A new study led by the Konrad Lorenz Research Center for Behavior and Cognition at the University of Vienna sheds light on a long-standing mystery in animal behavior: why do certain individuals gain more influence than others within a group? The research shows that bold geese – but not aggressive ones – are more likely to be accepted as leaders, while exploratory individuals tend to follow them – revealing a nuanced interplay of personality and social roles in collective movement decisions. The results of the study have just been published in the journal iScience.

Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks. Graph neural networks (GNNs) have achieved great success in representation learning on graphs, facilitating various downstream tasks. However, GNNs have several drawbacks such as lacking interpretability, can easily inherit the bias of data and cannot model casual relations. Recently, counterfactual learning on graphs has shown promising results in alleviating these drawbacks. Various approaches have been proposed for counterfactual fairness, explainability, link prediction and other applications on graphs. To facilitate the development of this promising direction, in this survey, researchers categorize and comprehensively review papers on graph counterfactual learning. Researchers divide existing methods into four categories based on problems studied. For each category, they provide background and motivating examples, a general framework summarizing existing works and a detailed review of these works. Researchers point out promising future research directions at the intersection of graph-structured data, counterfactual learning, and real-world applications. To offer a comprehensive view of resources for future studies, researchers compile a collection of open-source implementations, public datasets, and commonly-used evaluation metrics. This survey aims to serve as a “one-stop-shop” for building a unified understanding of graph counterfactual learning categories and current resources.

In southwestern Kenya more than 2.6 million years ago, ancient humans wielded an array of stone tools—known collectively as the Oldowan toolkit—to pound plant material and carve up large prey such as hippopotamuses. These durable and versatile tools were crafted from special stone materials collected up to eight miles away, according to new research led by scientists at the Smithsonian’s National Museum of Natural History, Cleveland Museum of Natural History and Queens College. Their findings, published Aug. 15 in the journal Science Advances, push back the earliest known evidence of ancient humans transporting resources over long distances by some 600,000 years.

Older siblings and friends may play important, and sometimes overlooked, roles in helping parents keep their children safe on online gaming platforms like Roblox and Minecraft, according to new research led by Penn State.

Thanks to AI technologies, the spread of mass-produced contextually relevant articles and comment-laden social media posts has become so commonplace that it can appear as though it’s coming from different information sources. The resulting “echo chamber” effect could reinforce a person’s existing perspectives, regardless of whether that information is accurate.

 

A new study involving Binghamton University, State University of New York researchers offers a promising solution: developing an AI system to map out interactions between content and algorithms on digital platforms to reduce the spread of potentially harmful or misleading content. 

Media Invitation – IJCAI 2025, Montréal, Canada
Artificial Intelligence for a Better World – Since 1969

The 34th International Joint Conference on Artificial Intelligence (IJCAI) takes place August 16–22, 2025 in Montréal, Canada, bringing together over 2,000 AI researchers, practitioners, and thought leaders. Guided by the theme “AI at the service of society”, IJCAI 2025 features world-class keynote speakers, award-winning researchers, thematic tracks on AI for Social Good, Human-Centred AI, and AI, Arts & Creativity, as well as admission free public events like the AI Lounge: Between Wonder and Caution.

Highlights include talks by Yoshua Bengio, Heng Ji, Luc De Raedt, Bernhard Schölkopf, and IJCAI 2025 awardees Aditya Grover, Rina Dechter, and Cynthia Rudin. The program also showcases AI-driven competitions, an AI Art Gallery, and discussions on ethics, creativity, and global impact.

Full program & details: https://2025.ijcai.org
Media contact: mrozman@ijcai.org