Objective: To assess trends in family physicians' (FPs) electronic health record (EHR) satisfaction and their experience of interoperability across organizations.
Materials and Methods: Serial cross-sectional analysis of five waves of the American Board of Family Medicine's Continuous Certification Questionnaire (202...
Carl Y. Zhang, Nathaniel Hendrix, Robert L. Phillips et al.· 0 citations
Opacity is a widely used channel in data visualization, but it remains less well understood compared to channels such as color, length, size, etc. Recent work from Meng et al. investigated the impact of opacity across competing color schemes, finding that certain color schemes were associated with better participant ac...
Caterina Ponti, Shano Liang, Lane Harrison et al.· 0 citations
Designing learning interfaces is often an ill-structured problem: effective solutions depend on learning goals, subject matter, learner characteristics, and interaction context that are difficult to generalize. Designers must integrate knowledge from learning sciences, interaction design, and subject domains when trans...
Lorena Lyon, Hyoungwook Jin, Vincent Cavez et al.· 0 citations
Bipolar disorder is strongly associated with financial instability. We examine how different interventions motivate individuals with bipolar disorder to share financial data with others. This approach can inform the development of tools for digital monitoring and intervention designed to promote financial stability in...
Jeff Brozena, Johnna Blair, Dahlia Mukherjee et al.· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
Crossing-based selection is well-studied, yet past research has overlooked multi-object and attribute selection with crossing gestures. We present viaCross, a pen-based technique in which crossing strokes define attribute constraints, paired with attribute widgets that visualize and allow subsequent edits to these cons...
Benedict Leung, Mariana Shimabukuro, Christopher Collins· 0 citations
Online students often face emotional challenges such as frustration, isolation, and fluctuating motivation, which can hinder sustained engagement in online learning. While affective chatbots have shown promise in healthcare and wellness, most learning support chatbots focus primarily on cognitive assistance with limite...
AI sycophancy, the tendency of AI systems to excessively agree with, flatter, or validate users, is an emerging concern in human-AI interaction. It is especially consequential in problem-sharing contexts, where users may seek both information and emotional validation. This paper conceptualizes AI sycophancy as excessiv...
AI-driven hazard tools are increasingly proposed for resident-facing risk communication. However, residents are often asked for feedback only after decisions about data use, privacy, and explanation have been made. This study takes an earlier approach by examining residents' values, concerns, and practical expectations...
Sanaz Sadat Hosseini, Mona Azarbayjani, Mohammad Pourhomayoun et al.· 0 citations
Objective. Ear-worn biopotential devices are being designed around a coupling that has not been computed: how strongly each speech articulator reaches electrodes on the jaw and around the ear. We compute it, and test the answer against the three things that could produce it spuriously - source orientation, electrode co...
In cognitive psychology, the sense of agency refers to the feeling of controlling an external event through one's own actions. This paper asks how people experience agency when they give an instruction to a computer, which then acts on their behalf. Research in human-human interaction has found that while people experi...
Johanna Didion, Diego Garaialde, David Coyle· 0 citations
Recent program evolution systems use large language models (LLMs) to generate and iteratively improve populations of programs, producing striking advances in mathematics, algorithm design, and scientific computing. Yet these systems largely operate as fully automated black boxes. As populations grow, domain experts mus...
Feng Liang, Sizhe Cheng, Yikai Li et al.· 0 citations
Continuous colormaps are widely used to visualize scalar fields, and their quality is typically evaluated using measures such as discriminative power and uniformity. Existing measures primarily characterize the intrinsic perceptual properties of the colormap itself, largely independent of the underlying data distributi...
Xi Duan, Yiwei Lin, Shiqing Xin 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.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
