The current paradigm of artificial intelligence (AI) design elevates conversational chatbot interfaces, making them the default mode through which hundreds of millions of people interact with AI systems globally. This narrative review identifies three related harms produced by the single-voice chatbot interface, drawin...
Avijit Ghosh, Afifah Kashif, Isabelle Kohout et al.· 0 citations
This work synthesizes findings into a conceptual model explaining how teachers coordinate instructional intent, AI assistance, and judgments of classroom readiness during lesson authoring while preserving teacher control and addressing computing-specific authoring needs.
Tahreem Yasir, Wen-Bo Li, Deniz Ozturk et al.· 0 citations
Aggregated academic search interfaces combine resources from heterogeneous sources, such as scholarly libraries and reference encyclopedias, into a single workspace. Such tasks frequently span multiple sessions, requiring learners to return to and resume work after hours or days. End-of-session consolidation, the activ...
Instructions to assemble flat-packed furniture rely on visuals, making them inaccessible to Blind and Low Vision (BLV) individuals. Consequently, BLV individuals depend on caregivers or external services (e.g., Be My Eyes), limiting their autonomy. We explore how to empower them to assemble such furniture themselves, b...
Bo Liu, Gene S.-H. Kim, Franklin Mingzhe Li et al.· 0 citations
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Community accounts of ADHD can complement clinical understandings by foregrounding members'own definitions of time-management difficulties and support. We used human-led, LLM-assisted thematic analysis to examine 5,379 relevant r/ADHD posts from 2020 to 2025. Across five challenge and nine strategy themes, members desc...
Shi-Zhao Liu, Lei Cao, Celia T. Lee et al.· 0 citations
Perspectivist NLP has established that annotator positionality shapes labels for subjective tasks, but the field still lacks methods for operationalising it. Positionality is typically operationalised as a demographic form completed at recruitment: a static attribute recorded once and treated as a covariate, on the ass...
While adaptive experimental design has outgrown one-dimensional, staircase-based adaptations, most cognitive experiments still control a single factor and summarize performance with a scalar. In contrast, we validate here a Bayesian, two-axis, active-classification approach in an immersive virtual testing environment,...
Dom CP Marticorena, Chris Wissmann, Zeyu Lu et al.· 0 citations
Vision-language-action (VLA) policies issue sparse targets whose arrival at the robot controller is delayed and irregular, so a reasonable predicted action can still produce abrupt motion near people. Remedies are evaluated on different streams, delays and metrics. JitterVLA replays identical commands and arrival trace...
Faith Ogunwoye, Didar Seyidov, Konstantin Gubernatorov et al.· 0 citations
High-risk applications of deep learning require precise characterization of model decision-making. We conduct a systematic explainability evaluation across Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), and Vision Mamba (ViM). Unlike predominantly qualitative studies, we quantify the alignment betwee...
Marco Stefani, Edoardo Parpaiola, Matteo Bino et al.· 0 citations
Generative creative interfaces routinely report the user's position within a space of possibilities. Such displays imply that the quantities shown were measured from the artefact; in a growing class of systems they are instead predicted by a language model describing its own output, and the two are indistinguishable on...
Large language models (LLMs) are increasingly under scrutiny for perpetuating identity-based discrimination in high-stakes domains such as hiring, particularly against people with disabilities (PwD). However, existing research remains largely Western-centric, overlooking how intersecting forms of marginalization--such...
Mahika Phutane, Hayoung Jung, Matthew Kim et al.· 0 citations
Large language models (LLMs) are increasingly used to simulate students at different mastery levels to generate synthetic training data and stress-test tutoring systems. Existing approaches primarily leverage an LLM to answer questions or perform tests while instructing it to simulate various skill levels. However, LLM...
Yuan An, Emily Wang, Benjamin Wang et al.· 0 citations
AI agents can generate code at a scale that’s hard for humans to review line-by-line. PDD Kit helps ensure the code is doing what the developer intended by creating formal specifications and testing against them. It converts developer intent into a Verus specification, proves AI-generated code meets it for every input, and uses tests where proofs aren't practical. Developers review intent, not every line. The post Formally verifying agent-written full-stack web apps with PDD Kit appeared first o…
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
MIT News · Artificial Intelligence· news.mit.eduOct 23, 2026
During the School of Humanities, Arts, and Social Sciences’ 75th Anniversary Symposium, President Sally Kornbluth said “MIT has never needed your particular insight and guidance more than we do now.”
MIT News · Artificial Intelligence· news.mit.eduOct 23, 2026
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
MIT News · Artificial Intelligence· news.mit.eduOct 22, 2026
“X-Hinges” helps design and 3D print items like lamps and gloves with an interactive twist: automatically embedded sensors that perceive and adaptively respond to human contact.
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