Agentic artificial intelligence (AI) is shifting from decision support to autonomous coordination, challenging established assumptions about managerial authority. This qualitative conceptual paper synthesises recent literature in algorithmic management, organisational theory, and human-computer interaction to examine h...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
It is argued that preventing lasting harm to young adults'dvelopment is paramount, and implications for rethinking AI chatbot dependence grounded in this understanding are provided.
Ashlee Milton, L. Ajmani, Amy K. Heger et al.· 1 citation
Concept Bottleneck Models (CBMs) are interpretable-by-design neural networks that detect human-understandable concepts from the input and use them to generate predictions. By allowing users to inspect the concepts underlying a prediction and explore how predictions change under alternative concept configurations, CBMs...
A. Bogani, Nicola Debole, E. Marconato et al.· 0 citations
Tact, a browser-based pipeline that converts a spoken or typed story idea into printable braille with a matching raised tactile illustration, without an account or mandatory cost and with an offline-capable path is presented.
Iliano Fasolino· Zenodo (CERN European Organi...· 0 citations
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In exploratory factor analysis (EFA), one aims to describe latent variables by constructing a factor model based on the relationships among manifest variables. For a model to be useful, it is not enough that it is grounded on data; it must also be meaningful. Hence, in practice, one attempts to interpret different fact...
Justin Philip Tuazon, Joemari Olea, Richelle Ann Juayong· 0 citations
Browser-based webcam gaze trackers are increasingly used for crowd-scale data collection and in clinical settings where lab eye trackers are impractical, but the reported latency numbers may not represent real world functionality. The common practice of timestamping each gaze sample when it is emitted, rather than when...
Proactive assistance with large language models (LLMs) has received growing attention in the human computer interaction (HCI) community. However, most past work on proactive LLMs' assistance has focused on adult users and task-oriented settings, leaving open how such systems could support children, whose interests and...
Building on critical feedback and concerns, Fabula is used as a cultural probe in adversarial design, and potentials for writing feedback and for interactive storytelling are identified.
P. Mirowski, Benjamin D. Wedin, Reinald Kim Amplayo et al.· arXiv.org· 1 citation
People passively interact with ambient surfaces such as tables, chair backs, and armrests throughout daily life, making them natural candidates for ubiquitous tactile interfaces. However, transforming these everyday surfaces into practical haptic interfaces remains challenging. Existing solutions typically rely on dens...
Shubham Rohal (University of California, Merced), Dong Yoon Lee (University of California et al.· 0 citations
Sign Parameter-Infused (SPI) prompting is introduced, which integrates standard SL parameters, like hand shape, motion, and orientation, directly into the textual prompts, which makes the instructions more structured and reproducible than free-form natural text from vanilla prompting.
Recent advances in large language models (LLMs) have shown great potential in automating the process of visualization authoring through simple natural language utterances. However, instructing LLMs using natural language is limited in precision and expressiveness for conveying visualization intent, leading to misinterp...
Zhen Wen, Luoxuan Weng, Yinghao Tang et al.· 0 citations
This work proposes Caption-once, Frames-onDemand (CFD), a budget-aware edge-cloud agentic framework that turns visual access into a first-class, query-conditioned cost, capping per-query frame consumption regardless of video length.
Wei-Tong Cai, Hang Zhang, Yu-Kai Huang et al.· 2 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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