AI tools for digital product design now offer prompt-to-design capabilities, allowing designers and their non-designer colleagues to create prototypes through conversational workflows with large language models (LLMs). While these tools promise time savings, experimental evidence in product design remains limited compa...
Remy Stewart, Olabode Anise, Andrew Hogan et al.· 0 citations
A central concern with language models is sycophancy: their tendency to defer to users'views at the expense of independent substantive judgment. In parallel, work on social sycophancy has focused on behaviors such as validation and positivity that may signal inappropriate deference. Yet the markers of social sycophancy...
C. Isley, Johann D. Gaebler, Max Lamparth et al.· 1 citation
It is proposed that CNN training's classification bottleneck compresses brain-relevant information at depth, unlike transformers's self-attention and non-classification objectives, which reflect signal strength and persistence rather than distinct brain regions.
S. Baghel, Kshitij Dwivedi, Dinesh Singh et al.· 0 citations
Deep learning systems now mediate military decisions to use force, yet their internal logic resists inspection, their evaluation practices are gameable, and their deployment fractures accountability across dispersed stakeholders. The ethical challenge posed by these systems is fundamentally epistemic: not just whether...
Nicolas Drapier, Florian Mauberger, Aladine Chetouani et al.· 0 citations
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Large language models increasingly support decisions where values are in tension, yet little is known about whether interacting with them changes which values users prioritize. In a preregistered study, 200 U.S. adults interacted with ChatGPT, Claude, or Gemini as a thinking partner or read fixed AI-generated considera...
A chatbot-building environment with adjustable trust-relevant traits, describing what children believe makes a chatbot trustworthy, is developed, and seven design dimensions describing what children believe makes a chatbot trustworthy are identified.
Deniz Ozturk, Jia-Yu Li, Dakshita Singh et al.· 0 citations
This brief presents a circuit-level conductive-textile interconnection technique for batteryless distributed wearable modules. Two conductive textile layers separated by an insulating fabric layer are used as a garment-wide shared bus that simultaneously conveys DC power and pulse-based data signals without point-to-po...
Programming a robot arm requires users to interpret coordinate frames, joint rotations, and trajectories that are not directly visible. Augmented reality (AR) can make these spatial relations visible, but its benefits may depend on users' spatial ability. We conducted a randomized between-subjects experiment ($N=71$) i...
Nicolas Leins, Muriel Fischer, Malte Teichmann et al.· 0 citations
Explainable artificial intelligence (XAI) reveals how explanatory variables relate to a response variable, yet communicating XAI outputs to laypersons remains difficult, limiting trust in AI-based predictions. Large language models (LLMs) can translate technical explanations into accessible narratives, but iterative re...
Tomoaki Yamaguchi, Yutong Zhou, Masahiro Ryo et al.· 0 citations
We present the Extended Reality Universal Planning Toolkit (ERUPT), an extended reality (XR) system for interactive motion planning. This paper serves to introduce our open-source system to others who can use it as a base to develop immersive robot interaction applications. Our system allows users to create and dynamic...
Isaac Ngui, Courtney McBeth, Andr\'e Santos et al.· 0 citations
Voice is a central element of identity. We recognize people by their voice, and we uniquely express who we are with it. For people who rely on augmentative and alternative communication (AAC) systems, such as speech-generating devices (SGD), the device's voice becomes an identity marker others associate with them. Yet,...
Tobias Weinberg, Aaleyah Lewis, Ricardo E. Gonzalez Penuela et al.· 0 citations
People increasingly turn to LLMs for emotional support, yet common evaluations reward responses that feel helpful and may miss consequential response behaviors. We introduce a theory-informed measurement framework that decomposes LLM emotional-support responses into Soothe (affective comfort), Reframe (cognitive perspe...
Vivienne Bihe Chi, Adithya V Ganesan, Ryan L Boyd 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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