The 2023 symposium of the Norwegian AI Society aims at bringing together researchers and practitioners in the field of Artificial Intelligence from Norway and Scandinavia to present on-going work and discuss the future directions of AI. With the symposium NAIS provides a forum for networking among researchers as well as building links with related research fields, practitioners, businesses, and the public sector.


The main event will be held at the Ulrikes aula. The details of the room and how to find it are in the link. The venue is in the city centre, walking distance from the train station and numerous hotels.

The University of Bergen is the second oldest university of Norway Founded in 1946 on scientific traditions from Bergen Museum (1825). The UiB AI platform coordinates, promotes and makes visible research, education and innovation initiatives in artificial intelligence at the University of Bergen.



Time Day 1: June 14, 2023
12:00-12:15 Opening
12:15-13:15 Keynote I: A Theory for AI Computation?
Speaker: Ana Ozaki
13:15-13:30 Coffee Break
13:30-14:30 Paper group 1:
  • Making Sense of Nonsense: Integrated Gradient-based Input Reduction to Improve Recall for Check-worthy Claim Detection. Ghazaal Sheikhi (Check24 GmbH); Andreas Lothe Opdahl (The University of Bergen); Samia Touileb (University of Bergen); Vinay Jayarama Setty (University of Stavanger).
  • Container-Based IoT Architectures: Use Case for Visual Person Counting. Tiago S. Veiga (Norwegian University of Science and Technology); Hafiz Areeb Asad (NTNU); Frank Kraemer (NTNU); Kerstin Bach (Norwegian University of Science and Technology).
  • Construction of a relevance knowledge graph with application to the LOCAL news angle. Bjørnar Tessem (University of Bergen); Marc Gallofré Ocaña (University of Bergen); Andreas Lothe Opdahl (The University of Bergen).
14:30-14:45 Coffee Break
14:45-15:45 Paper group 2:
  • EvoLP: A Playground for Evolutionary Computation in Julia. Xavier F.C. Sánchez-Díaz (Norwegian University of Science and Technology); Ole J Mengshoel (Norwegian University of Science and Technology).
  • Bayesian Exploration in Deep Reinforcement Learning. Ludvig Killingberg (Norwegian University of Science and Technology); Helge Langseth (Norwegian University of Science and Technology).
  • The AI Act and the risks posed by generative AI models. Dag Elgesem (University of Bergen).
15:45-16:00 Coffee Break
16:00-16:45 Keynote II: Endrocrine digital twin as an example of Medical AI
Speaker: Helge Ræder
17:00-18:30 Public Lecture: Maskiner tenkjer ikkje. Dei reknar.
Speaker: Bjørnar Tessem
Location: Media City Bergen (click for location )
19:45 Dinner: Kranen, bybanen stop Florida (click for location ).
Time Day 2: June 15, 2023
09:00-10:00 Keynote III: AI and Games.
Speaker: Peter Wingaard, CEO Rain AS
10:00-10:15 Cofee break
10:15-11:35 Paper group 3:
  • Automatic detection of manipulative Consent Management Platforms and the journey into the patterns of darkness. Marius Pedersen (University of Bergen); Frode Guribye (University of Bergen); Marija Slavkovik (University of Bergen).
  • Generating Natural Language Dialogues using Large Language Models with Adapters. Ellen Zhang Chang (Norwegian University of Science and Technology (NTNU)); Ole J Mengshoel (Norwegian University of Science and Technology).
  • Analyzing literary texts in Lithuanian Sign Language with Computer Vision: a proof of concept. Vadim Kimmelman (University of Bergen); Anželika Teresė (Vilnius University).
  • Crowd Simulation with Deliberative-reactive Agents. Cristian Berceanu (University Politehnica of Bucharest); Ionut Banu (University Politehnica of Bucharest); Bettina S. Husebo (University of Bergen); Monica Patrascu (University of Bergen).
11:35-11:50 Coffee Break
11:50-12:50 General NAIS assembly
12:50-13:00 Closing


A Theory for AI Computation?

Ana Ozaki, University of Oslo

Artificial Intelligence (AI) has become ubiquitous in our everyday lives. There has been intense research on tasks related to language generation and understanding and, as a result of the improvements in these tasks (see e.g. BERT, (chat)GPT, and Bard), AI has been applied to enhance user experience in household appliances, virtual personal assistants, search engines, recommender systems, among others. A big portion of articles on machine learning are based on experimental evaluations, where the goal is often to provide evidence of an improvement of accuracy results on benchmarks. While the advance of application-driven research in AI at such a pace is exciting, we also envision an urgent need of establishing and standardizing a formalization of certain notions used in the field, starting with basic conceptual questions. What is a learning algorithm? What does it mean (formally!) to say that it has learnt to perform a certain task? In this talk we cast light on abysmal literature gaps between AI and foundational research. We also highlight contributions made by multiple authors towards filling gaps.

Ana Ozaki is an associate professor at the University of Bergen and at the University of Oslo, Norway. She is an AI researcher in the field of knowledge representation and reasoning and in learning theory. Ozaki is interested in the formalization of the learning phenomenon so that questions involving learnability, complexity, and reducibility can be systematically investigated and understood. Her research focuses on learning logical theories formulated in description logic and related formalisms for knowledge representation. She is the principal investigator of the project Learning Description Logic Ontologies funded by RCN.

Endrocrine digital twin as an example of Medical AI

Helge Ræder, University of Bergen

The use of artificial intelligence is becoming increasingly prevalent in medical research and will continue to push the boundaries of what medical research is, and can do. Hormones are essential signaling chemicals that coordinate the function of the body’s various organs. They are secreted in pulses with distinct rhythms which may be ultradian (24h) or circadian (diurnal), and modulated by external factors such as sleep, food intake, physical activity and stress. Endocrine disorders arise when these rhythms are changed. A human digital twin is a virtual representation of a real person, created by collecting and analyzing data from various sources such as medical records, wearable devices, social media activity, and other digital interactions. An human endocrine virtual twin model would build on a spectrum of implemented, demonstrated, validated and early phase real-world data of the hormonal system, including clinical, device-based and other disease and well-being related data. The digital twin can be used to simulate and predict a person's behaviour, preferences, health, and other attributes, allowing for personalized and data-driven decisions.

Helge Ræder is a professor at the Clinical Institute 2 at the University of Bergen. He is a Vice Dean for Innovation at Faculty of Medicine and a Consultant Pediatrician. His research aims to characterize and better understand the major signaling pathways involved in endocrine disease.

AI and Games

Peter Wingaard, CEO Rain AS

This talk is about game AI. Largely it is a history of pretending to be smart. In games, we do that with everything. "Will people think this random distortion is water?" "Does this look like real light to you?" "Does the enemy feel smart enough to be human, yet dumb enough to stick their head out for you to hit with a shot at regular and predictable intervals?" Our AI's are no different.

Peter has been running the game studio Rain in Bergen since 2010, growing the company to 20 people. With a lifelong passion for game design he has kept a hand on the technical aspects of game creation.


Registration is now open. Note that we cannot have on-site registration and the registration will close on June 11th (Oslo time). At least one author of an accepted paper must registier to the conference. The registration fee will cover the cost of food during the event including the conference dinner, which will be held at Kranen .
The registrtion fee is 1200 NOK for students and 1800 NOK for regular attendees.
Please click the following link to register:


Abstract Registration Deadline: April 28, 2023 (extended)
Submission Deadline: May 5, 2023 (Extended)
Notification Date: May 22, 2023
Camera-Ready Deadline: June 2, 2023
Symposium Dates: June 14-15, 2023

Call for Papers

Contributions are welcome from all areas of Artificial Intelligence, and topics of interest include but are not limited to:

  • Machine Learning
  • Knowledge Representation
  • Robotics
  • Planning and Scheduling
  • Natural Language Processing
  • Computer Vision
  • Search Algorithms
  • Multi-Agent-Systems
  • Industrial Applications
  • Philosophical and Ethical Foundations

Submission Instructions

We welcome and encourage the submission of high-quality papers that have not already been published elsewhere. Submissions must be in English and must follow the single column CEUR format, using the supplied official template files. Papers should not exceed 12 pages excluding references for long papers, and 6 pages excluding references for short papers. The short (6 pages) papers can be a summary of work that has been published (or accepted for publication)in 2022 and 2023, in which case the authors should state this clearly in the submisson. Submissions that do not conform to the CEUR styles will be desk rejected.

All submitted papers will be single-blind peer-reviewed by two to three reviewers.

The proceedings of the symposium will be published in the CEUR Free Open-Access Proceedings for Computer Science Workshops. These proceedings are approved as a scientific publication channel at level 1 in Norway.

We highly encourage early-stage researchers and PhD students to submit their work.

Paper submission is electronic via this address:

Program Co-Chairs

Local Organizing Committee

Program Committee

Eniafe Ayetiran (Norwegian University of Science and Technology )
Massimiliano Ruocco (Norwegian University of Science and Technology)
Andreas Lothe Opdahl (The University of Bergen)
Mehdi Elahi (University of Bergen)
Monica Patrascu (University of Bergen)
Helge Langseth (Norwegian University of Science and Technology)
Hugo Lewi Hammer (OsloMet)
Laurence Dierickx (University of Bergen)
Valeria Vitelli (University of Oslo)
Odd Erik Gundersen (Norwegian University of Science and Technology)
Martin Sætra (Norwegian Meteorological Institute and Oslo Metropolitan University)
Dag Elgesem (University of Bergen)
Ole Mengshoel (Norwegian University of Science and Technology)
Vadim Kimmelman (University of Bergen)
Tiago Veiga (Norwegian University of Science and Technology)
Kerstin Bach (Norwegian University of Science and Technology)

Connect with the Norwegian AI Society on