ECML PKDD 2024. In May 2023, she received the Distinguished Service Contributions Award for the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD).

Marco Ragni

Marco Ragni is a full professor at the Faculty of Behavioural and Social Sciences and chair of Predictive Analytics, focusing on the intersection of computational cognitive science and artificial intelligence. His research includes predictive modelling of cognitive processes, particularly in reasoning and decision-making, and extends to human-system interaction and cognitive systems in teaming contexts. At TU Chemnitz, Ragni serves as the Head of the Central Institution Man and Technology (MeTech) and is a Faculty Council Member. He is also a member of the Examination Board of the Faculty of Philosophy and has been the Speaker of the Cognition Section within the Artificial Intelligence Section of the German Informatics Society since 2012. He has organised workshops and tutorials at international conferences, including “Predicting the Individual Reasoner” at CogSci 2019 and “Bridging the Gap between Human and Automated Reasoning” at IJCAI 2016 and 2018. In his editorial capacity, he served as an editor for the journal “Künstliche Intelligenz” until 2023. He has also guest-edited for journals such as Cognitive Science and Cognitive Systems Research. His review work includes contributions to journals and conferences like Communications of the ACM, Journal of Artificial Intelligence Research, Cognitive Science, Spatial Cognition and Computation, and Advances in Modal Logic. Ragni’s participation in the Cognitive Science Conference, the German Conference on AI, and the DAAD-funded Logic Summer School in Mongolia reflect his active role in the fields of cognitive science and AI.

Olga Fink

Olga Fink has been an assistant professor of intelligent maintenance and operations systems at EPFL since March 2022. Olga is also a research affiliate at the Massachusetts Institute of Technology. Olga’s research focuses on Hybrid Algorithms Fusing Physics-Based Models and Deep Learning Algorithms, Hybrid Operational Digital Twins, Transfer Learning, Self-Supervised Learning, Deep Reinforcement Learning and Multi-Agent Systems for Intelligent Maintenance and Operations of Infrastructure and Complex Assets. Before joining the EPFL faculty, Olga was an assistant professor of intelligent maintenance systems at ETH Zurich from 2018 to 2022, awarded the prestigious professorship grant of the Swiss National Science Foundation (SNSF). Between 2014 and 2018, she headed the research group “Smart Maintenance” at the Zurich University of Applied Sciences (ZHAW). Olga received her PhD from ETH Zurich and a Diploma in industrial engineering from the Hamburg University of Technology. She has gained valuable industrial experience as a reliability engineer with Stadler Bussnang AG and as a reliability and maintenance expert with Pöyry Switzerland Ltd. Olga has been a member of the BRIDGE Proof of Concept evaluation panel since 2023. Moreover, Olga serves as an editorial board member of several prestigious journals, including Mechanical Systems and Signal Processing, Engineering Applications of Artificial Intelligence, Reliability Engineering and System Safety and IEEE Sensors Journal. In 2018, Olga was honoured as one of the “Top 100 Women in Business, Switzerland”. Additionally, in 2019, she earned the distinction of being recognised as a young scientist of the World Economic Forum. In 2020 and 2021, she was honoured as a young scientist at the World Laureate Forum. In 2023, she was distinguished as a fellow by the Prognostics and Health Management Society.