Konferenzen  >  Informatik  >  Netzgemeinschaften und Gesellschaftliche Aspekte der Informationstechnologie

We are delighted to extend our invitation to the 3rd International Conference on AI-Generated Content (AIGC 2025), scheduled for December 27-28, 2025, in the vibrant city of Hangzhou. Building on the success of AIGC 2023 in Shanghai and AIGC 2024 in Beijing, AIGC 2025 will continue to serve as a premier platform for sharing cutting-edge research and discussing the latest trends in AI-generated content. This conference will adopt a hybrid format, facilitating both in-person and online participation, providing an excellent opportunity for reconnecting with colleagues we haven't had the chance to meet for an extended period.

Conference Secretariat;     Tel.: [+86-15618780723];     Email: contact@icaigc.org

T1: Foundations of AI Artificial General Intelligence Machine Learning Deep Learning Transformer Neural Networks T2: AI in Creative Expression Generative AI AI-generated Audio AI-generated Art AI-generated Image T3: Advanced AI Applications Natural Language Processing (NLP) Computer Vision Diffusion Models for Machine Learning AI in Robotics

Neuronale Netze und Künstliche Intelligenz, Maschinelles Lernen,    Mustererkennung und Bildverarbeitung, Maschinelles Sehen

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

The five-day seminar will bring together AI and ML researchers from various universities with representatives from NGOs pursuing various social good goals, such as providing legal aid, providing humanitarian assistance, advocating for gender justice, denouncing growing levels of inequality, and defeating poverty. On these topics, NGOs have rich domain knowledge, just like they have vast networks with (non-)governmental actors in developing countries. Mostly, NGOs have their finger on the pulse of the challenges that the world & especially its most vulnerable inhabitants are facing today, and will be facing tomorrow.

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

The rapid advancements in digital technologies, particularly generative AI, have triggered a profound shift in the relationship between technology, humans, society, and the values that shape our world. These developments challenge the traditional understanding of computer science, both as a discipline and as a driver of societal transformation.

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

Social Inteliigence in AI Theory of Mind Large Language Models Social Arificial Intelligence Social Agents

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

In this Dagstuhl Seminar, we aim to bring together researchers and industry practitioners who study and build digital games. The goal is to generate a better understanding of the harms in games and progress towards enriching playful experiences for broad groups of players.

games; toxicity; deceptive design; problematic gaming; accessibility;

Benutzerschnittstellen, User Experience, Virtuelle Realität ,    Mulitimedia und Computergrafik, Spiele

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

We expect this Dagstuhl Seminar to have outcomes that support research and development in the area of physically assistive robotics, including: documentation of guidelines on how to include the disabled community and other stakeholders in research; highlights and insights about how different disciplines can come together to work on physically assistive robotics; clear open questions regarding topics that still need to be explored in this field in the future; establishment of collaborations between researchers, community, and industry.

Robotik, Automatisierung & Mechatronik,    Medizintechnik

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

This Dagstuhl Seminar is relevant to the diverse fields of data management, data engineering, human computation and crowdsourcing, data-driven decision-making, responsible AI, and data governance. The seminar looks at three perspectives: Human, Computational, and Institutional. There is an evident need to bring together perspectives from domain experts who understand the properties and semantics of the datasets (human perspective); from algorithmic advancements that can help improve data quality (computational perspective); and from institutional imperatives including regulations, standards and organizational policies that create necessary safeguards for governance of data pipeline processes (institutional perspective).

Data Quality; Bias and Fairness; Responsible AI

Benutzerschnittstellen, User Experience, Virtuelle Realität ,    Datenbanktechlologie, Suchmaschinen und Data-Mining