Date
Thursday November 2, 2023 from 9:30 AM to 6:30 PMLocation
EindhovenAddress
Noord Brabantlaan 1AOrganizer
Eindhoven AI Systems InstituteCo-organizer
AI-hub Brainport | Province of North Brabant | AI Innovation CenterPrice
FreeAI Summit Brainport 2023 is SOLD OUT! Unable to join the live event? You are welcome to watch the livestream of the plenary opening and the Research track.
Human-Centered AI
After the success of the first edition with over 500 participants, we join forces again with AI Hub Brainport and the Province of North Brabant. The next edition of AI Summit Brainport with the theme Human-Centered AI will take place in Evoluon, Eindhoven. Ready to meet researchers, industry leaders and other AI enthusiasts in Brainport Eindhoven and enhance your AI knowledge and skills? You are welcome to join the AI Summit Brainport on Thursday the 2nd of November.
Date: Thursday 2nd of November 2023
Time: 10:00h - 18:00h (doors open at 09:00h)
Location: Evoluon, Eindhoven
Please note: participation is free of charge, but registration is required. If, for any reason, you find yourself unable to attend the AI Summit Brainport, and you did register we urge you to cancel your ticket. A fee of € 25,- will be charged in case of no-show.
EAISI Research Track
After a plenary start with a keynote by Wijnand IJsselsteijn and a conversation about the EU AI Act with experts, we offer four different tracks; Research, Expert, Adoption and Start-up track.
In the EAISI Research track, TU/e researchers and partners will present their latest findings, specifically around the theme of human-centered AI. Because, not coincidentally, EAISI specifically leverages the university's expertise in Human-Computer Interaction and Ethics as a core competence, aside of Data Science and Engineering Systems.
Join the discussions and get to know in detail what is happening in the center of Brainport’s AI research.
Program
Plenary session
| Day chair: Jolanda ter Maten | |||
|---|---|---|---|
| 09:00 | Doors open: Coffee & expo | ||
| 10:00 | Opening | Martijn van Gruijthuijsen Carlo van de Weijer | |
| 10:10 | Round table | Short introduction to the EU AI Act by Susan Hommerson, followed by a conversation with experts: Jelle Donders Koen Holtman Wouter van der Loop Susan Hommerson | EU AI Act | The impact of AI governance Engage in thought-provoking conversations on the impact of AI governance alongside an interesting panel including legal experts and Brainport partners. |
| 10:35 | Keynote | Wijnand IJsselsteijn Full Professor department IE&IS – Cognition and Affect in Human Technology Interaction | The Imitation Game Revisited: Questioning the Metaphors We Use to Understand AI |
| 11:00 | Coffee break | ||
EAISI research track - Morning program
| 11:20 | Welcome | Wim Nuijten | |
| 11:30 | Research talk | Emilia Barakova Assistant Professor department Industrial Design – Future Everyday TU/e | Pain and stress management using smart connected systems of Social Robots and Wearables |
| 11:50 | Short research talks | Diego Morales Perez Maryam Azani Kees Maton | Systems that care about what we care about: Companies and the Value Alignment Challenge
Human decision-making in production planning systems: How do superior information and systematic bias impact performance?
How do employees experience their collaboration with AI in decision-making, and why is this important? |
| 12:15 | Research talk | Frauke Behrendt | Governance with AI: Shaping sustainable futures and decision making |
| 12:40 | Duo research talk | Regina Luttge Bert de Vries | BayesBrain - The World's First Hybrid Neuro-Silicon AI Computer |
| 13:00 | Lunch break | ||
EAISI research track - Afternoon program
| 14:00 | Welcome back |
| |
| 14:05 | Research talk | Merel Noorman Assistant Professor AI, Robotics and STS at Tilburg University | AI and energy justice |
| 14:25 | Research talk | Vlasta Sikimić | Values and automated grant review |
| 14:50 | Research talk | Rianne Conijn Assistant Professor Human Technology Interaction at TU/e | Optimizing human-AI collaboration in education to support learning |
| 15:15 | Short research talks by PhD's | Olaf Adan Pei-Ying Lin | Moving beyond the prompt
Our Respectable Creative Non-Human Partner in Textile – Embracing AI Surprises |
| 15:35 | Research talk | Gerard Schouten Leading lector at Knowledge Center Applied AI for Society, Fontys | Create impact with trustworthy AI - The case of assessing biodiversity |
| 16:00 | Central closing by Koert van Mensvoort | Creative Director of next nature Network & Carlo van de Weijer | General Manager EAISI | ||
| 16:20 - 18:00 | Exposition, networking & drinks | ||
Abstracts
WIJNAND IJSSELSTEIJN | Full Professor - Human-Technology Interaction, Industrial Engineering & Innovation Sciences, TU/e
The Imitation Game Revisited: Questioning the Metaphors We Use to Understand AI
In the world of artificial intelligence, metaphors have long been our guiding lights, shaping our perception and understanding of AI systems. From "deep learning" to "neural networks," these metaphors help bridge the gap between complex technology and human comprehension. However, as AI technology advances, it becomes increasingly vital to scrutinize the metaphors we employ, and their implications. The language we use to describe AI and our interactions with artificially intelligent systems, shapes our understanding and the public discourse about what AI systems are, can do, and ought to do. In his talk, Wijnand IJsselsteijn will explore some of the ways in which these metaphors influence our perception of AI and explore whether they still serve as accurate representations.
Wijnand IJsselsteijn has an active research program on the impact of media technology on human psychology, and the use of psychology to improve technology design. His focus is on conceptualizing and measuring human experiences in relation to digital environments (immersive media, serious games, affective computing, personal informatics) in the service of human learning, health, and wellbeing. Wijnand IJsselsteijn has a background in artificial intelligence and cognitive neuropsychology (MSc, Utrecht University). He obtained his PhD in 2004 on the topic of telepresence. He is scientific director of the interdisciplinary Center for Humans and Technology at TU/e, which explicitly focuses on people- and value-centred perspectives of technology understanding, engineering, and design.
EMILIA BARAKOVA | Assistant Professor - Future Everyday, Industrial Design, TU/e
Pain and stress management using smart connected systems of Social Robots and Wearables
Numerous user groups, including adults with dementia, intellectual disabilities, and young children in postoperative care, face challenges in accurately expressing their stress, , pain, and worries. To address these issues, we combined robots, wearables, and mobile apps, to transform social robots into effective tools for promoting positive affect, and distraction from pain. In our robot-assisted therapies, we integrated contextual aspects such as a hospital or care home settings, along with the active involvement of caregivers and parents. Through this multidimensional approach, we aimed to provide tailored support to diverse user populations and facilitate their well-being and quality of life.
Emilia Barakova is Assistant Professor of Socially Intelligent Systems. She is the head of the Social Robotics Lab and leader of the Physical and Social Rehabilitation educational squad. Barakova is an expert in the field of embodied social interaction with and through technology, social, cognitive and brain-inspired robotics, modeling expressiveness of movement and designing technologies for individuals in social isolation and special needs groups. She has specialized in combining methods from neuro- and cognitive sciences, robotics, and computational intelligence to model social behavior. Barakova has organized three international conferences (1 ACM, 2 IEEE and has been invited as Keynote speaker at many international conferences. She has served as an intermediate director of German-Japanese Research Lab in Japan. → Back to program
DIEGO MORALES PEREZ | PhD Philosophy & Ethics, Industrial Engineering & Innovation Sciences, TU/e
Systems that care about what we care about: Companies and the Value Alignment Challenge
Artificial intelligence (AI) is a technology that has had impressive advancements in its ability to process data, employ natural languages, and to make decisions, reaching levels of performance equal to, or higher than, humans. As these systems are increasingly becoming socially and industrially embedded, care is required to ensure that they select and prioritize decisions or actions that are in line with the values and well-being of users, companies, and societies as a whole.
MARYAM AZANI | PhD Operations planning, Accounting & Control, Industrial Engineering & Innovation Sciences, TU/e
Human decision-making in production planning systems: How do superior information and systematic bias impact performance?
Production planning systems support planners by providing information and suggestions. An effective system doesn't have to be complex; it should guide planners towards efficient production plans. Planners can leverage their expertise, intuition, and information beyond what the system offers, resulting in superior plans. However, cognitive biases and limited understanding of stochasticity hinder performance. This project explores the interaction between production planning systems and human decision-makers in stochastic environments and provides guidelines for designing behaviourally compatible systems.
KEES MATON | PhD Human Performance Management, Industrial Engineering & Innovation Sciences, TU/e
Attitudes towards (AI) Augmented Decision-Making at work; an Exploration and Qualitative Validation of Experiential Components
Succesful augmented decision-making (i.e., human-AI collaboration), requires a deep involvement of employees with the AI-system, to know when to and not to intervene. Such a state depends on employees’ positive experiences. However, research lacks identification of employees’ experiential evaluations with augmented decision-making. By performing 17 interviews among AI-users from three organizations, this research aims to develop a framework of factors associated and behavioral outcomes of experiential attitudes towards augmented decision-making. Practical recommendations and future research steps are discussed.
FRAUKE BEHRENDT | Associate professor Technology, Innovation & Society, Industrial Design, TU/e
Governance with AI: Shaping sustainable futures and decision making
This presentation focusses on the role of AI in governance and decision making with regards to sustainable futures, using Mobility as a Service (MaaS) as case study. It combines field work and a narrative literature review. The presentation contributes a novel approach towards understanding the role of AI in governance processes, and implications for social and environmental sustainability.
Dr Frauke Behrendt is Associate Professor in Transitions to Sustainable Mobility at the Technology, Innovation and Society Group at TU/e. Her expertise is on smart and sustainable mobility as well as digital/data culture and society. Behrendt’s research is located at the intersection of three key themes: Mobility, Sustainability and Digitalization. It engages at the local, national and international scale, investigates a range of modes, explores the past, present and future – and considers the user experience, the design and industry perspective, and the policy landscape – of how we can move towards radically more sustainable mobilities. → Back to program
REGINA LUTTGE | Associate Professor department Mechanical Engineering - Microsystems
BERT DE VRIES | Full Professor department Electrical Engineering - Signal Processing Systems
BayesBrain - The World's First Hybrid Neuro-Silicon AI Computer
Computation in biological brain tissue consumes about a million times less power than silicon-based AI systems. Motivated by this fact, this project aims to develop the world’s first hybrid neuro-silicon AI computer, introducing a fundamentally new paradigm of AI computing. We will combine an in-silico Bayesian control agent with neural tissue hosted by a microfluidic Brain-on-Chip (BoC) that together form a hybrid learning system capable of solving real-world AI problems.
Regina Luttge studied Applied Sciences in Germany and worked as an engineering researcher at Institut für Mikrotechnik in Mainz for nearly five years prior to starting her PhD studies in Microsystems Technologies at Imperial College, London, in 1999. In 2003 she received her PhD from the University of London on the development of fabrication technology for micro-optical scanners. Switching her research interest to microfluidics applications, Luttge went on to work at the University of Twente MESA+ Institute for Nanotechnology. Initially as a senior scientist and later as an Assistant Professor. She was appointed Associate Professor in the TU/e Microsystems Group in 2013. Regina Luttge is Chair of Neuro-Nanoscale Engineering at Eindhoven University of Technology. Her research line investigates and develops microsystems for medicine and biology with integrated bio-inspired functionality mediated by shrinking structural dimensions and controlling material properties at the nanoscale applying emerging and established micro-nanofabrication methods.
Bert de Vries received M.Sc. (1986) and Ph.D. (1991) degrees in Electrical Engineering from Eindhoven University of Technology (TU/e) and the University of Florida, respectively. From 1992 to 1999, he worked as a research scientist at Sarnoff Research Center in Princeton (NJ, USA). Since 1999, he has been employed in the hearing aids industry, both in engineering and managerial positions. De Vries was appointed part-time professor in the Signal Processing Systems Group at TU/e in 2012. His research focuses on the development of intelligent autonomous agents that learn from in-situ interactions with their environment. And on using these agents to automate the development of novel signal processing algorithms, see biaslab.org. Our research draws inspiration from diverse fields including computational neuroscience, Bayesian machine learning and signal processing systems. A current major application area concerns personalization of medical signal processing systems such as hearing aid algorithms. In the past, De Vries contributed to research projects over a wide range of signal and image processing topics, such as word spotting, financial market prediction and breast cancer detection from mammograms. → Back to program
MEREL NOORMAN | Assistant Professor AI, Robotics and STS at Tilburg University
AI and energy justice
Artificial Intelligence (AI) techniques are increasingly used to address the challenges of the energy transition. Such challenges include the integration of renewable and more volatile energy sources as well as the increased demands on the limited network capacity due to the growing electrification. AI techniques may offer promising solutions, but they also raise multiple concerns. One key concern is how AI will affect energy justice. This talk will look at what the energy justice implications are of the use of AI in smart electricity systems and what these implications mean for the design and regulation of these technologies.
Merel’s research interests include the governance and regulation of AI and robotics, with a particular focus on the responsible development and use of complex intelligent technologies. In her current work she explores the relations between AI and democracy. She studied AI and science & technology at the University of Amsterdam and Edinburgh University and received her PhD from Maastricht University. Since then, she has co-initiated and worked on various research projects in the U.S. and the Netherlands, funded by the National Science Foundation, NWO-MVI, and the EU 5th framework program, looking at the ethical and social aspects of complex and intelligent computer technologies. She has also worked as advisor for the Dutch Council for Social Development (Raad voor Maatschappelijke Ontwikkeling) and was managing director for the software company VicarVision. → Back to program
RIANNE CONIJN | Assistant Professor - Human-Technology Interaction, Industrial Engineering & Innovation Sciences, TU/e
Optimizing human-AI collaboration in education to support learning
How can we avoid misuse of AI in education? How can we ensure that AI supports learning? In this talk, I will discuss how we can employ a human-centered design approach to improve human-AI collaboration in higher education. Specifically, I will detail how to provide students and teachers with meaningful insights in the underlying algorithm and its limitations, such that they can use the AI more effectively.
Rianne Conijn is an assistant professor in the Human-Technology Interaction group at Eindhoven University of Technology, the Netherlands. Her research interests include the analysis and interpretation of (sequences of) online and offline learning behavior to improve learning and teaching (learning analytics). In her research, she combines data-driven approaches (such as machine learning and statistical modeling), with theory and human-centered design.→ Back to program
OLAF ADAN | PhD Systemic Change, Industrial DESIGN, TU/e
Moving Beyond the Prompt
In this talk, Olaf introduces CollEagle, an AI-enabled tabletop system that takes a conversation-centric approach to integrating AI into collocated collaboration. Implementing speech recognition, keyphrase extraction and Named Entity Recognition, CollEagle identifies, collects, and generates subject matters from ongoing conversations, and presents these as a stream of post-it notes that can be curated as part of the natural conversation flow. Rooted in conversation, the tangible and collaborative form of interacting with AI-generated content presented in CollEagle offers a glimpse into the future of human-AI interaction.
PEI-YING LIN | PhD Human Technology Interaction, Industrial Design, TU/e
Our Respectable Creative Non-Human Partner in Textile – Embracing AI Surprises
For designers and craftsman, working with materials is requires listening and collaborating to the material. Materials have their own agency, and so does machines. With development of emerging generative AI, this research questions what if we bring together materials, machine, AI, and human for creative collaboration? What are the ways to unpack the complexity of such collaboration and how new design methodologies would emerge through such assemblage?
GERARD SCHOUTEN | Leading lector at Knowledge Center Applied AI for Society, Fontys
Create impact with trustworthy AI - The case of assessing biodiversity
In this presentation Gerard Schouten introduces a framework for creating societal and environmental impact with trustworthy AI. On top of human-centric quality aspects of trustworthy AI – such as model robustness, explainability, unfair bias, controllability, etc. – the framework consists of transdisciplinary process elements as a major condition for success. The framework is illustrated with a case that uses AI (computer vision) to gauge biodiversity, in particular wildflower richness and abundance. For this a unique expert-annotated reference dataset, with over 2500 images holding 150+ flowering plant species, is collected ‘in the wild’ (roadsides, urban areas, open fields) around the city of Eindhoven. The AI solution can be used by researchers and policy makers for large-scale automated wildflower monitoring and as an input to assess the value of so-called eco-systems services. The model can be embedded in a citizen science app to engage people for planet health.
Gerard Schouten is professor at the Fontys University of Applied Sciences, school of ICT and leads the Fontys Knowledge Center Applied AI for Society. His research topic is AI and data. His interests include machine learning, deep learning, and in particular the creation of impact with trustworthy AI – explainable, fair and ‘green’ – for people and planet. Gerard is a valued member of the data advisory board of the province of Noord-Brabant. He also holds a position as guest researcher at the Naturalis Biodiversity Center where he focuses on applied AI for biodiversity.
Gerard graduated in physics, and has a PhD in the field of cognitive science (TU/e). He worked many years as a senior scientist for Philips Healthcare where he specialized in medical image processing and X-ray dose management. He has extensive experience in managing innovation projects and participated in many European research projects. → Back to program