1,275 research outputs found
Automating Moral Reasoning (Invited Paper)
No full textArtificial Intelligence ethics is concerned with ensuring a nonnegative ethical impact of researching, developing, deploying and using AI systems. One way to accomplish that is to enable those AI systems to make moral decisions in ethically sensitive situations, i.e., automate moral reasoning. Machine ethics is an interdisciplinary research area that is concerned with the problem of automating moral reasoning. This tutorial presents the problem of making moral decisions and gives a general overview of how a computational agent can be constructed to make moral decisions. The tutorial is aimed for students in artificial intelligence who are interested in acquiring a starting understanding of the basic concepts and a gateway to the literature in machine ethics
Ranked multidimensional dialogue act annotation
No full textWlodarczak M. Ranked multidimensional dialogue act annotation. In: Slavkovik M, ed. Proceedings of the 15th student session of the European Summer School for Logic, Language and Computation. Copenhagen; 2010: 162-172
Türkçe-Makedonca Konuşma Kılavuzu 1, Türk transkripsiyonu ile / Турско-македонски разговорник 1, со турска транскрипција
No full textThe materials for the “ Turkish-Macedonian phrase book” were compiled during the Macedonian language classes with the students from Turkey. The author of the phrasebook, Marija Leontik has also classified and enlarged the materials. In order to enable the learners to self-study, the sentence is first given in Turkish language, than in Macedonian, then follows transcription of the Macedonian sentence. The aim is the beauty of the Turkish language to facilitate the learning of the beauty of the Macedonian language. Several professors (Simon Sazdov, Esen Bejzat, Halil Acikgjoz, Sevim Hilmioglu) reviewed the book in order to make it more useful and conformant with the criteria for this types of books
PRISM models, output and timing information for experiments to investigate Information Diffusion in Social Networks
No full textThis deposit contains model files for the PRISM model-checking tool for a number of experiments exploring information diffusion in social networks described in Dennis and Slavkovik. Model-checking Information Diffusion in Social Networks with PRISM. Submitted to PRIMA 2019. It also contains the output of the PRISM experiments, a number of additional random networks that can be used to modify the models and the results of experiments to investigate the time taken for PRISM to build models and run model-checking as the number of agents in the networks increases
„Турско-македонски разговорник 1, со турска транскрипција“(“Turkish- Macedonian Phrasebook 1”)
No full textThe materials for the “ Turkish-Macedonian phrase book” were compiled during the Macedonian language classes with the students from Turkey. The author of the phrasebook, Marija Leontik has also classified and enlarged the materials. In order to enable the learners to self-study, the sentence is first given in Turkish language, than in Macedonian, then follows transcription of the Macedonian sentence. The aim is the beauty of the Turkish language to facilitate the learning of the beauty of the Macedonian language. Several professors (Simon Sazdov, Esen Bejzat, Halil Acikgjoz, Sevim Hilmioglu) reviewed the book in order to make it more useful and conformant with the criteria for this types of books
JA4AI – Judgment Aggregation for Artificial Intelligence (Dagstuhl Seminar 14202)
No full textThis report documents the programme and the outcomes of Dagstuhl Seminar 14202 on "Judgment Aggregation for Artificial Intelligence". Judgment aggregation is a new group decision-making theory that lies in the intersection of logic and social choice; it studies how to reach group decisions on several logically interconnected issues by aggregation of individual judgments. Until recently research in judgment aggregation was dominated by its originating context of philosophy, political science and law. Presently, however we are witnessing increasing work in judgment aggregation from researchers in computer science. Since researchers from such diverse disciplinary backgrounds working on judgment aggregation each publish within their own discipline with virtually no cross-discipline cooperation on concrete projects, it is essential that they are given an opportunity to connect to each other and become aware of the workings of the other side. This seminar has provided such an opportunity
Ethics and Trust: Principles, Verification and Validation (Dagstuhl Seminar 19171)
No full textThis report documents the programme of, and outcomes from, the Dagstuhl Seminar 19171 on "Ethics and Trust: Principles, Verification and Validation". We consider the issues of ethics and trust as crucial to the future acceptance and use of autonomous systems. The development of new classes of autonomous systems, such as medical robots, "driver-less" cars, and assistive care robots has opened up questions on how we can integrate truly autonomous systems into our society. Once a system is truly autonomous, i.e. learning from interactions, moving and manipulating the world we are living in, and making decisions by itself, we must be certain that it will act in a safe and ethical way, i.e. that it will be able to distinguish 'right' from `wrong' and make the decisions we would expect of it. In order for society to accept these new machines, we must also trust them, i.e. we must believe that they are reliable and that they are trying to assist us, especially when engaged in close human-robot interaction. The seminar focused on questions of how does trust with autonomous machines evolve, how to build a `practical' ethical and trustworthy system, and what are the societal implications. Key issues included: Change of trust and trust repair, AI systems as decision makers, complex system of norms and algorithmic bias, and potential discrepancies between expectations and capabilities of autonomous machines.
This workshop was a follow-up to the 2016 Dagstuhl Seminar 16222 on Engineering Moral Agents: From Human Morality to Artificial Morality. When organizing this workshop we aimed to bring together communities of researchers from moral philosophy and from artificial intelligence and extend it with researchers from (social) robotics and human-robot interaction research
Roadmap for Responsible Robotics (Dagstuhl Seminar 23371)
No full textThis report documents the program and the outcomes of Dagstuhl Seminar 23371 "Roadmap for Responsible Robotics". The seminar was concerned with robots across all their forms, particularly autonomous robots capable of making their own decisions and taking their own actions without direct human oversight. The seminar brought together experts in computer science, robotics, engineering, philosophy, cognitive science, human-robot interactions, as well as representatives of the industry, with the aim of contributing to the steps towards ethical and responsible robotic systems as initiated by actors such as the European Robotics Research Network (EURON), the European Union’s REELER, and others. We discussed topics including: "Why do autonomous robots warrant distinct normative considerations?", "Which stakeholders are, or should be, involved in the development and deployment of robotic systems, and how do we configure their responsibilities?", "What are the principal tenets of responsible robotics beyond commonly associated themes, namely trust, fairness, predictability and understandability?". Through intensive discussions of these and other related questions, motivated by the various values at stake as robotic systems become increasingly present and impactful in human life, this interdisciplinary group identified a set of interrelated priorities to guide future research and regulatory efforts. The resulting roadmap aimed to ensure that robotic systems co-evolve with human societies so as to advance, rather than undermine, human agency and humane values
Engineering Moral Agents -- from Human Morality to Artificial Morality (Dagstuhl Seminar 16222)
No full textThis report documents the programme of, and outcomes from, the Dagstuhl Seminar 16222 on "Engineering Moral Agents -- from Human Morality to Artificial Morality". Artificial morality is an emerging area of research within artificial intelligence (AI), concerned with the problem of designing artificial agents that behave as moral agents, i.e. adhere to moral, legal, and social norms. Context-aware, autonomous, and intelligent systems are becoming a presence in our society and are increasingly involved in making decisions that affect our lives. While humanity has developed formal legal and informal moral and social norms to govern its own social interactions, there are no similar regulatory structures that apply to non-human agents. The seminar focused on questions of how to formalise, "quantify", qualify, validate, verify, and modify the ``ethics" of moral machines. Key issues
included the following: How to build regulatory structures that address (un)ethical machine behaviour? What are the wider societal, legal, and economic implications of introducing AI machines into our society? How to develop "computational" ethics and what are the difficult challenges that need to be addressed? When organising this workshop, we aimed to bring together communities of researchers from moral philosophy and from artificial intelligence most concerned with this topic. This is a long-term endeavour, but the seminar was successful in laying the foundations and connections for accomplishing it
- …
