News
What Tech Workers Tell Their Kids About Careers in the Age of AI
UMD’s Katie Shilton studies how tech-worker parents are preparing their children for an AI-transformed workplace.
GW Researchers Receive New Grants to Study Applications of Trustworthy AI
Reporting from GW’s student newspaper highlights latest round of TRAILS seed grants.
When AI Writes for You, Can It Still Sound Like You?
UMD team finds that editing AI-generated text may not erase its stylistic fingerprints.
TRAILS Awards More Than $515K for Trustworthy AI Research
The fourth round of seed funding supports multidisciplinary teams tackling one of AI's biggest challenges: earning public trust.
AI Hiring Tools May Favor Their Own Work, UMD Study Finds
New research by UMD’s Jiannan Xu highlights emerging bias in AI-to-AI interactions—and practical fixes.
Team HAX Lab Wins National AI Innovation Challenge
Guided by Morgan State’s Naja Mack, the team earned top honors for a privacy-focused AI application designed to support communication and social well-being.
Can AI and People Play Nice?
UMD’s Jordan Boyd-Graber is uncovering what makes human-AI partnerships succeed through high-stakes quizbowl competitions, finding that trust may matter more than intelligence.
UMD Team Develops Precise “Undo Button” for AI Memory
UMD’s Soheil Feizi helped develop a new method removes problematic information from large language models without damaging their reasoning abilities.
The Role of Language in AI Research
UMD’s Marine Carpuat explains how multilingual AI systems can facilitate cross-language communication.
When the Feed Becomes the Front Line
UMD’s Cody Buntain is developing AI tools to analyze social media imagery from global conflicts, helping analysts establish ground truth while investigating the reliability of human-AI decision-making.
Rethinking the “Charisma Trap” in Human-AI Interaction
UMD’s Michelle Mazurek and GW’s Adam Aviv found that a chatbot’s polite demeanor creates a “charisma trap” that masks subtle biases and safety risks.
UMD Framework Used to Test Safety of Meta’s New Multimodal AI Model
UMD’s Furong Huang is co-leading efforts involving AI safety testing under simulated operational pressure.
How Generative AI Works—and Why It Can Mislead Users
GW’s David Broniatowski explains the pattern-based systems behind tools like ChatGPT, and the risks that come with them.
TRAILS Researchers Advance Robotics to Perform Complex Household Tasks
UMD’s Furong Huang and Tom Goldstein are advancing breakthroughs in trustworthy machine learning to create robotic systems that will excel in dynamic home environments.
A Building Code for Digital Infrastructures
GW’s David Broniatowski explains how the same infrastructural concern with AI keeps surfacing: a few companies shape how billions see information, speak, and organize.
AI-Enabled Manufacturing Will Change How, When and Where Goods Are Made
GW’s Susan Ariel Aaaronson explains how AI-enabled manufacturing is reshaping global production dynamics and risks, driving a new era of overcapacity.
AI’s Growing Energy Demands Raise Concerns About Infrastructure and Control
GW’s David Broniatowski is examining how AI systems interact not only with each other, but also with critical infrastructure and governance systems.
TRAILS Announces 11 Broader Impact Awards to Cultivate Next Generation of Trustworthy AI Leaders
New funding supports seed projects that incentivize a wide range of stakeholders to engage with and influence the future of AI.
Developing a Better Understanding of Global Participation in AI
UMD’s Maria Isabel Magaña talks about socio-cultural influences in AI development and governance.
What is Participatory Design in AI?
UMD’s Katie Shilton is leading research on participatory design to build trustworthy AI systems.