We sat down with Douglas Guillbault to discuss his paper, " Comparing Colorseeing, Colorblind, Painters, and Large Language Models in Their Processing of Color Metaphors ". The results have interesting implications for how we model human cognition, and in turn, how the concept of synaesthesia could be integrated to develop more intelligent AI models. A color metaphor is the use of color to describe something in a way that is not immediately literal. For example, to say "green with envy" would be a color metaphor, because envy doesn't have an immediate visual structure to it - we're evoking a broader, more flexible notion of what green conveys, beyond just its visible properties. What makes metaphors very interesting is that they often use past experience or cultural associations in new ways to talk about something beyond our current perception - either something imagined or in the future, which are many steps of abstraction away from the present. Metaphors provide an alternative pathway to get there.

Each year the AAAI recognizes a group of individuals who have made significant, sustained contributions to the field of artificial intelligence by appointing them as Fellows. We're talking to some of the 2026 AAAI Fellows to find out more about their work. In this interview, we chat to Sanmay Das, who was elected as a Fellow . Could you start with a quick introduction, where you work, and your general area of research? Broadly speaking, I work in multiagent systems. I've done a lot of work at the intersection of AI and economics, and over the last decade or so I've thought a lot about projects in the AI for social impact and social good space. In particular, my interest has been in the allocation of scarce societal resources, thinking about how AI can be integrated, and what it tells us about systems where we don't necessarily want full free market resource allocation.

Artificial intelligence systems that ask users to pause to consider AI's energy consumption and environmental impacts are likely to reduce unnecessary AI use, new research by Oregon State University suggests. The findings, published in Science Communication, are important as AI is already using electricity on scales that can be meaningfully compared to households, factories and towns. For example, the electricity needed to train a large language model would power 120 homes for a year, the researchers note; one AI-generated image has roughly the same energy cost as charging a smartphone. With about 85% of the world's energy still coming from fossil fuels, every megawatt-hour that can be carved from AI's electricity profile is significant, says the study's leader, Cheng "Chris" Chen of the OSU College of Liberal Arts. "Despite AI's substantial environmental impacts, information about those impacts is rarely disclosed or effectively communicated to everyday users of AI systems," said Chen, assistant professor in the School of Communication.

The AAMAS 2026 best paper awards were presented at the 25th International Conference on Autonomous Agents and Multiagent Systems, which took place from 25-29 May 2025 in Paphos, Cyprus. Lucy Smith is Senior Managing Editor for AIhub. Lucy Smith is Senior Managing Editor for AIhub. Eleanor Drage speaks with Tara Merk about how community-owned data centers could transform digital ownership and challenge the dominance of Big Tech. We find out more about multi-agent research for the allocation of scarce societal resources.

This post contains a list of the AI-related seminars that are scheduled to take place between 1 June and 31 July 2026. All events detailed here are free and open for anyone to attend virtually. Franco Accordino and Monika Lanzenberger (European Commission) The Digital Humanism (DIGHUM) Initiative The talk will be livestreamed on YouTube here . K Madhava Krishna (IIIT Hyderabad) Robotics Café The Google Meet link is here . Gianfranco Polizzi (University of Birmingham) Raspberry PI Sign up here to join.

Last week, OpenAI shocked the mathematical community by revealing that one of its internal artificial intelligence (AI) models had found a counterexample to a famous conjecture made by legendary Hungarian mathematician Paul Erdős in 1946. The planar unit distance problem, or Erdős problem 90, has intrigued mathematicians for decades. The new result is no mere curiosity. Canadian mathematician Daniel Litt described it as "the first result produced autonomously by an AI that I find interesting in itself". The breakthrough, produced with a general-purpose AI model rather than one specialised for mathematics, also highlights how AI is changing mathematical research itself.

Hosted by Eleanor Drage and Kerry McInerney, The Good Robot is a podcast which explores the many complex intersections between gender, feminism and technology. How can communities take back control of the digital infrastructure that powers everyday life? In this episode, Eleanor Drage speaks with Tara Merk about how community-owned data centers could transform digital ownership and challenge the dominance of Big Tech. The conversation explores alternative models of internet infrastructure that prioritize local empowerment, sustainability, and cooperative governance over corporate control. Drawing on examples from Germany's renewable energy sector and community-led initiatives, Merk reflects on how decentralized ownership models can create fairer and more environmentally responsible technological systems.

Find out more about our session on Wednesday 21 January.

Find out more about our session on Wednesday 21 January.

We consider the problem of modifying a description logic concept in light of models represented as pointed interpretations. We call this setting model change, and distinguish three main kinds of changes: eviction, which consists of only removing models; reception, which incorporates models; and revision, which combines removal with incorporation of models in a single operation. We introduce a formal notion of revision and argue that it does not reduce to a simple combination of eviction and reception, contrary to intuition. We provide positive and negative results on the compatibility of eviction and reception for EL-bottom and ALC description logic concepts and on the compatibility of revision for ALC concepts.