Hybrid Intelligence 2019 2029 Cltl

Hybrid Intelligence (HI): Augmenting Human Intellect: NWO Zwaartekracht 2019-2029 Developing HI needs fundamentally new solutions to core research problems in AI: current AI technology surpasses humans in many pattern recognition and machine learning tasks, but it falls short on general world knowledge, common... These challenges are being addressed in four interconnected research lines: Collaborative HI: How to design and build intelligent agents that work in synergy with humans, with awareness of each other’s strengths and limitations? We develop shared mental models for communication between humans and agents, computational theories of mind to enable collaboration, and exploit multimodal interaction for seamless dialogues. Coordinators: Dr.

Hayley Hung, h.hung@tudelft.nl and Prof. Koen Hindrinks, k.v.hindriks@vu.nl Adaptive HI: The world in which Hybrid Intelligent systems operate is dynamic, as are the teams of humans and agents that make up such HI systems. HI systems thus need to operate in situations not anticipated by their designers, and cope with variable team configurations, preferences and roles. This requires progress in online reinforcement learning, auto ML, and the integration of learning and reasoning. Coordinators: Dr.

Herke van Hoof, h.c.vanhoof@uva.nl and Prof. Guszti Eiben, a.e.eiben@vu.nl Responsible HI: Addressing and mitigating some of the perceived risks of Artificial Intelligence technologies requires ethical and legal concerns to be an integral part of the design and operation of HI systems. Values such as transparency, accountability, trust, privacy and fairness can no longer be relegated to regulations that apply after system’s deployment. We develop methods to include ethical, legal and societal considerations into the design process (“ethics in design”) and into the performance (“ethics by design”) of HI systems. Coordinators: Dr.

M. Birna van Riemsdijk, m.b.vanriemsdijk@utwente.nl and Prof. Bart Verheij, bart.verheij@rug.nl This is a preview of subscription content, log in via an institution to check access. Price excludes VAT (USA) Tax calculation will be finalised during checkout. For further work on this topic see Dellermann et al.

(2019). https://deepmind.com (accessed 19 Mar 2019). https://ai.google/research/teams/brain/pair (accessed 19 Mar 2019). Hybrid Intelligence is a 10-year NWO-funded gravitation project (2019-2029) lead by prof. Frank van Harmelen (VU). It is a Dutch national research program formed initially by a collaboration of top AI researchers from the VU Amsterdam, the University of Amsterdam, the TU Delft, and the Universities of Groningen, Leiden, and...

UT joined as an associate partner in 2021. Involved researchers work in areas such as machine learning, knowledge representation, natural language understanding & generation, information retrieval, multi-agent systems, psychology, multimodal interaction, social robotics, AI & law and ethics of technology. Hybrid Intelligence (HI) is the combination of human and machine intelligence, expanding human intellect instead of replacing it. HI takes human expertise and intentionality into account when making meaningful decisions and perform appropriate actions, together with ethical, legal and societal values. The project’s goal is to design Hybrid Intelligent systems, an approach to Artificial Intelligence that puts humans at the centre, changing the course of the ongoing AI revolution. Current AI technology surpasses humans in many pattern recognition and machine learning tasks, but it falls short on general world knowledge, common sense, and the human capabilities of (i) Collaboration, (ii) Adaptivity, (iii) Responsibility...

These challenges are being addressed in four corresponding research lines. Link to project website: https://www.hybrid-intelligence-centre.nlLink to UT project website: https://intimate-computing.net/hybrid-intelligence/ Contact person:Dr. Birna van Riemsdijkm.b.vanriemsdijk@utwente.nl At CLTL we teach and study Computational Linguistics and Natural Language Processing (NLP). We are interested in how language works and how we can analyse it using computational methods.

We are interested in the abstract structures that form the basis of human language and on how to extract and analyse them. Our research is inherently interdisciplinary. Many of our staff collaborate with experts in other fields, such as psychology to help identify bias, journalism to improve engagement, medicine to help better monitor patients, and history to help them identify and... The CLTL has a strong track record in conversational AI, but we are also developing Dutch FrameNet, and work on entity and event detection, hate speech and subjectivity. The CLTL is a long-standing participant of the Global Wordnet Association and a contributor to the Global Wordnet Grid for Dutch. We also study meaning in distributional representations, contextual embeddings and multilingual representations.

The CLTL actively studies, builds and uses Large Language Models. We notably research hallucination and bias in these models and how to correct them. arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community?

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