- Phone+47 55 58 23 77
- Visitor AddressFosswinckels gate 6Room613
- Postal AddressPostboks 78025020 Bergen
Marija Slavkovik is an associate professor at the University of Bergen in Norway. Her area of research is Artificial Intelligence (AI) with expertese in collective reasoning. Slavkovik is active in the AI subdisciplines of: multi-agent systems, machine ethics and computational social choice.
Slavkovik believes that the world can be improved by automating away the borring, repetitive and dangerous human tasks and that AI has a crutial role to play towards this goal. In AI, the big problem she hopes to solve is the efficient self-coordination of systems of artificial intelligent agents.
In machine ethics, Slavkovik is active in engineering machine ethics problems - How can we build autonomous systems and artificial agents that behave ethically? Want to know what is happening in machine ethics since it stopped being an SF-only topic? There is a tutorial for that. Slavkovik co-organised a Dagstuhl Seminar in 2019 on this topic. She is also one of the guest editors of the Special Issue on Ethics for Autonomous Systems of the AI Journal.
Slavkovik is the vice-chair of the Norwegian Artificial Intelligence Society and member of the informal advisory group on Ethical, Legal, Social Issues of CLAIRE. She is in the education committee of NORA curently working on developing a national phd course on AI ethics.
In computational social choice and multi-agent syste, Slavkovik is particularly active in Judgment Aggregation. If you are wondering what this is there is a tutorial for that. Her new passion in this field is looking for ways to consider social network interaction of agents and what impact that can have on collective reasoning and decision-making, particularly in aggregation. For more on what social network analysis has to do with AI go here.
Slavkovik was the chair and host of the 16th European Conference on Multi-Agent Systems EUMAS held December 6-7, 2018 in Bergen. Here are the proceedings. She is also in the board of EURAMAS.
Marija is an active speaker on issues of AI and Ethics. Links to some given talks, articles and interviews.
Video & audio
- Kunstig intelligens og maskinetikk Akademisk lunsj Bergen Library Available as podcast.
- Who's a good robot? CHRISTIE-KONFERANSEN: The robots are coming, are you? Video? (Jump to 5:36:00)
- For the good of all, CLAIRE (jump to 2:20)
- Ben Gyford's Machine Ethics Podcast.
- AI and Ethics. Teaching machines to behave with TechNadine.
- AI Inspiration talk. Nordic testbed network.
- The usefullness of useless AI by Marija Slavkovik. The AI Hub.
- Press for Building Jiminy Cricket: An Architecture for Moral Agreements Among Stakeholders :New Scientist, Daily Mail
- People know when to break the rules, but machines don’t by the Tek-Lab.
- Shame on you robot by TORHILD DAHL
- Researcher profile by UiB
- Condorcet’s jury theorem and the truth on the web by Marija Slavkovik in VoxPublica
- „Ништо не е бесплатно – ние трампаме дел од нашето време и внимание“ by Ирена Трајковска in VezilkaMagazine
Doctoral students (main superviser)
- Than Htut Soe started in February 2018 and is a doctoral student on the BIA funded project Beter Video workflows via Real-Time Collaboration and AI-Techniques in TV and New Media. Soe's thesis explores the cooperation between AI methods and human interaction in video editing. Recent publication: Circumvention by design - dark patterns in cookie consent for online news outlets at NordiCHI 2020: 19:1-19:12.
- Mina Young Pedersen started in October 2019. Pederesen's thesis explores the interplay of logic reasoning and social networks.
- Flavio Tisi (co-supervision with Sonja Smets).
- Einar Søreide Johansen
- Hanna Kubacka (co-supervision with Jan-Joachim Rückmann). Related publication: Predicting the winners of Borda, Kemeny and Dodgson elections with supervised machine learning [pdf]
- Spring 2021 INFO383 Research topics in AI ethics.
- Automn 2020 INFO282 Knowledge representation and reasoning.
- Spring 2020 INFO381 Research Topics in AI. The topic of the course is AI Ethics. Detailed program.
- Autumn 2019 INFO283 Basic Algorithms in Artificial Intelligence.
- Spring 2019 INFO284 Machine Learning.
- Spring 2017 INFO381 Research Topics in AI. The topic of the course is Machine Ethics. Detailed program.
- Autumn 2016, 2017, 2018 INFO125 Data Management.
Office hours are by appointment.
- 2020. The Complexity Landscape of Outcome Determination in Judgment Aggregation. . The journal of artificial intelligence research. 687-731.
- 2019. Improving Judgment Reliability in Social Networks via Jury Theorems. Lecture Notes in Computer Science (LNCS). 230-243.
- 2019. Autonomous yet moral machines. CEUR Workshop Proceedings.
- 2019. Aggregating Probabilistic Judgments. Electronic Proceedings in Theoretical Computer Science. 273-292.
- 2018. Classifying the autonomy and morality of artificial agents. CEUR Workshop Proceedings. 67-83.
- 2018. Aggregation of probabilisitic logically related judgments. NIKT: Norsk IKT-konferanse for forskning og utdanning.
- 2017. `How did they know?' Model-checking for analysis of information leakage in social networks. Lecture Notes in Computer Science (LNCS). 42-59.
- 2017. The Norwegian Oil Fund Investment Decider N.O.F.I.D. NOKOBIT - Norsk konferanse for organisasjoners bruk av informasjonsteknologi.
- 2017. Implementing Asimov’s First Law of Robotics. NIKT: Norsk IKT-konferanse for forskning og utdanning.
- 2017. A partial taxonomy of judgment aggregation rules and their properties. Social Choice and Welfare. 327-356.
- 2017. A modified Vickrey auction with regret minimization for uniform alliance decisions. Studies in Computational Intelligence. 61-72.
- 2016. Iterative judgment aggregation. Frontiers in Artificial Intelligence and Applications. 1528-1536.
- 2016. Formal verification of ethical choices in autonomous systems. Robotics and Autonomous Systems. 1-14.
- 2016. Agenda Separability in Judgment Aggregation. Proceedings of the AAAI Conference on Artificial Intelligence. 1016-1022.
- 2015. An abstract formal basis for digital crowds. Distributed and parallel databases. 3-31.
- 2014. Not all judgment aggregation should be neutral. CEUR Workshop Proceedings. 198-211.
- 2014. Measuring Dissimilarity between Judgment Sets. Lecture Notes in Computer Science (LNCS). 609-617.
- 2014. How Hard is it to compute majority-preserving judgment aggregation rules? Frontiers in Artificial Intelligence and Applications. 501-506.
- 2014. Ethical Choice in Unforeseen Circumstances. Lecture Notes in Computer Science (LNCS). 433-445.
- 2014. A weakening of independence in judgment aggregation: agenda separability. Frontiers in Artificial Intelligence and Applications. 1055-1056.
- 2016. Engineering Moral Agents - from Human Morality to Artificial Morality (Dagstuhl Seminar 16222). 5. 5. .
- 2014. A tutorial in judgment aggregation.
- 2019. What we talk about when we talk about AI and Ethics.
- 2019. Building Jiminy Cricket: An Architecture for Moral Agreements Among Stakeholders.
- 2019. April 22 – 26 , 2019, Dagstuhl Seminar 19171 Ethics and Trust: Principles, Verification and Validation.
- 2019. Answer Set Programming for Judgment Aggregation.
- 2017. Who's a good robot.
- 2017. Towards moral autonomous systems.
- 2017. Engineering Machine Ethics.
- 2014. JA4AI - Judgment Aggregation for Artificial Intelligence (Dagstuhl Seminar 14202). Dagstuhl Reports. 27-39.
- 2019. Multi-Agent Systems - 16th European Conference, EUMAS 2018, Bergen, Norway, December 6-7, 2018, Revised Selected Papers. Lecture Notes in Computer Science 11450. Springer Nature.
- 2017. Condorcet's jury theorem and the truth on the web. Vox publica.
- 2018. Machines That Know Right And Cannot Do Wrong: The Theory and Practice of Machine Ethics. The IEEE Intelligent Informatics Bulletin. 8-11.
- 2016. Dagstuhl Manifesto - Engineering Moral Machines. Informatik-Spektrum.
- 2020. Teaching AI Ethics: Observations and Challenges.
- 2020. Predicting the Winners of Borda, Kemeny and Dodgson Elections with Supervised Machine Learning. 19 pages.
- 2020. Model-Checking Information Diffusion in Social Networks with PRISM. 18 pages.
- 2020. Circumvention by design - dark patterns in cookie consent for online news outlets. 1 pages.
- 2020. Bias mitigation with AIF360: A comparative study.
- 2020. Addressing the ethical principles of the Norwegian National Strategy for AI in a kindergarten allocation system.
- 2019. The Complexity of Elections with Rational Actors. 3 pages.
- 2019. Answer Set Programming for Judgment Aggregation. 7 pages.
- 2018. On the Distinction between Implicit and Explicit Ethical Agency. 7 pages.
- 2017. Formal Models of Conflicting Social Influence. 17 pages.
- 2017. Complexity Results for Aggregating Judgments using Scoring or Distance-Based Procedures. 10 pages.
- 2014. A Judgment Set Similarity Measure Based on Prime Implicants. 2 pages.
- 2013. Some complexity results for distance-based judgment aggregation. 13 pages.
- 2013. Judgment Aggregation Rules and Voting Rules. 14 pages.
MediaFutures: Research Centre for Responsible Media Technology & Innovation. Role: co-leader of WP2 – User Modeling, Personalisation & Engagement.
- Better Video workows via Real - Time Collaboration and AI - Techniques in TV and New Media. Funded by The Research Council of Norway. Type of project: User-driven Research based Innovation (BIA). Grant: NOK 8.4 million. Role: main supervisor of one of the two doctoral students hired on this project.
- The Machine Ethics Challenge to Artificial Intelligence and Society. Funded by the Strategic Programme for International Research Collaboration of the Univeristy of Bergen. Grant: NOK 75.000. Role: PI. The grant will support the establishment of a highly interdisciplinary international network of collaborators on the topic of machine ethics.
Marija Slavkovik is the project manager of a SAMKUL grant whose goal is to prepare funding proposals to explore the machine ethics issues in modern journalism. The first meeting of the network is held in Bergen, November 29-30. Results here.
Through the support of SPIRE from the Faculty of Social Sciences at the University of Bergen, Marija Slavkovik was working to establish an international research network that engages in developing the interdisciplinary research area of logic-based methods for social network analysis in artificial intelligence (AI). Results here.