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. Over the course of the next few months, we'll be talking to some of the 2025 AAAI Fellows. In this interview we hear from Roberto Navigli, Sapienza University of Rome, who was elected as a Fellow for "significant contributions to multilingual Natural Language Understanding, and development of widely recognized methods for knowledge resource construction, text disambiguation, and semantic parsing". We find out about his career path, some big research projects he's led, and why it's important to follow your passion. My area of research is natural language processing (NLP).

Ice cores in freezers, dinosaurs on display, fish in jars, birds in boxes, human remains and ancient artifacts from long gone civilizations that few people ever see – museum collections are filled with all this and more. These collections are treasure troves that recount the planet's natural and human history, and they help scientists in a variety of different fields such as geology, paleontology, anthropology and more. What you see on a trip to a museum is only a sliver of the wonders held in their collection. Museums generally want to make the contents of their collections available for teachers and researchers, either physically or digitally. However, each collection's staff has its own way of organizing data, so navigating these collections can prove challenging.

This prestigious award is made for excellence in research in the area of autonomous agents. It is intended to recognize researchers in autonomous agents whose current work is an important influence on the field. Professor Shlomo Zilberstein was recognised for his work establishing the field of decentralized Markov Decision Processes (DEC-MDPs), laying the groundwork for decision-theoretic planning in multi-agent systems and multi-agent reinforcement learning (MARL). The selection committee noted that these contributions have become a cornerstone of multi-agent decision-making, influencing researchers and practitioners alike. Shlomo Zilberstein is Professor of Computer Science and former Associate Dean of Research at the University of Massachusetts Amherst. He is a Fellow of AAAI and the ACM, and has received numerous awards, including the UMass Chancellor's Medal, the IFAAMAS Influential Paper Award, and the AAAI Distinguished Service Award.

The workshop featured 20 accepted papers across diverse application areas, including five oral presentations and 15 posters. Research topics ranged from agent debate evaluation and taxonomy expansion to hypothesis generation, AI4Research benchmarks, caption generation, drug discovery, and financial auditing. Additionally, the workshop hosted a dedicated mentoring session for early-career researchers. The workshop had six inspiring invited talks from academic and industry experts covering a wide range of research topics. Professor Wei Wang (UCLA) presented work on multimodal scientific foundation models for knowledge extraction and synthesis.

Hosted by Eleanor Drage and Kerry McInerney, The Good Robot is a podcast which explores the many complex intersections between gender, feminism and technology. To develop voice assistants like Siri and Alexa, companies spend years investigating what sounds like a human voice and what doesn't. But what we've ended up with is just one possibility of the kinds of voices that we could be interacting with. In this episode, we talked to sound engineer Frederik Juutilainen, and assistant professor at the University of Copenhagen, Stina Hasse Jørgensen, about their participation in [multi'vocal], an experimental research project that created an alternative voice assistant by asking people at a rock festival in Denmark to speak into a portable recording box. We talk about voice assistants' inability to stutter, lisp and code switch, and whether a voice can express multiple personalities, genders and ages.

An original photograph taken by Felice Frankel (left) and an AI-generated image of the same content. For over 30 years, science photographer Felice Frankel has helped MIT professors, researchers, and students communicate their work visually. Throughout that time, she has seen the development of various tools to support the creation of compelling images: some helpful, and some antithetical to the effort of producing a trustworthy and complete representation of the research. In a recent opinion piece published in Nature magazine, Frankel discusses the burgeoning use of generative artificial intelligence (GenAI) in images and the challenges and implications it has for communicating research. On a more personal note, she questions whether there will still be a place for a science photographer in the research community.

Science communication is an invaluable skill for researchers. It can help demystify AI for a broad range of people including policy makers, business leaders, and the public. In a panel session at the 33rd International Joint Conference on Artificial Intelligence (IJCAI-24), Michael Wooldridge and Toby Walsh talked with Peter Stone about lessons they've learnt from communicating about AI with different audiences. They gave advice on how to talk to media, how you should tailor your communication for various audiences, and how to tackle different methods of communication. They drew on their personal experiences to provide hints and tips for anyone thinking about engaging in outreach. You can watch the recording here.

In this interview series, we're meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. The Doctoral Consortium provides an opportunity for a group of PhD students to discuss and explore their research interests and career objectives in an interdisciplinary workshop together with a panel of established researchers. In the third of our interviews with the 2025 cohort, we heard from Tunazzina Islam who has recently completed her PhD in Computer Science at Purdue University, advised by Dr Dan Goldwasser. Her primary research interests lie in computational social science (CSS), natural language processing (NLP), and social media mining and analysis. We now live in a world where we can reach people directly through social media, without relying on traditional media such as television and radio.

After a year of shoehorning generative AI into its flagship products, Microsoft is trying to recoup the costs by raising prices, putting ads in products, and cancelling data centre leases. Google is making similar moves, adding unavoidable AI features to its Workspace service while increasing prices. Is the tide finally turning on investments into generative AI? The situation is not quite so simple. Tech companies are fully committed to the new technology – but are struggling to find ways to make people pay for it.

Image taken from the front cover of the Future of AI Research report. The Association for the Advancement of Artificial Intelligence (AAAI), has published a report on the Future of AI Research. The report, which was announced by outgoing AAAI President Francesca Rossi during the AAAI 2025 conference, covers 17 different AI topics and aims to clearly identify the trajectory of AI research in a structured way. The report is the result of a Presidential Panel, chaired by Francesca Rossi, and comprising of 24 experienced AI researchers, who worked on the project between summer 2024 and spring 2025. As well as the views of the panel members, the report also draws on community feedback, which was received from 475 AI researchers via a survey.