Meal awareness can help people reflect on hydration, chewing rhythm, and conversation-heavy meals, but many eating-sensing approaches rely on cameras, microphones, food photographs, or repeated self-logging. PPG and IMU offer a narrower sensing path by capturing physiological and motion patterns around meal-adjacent ac...
Yuxuan Hou, Jiao Li, Lin-Chuang Jiang et al.· 0 citations
Users browsing the web struggle to locate relevant information on cluttered pages and to complete web navigation tasks. Current web agents can answer questions and automate actions, but return answers without showing where the information comes from, forcing users to manually verify results and blindly trust every auto...
Tin Nguyen, Thang T. Truong, Runtao Zhou et al.· 0 citations
AI assistants on smart glasses need to know what surrounds the user and what the user is looking at. Obtaining this context typically relies on a world-facing camera, raising privacy concerns for bystanders. We present GlintMarkers, a system for gaze-anchored spatial perception using a single inward-facing eye camera....
Seungjoo Lee, Vimal Mollyn, Chris Harrison et al.· 0 citations
Picky eating can limit children's dietary variety and create tension in family feeding routines. Existing food-related technologies often focus on mealtime intervention or standalone educational artifacts, offering limited support for connecting low-pressure narrative engagement with children's real-world food explorat...
Yanuo Zhou, Jun Fang, Yuntao Wang et al.· 0 citations
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It is argued that AI/ML methods were born from specific platform and internet infrastructures, and so they can struggle to integrate with very different (in this case meteorological) ways of organizing data pipelines.
LLM-powered computer-use agents (CUAs) shift users from direct manipulation to supervising an unfolding action sequence, yet existing oversight research mostly evaluates static decisions rather than real-time oversight across an agent trajectory. We compared four oversight strategies with 48 participants across 192 liv...
Chaoran Chen, Zhiping Zhang, Zeya Chen et al.· 0 citations
In today's in-person group discussions, smartphones are integrated as intelligent workstations; yet given their co-presence in such face-to-face interactions, whether and how they may enhance people's behavioral engagement with others remains underexplored. This work investigates how animating personal smartphones to m...
Ziqi Pan, Ziqi Liu, Jinhan Zhang et al.· 0 citations
Personalized social media feeds infer preferences from behavior, leaving people little direct control over what they see. Existing controls range from post-level reactions to rules and natural language, but little is known about how people use them together or how added expressiveness changes effort. We built PILOT, a...
Agam Goyal, Frederick Choi, Eshwar Chandrasekharan· 0 citations
Online communities rely on volunteer moderators to maintain order. Despite their key role, moderators are given a toolbox of punishments and far less support for encouraging contributions they want to see more of. We introduce the Positive Queue as a positive counterpart to Reddit's modqueue: a dedicated space for mode...
Charlotte Lambert, Agam Goyal, Eunice Mok et al.· 0 citations
HCI often draws on users' articulated needs and expectations to explore design opportunities for emerging technologies. Yet, these accounts are shaped by how technologies take form over time. We examine this dynamic through a two-phase interview study of enterprise AI in a project-based software development organizatio...
Qing Xiao, Xinlan Emily Hu, Mark E. Whiting et al.· 0 citations
The results suggest that differences in both experience with values and professional domain can impact how values are translated into designs, and that while software engineers did not misunderstand the principles, theologians had a broader understanding.
L. Conwill, Megan K. Levis, Karla A. Badillo-Urquiola et al.· 3 citations
Children increasingly turn to online information access systems that are primarily designed for the mainstream population, e.g., adults, but possess a limited understanding of how these systems work, contributing to their unstructured and ineffective search practices. This lack of knowledge can hinder their curiosity a...
Diletta Micol Tobia, Hrishita Chakrabarti, Maria Soledad Pera et al.· 0 citations
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduSep 30, 2026
Able to defeat top-ranked human players and more efficient than other models, the new system could help decision-makers in military maneuvers or business negotiations.
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
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