Cornell Tech

schoolSchoolbar_chart#129 Global Rank

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#129

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Recent Publications

Comparing Fabrication Workflows in CAD to Support Design Reasoning

When novices fabricate, they start by choosing a workflow (e.g., laser cutting, 3D printing, etc.) and corresponding software from a narrow set they know. As they advance their design, another workflow might better suit their intent, but their models remain committed to the original workflow. This prohibits exploratio…

CHI '26Content Moderation & Platform Governance +3

Beyond Community Notes: A Framework for Understanding and Building Crowdsourced Context Systems for Social Media

Social media platforms are increasingly adopting features that display crowdsourced context alongside posts, a technique pioneered by X's Community Notes. These systems---which we term \textit{Crowdsourced Context Systems} (CCS)---have the potential to reshape the information ecosystem as major platforms embrace them…

CHI '26Intelligent Voice Assistants (Alexa, Siri, etc.) +2

Lost in Transcription: Subtitle Errors in Automatic Speech Recognition Reduce Speaker and Content Evaluations

Researchers have demonstrated that Automatic Speech Recognition (ASR) systems perform differently across demographic groups. In this work, we examined how subtitle errors affect evaluations of speakers and their content using a preregistered online experiment (N=207, U.S.-based crowdworkers). Participants watched spea…

CHI '26Privacy Perception & Decision-Making +1

Who Is At Risk? Examining the Prevalence of Digital-Safety Attacks and Contextual Risk Factors in the United States

A growing body of qualitative research has identified contextual risk factors that elevate people’s chances of experiencing digital-safety attacks. However, the lack of quantitative data on the population-level distribution of these risk factors prevents policymakers and tech companies from developing targeted, evide…

CHI '26Human-LLM Collaboration +2

Sharing the Care: Investigating How Conversational AI Might Facilitate Coordination Among Home Care Workers and Family Caregivers

This paper presents a qualitative study with 17 participants that uses video elicitations to investigate how conversational AI agents driven by large language models might support "shared care," or coordination of home-based care among family caregivers (FCs) and home care workers (HCWs) who care for the same care rec…

CHI '26Universal & Inclusive Design +2

Understanding How Accessibility Practices Impact Teamwork in Mixed-Ability Teams that Collaborate Virtually

Virtual collaboration has transformed how people in mixed-ability teams, composed of disabled and non-disabled people, work together by offering greater flexibility. In these settings, accessibility practices, such as accommodations and inclusive norms, are essential for providing access to disabled people. However, w…

CHI '26Honorable MentionHuman-LLM Collaboration +2

How Multimodal Large Language Models Support Access to Visual Information: A Diary Study With Blind and Low Vision People

Multimodal large language models (MLLMs) are changing how Blind and Low Vision (BLV) people access visual information. Unlike traditional visual interpretation tools that only provide descriptions, MLLM-enabled applications offer conversational assistance, where users can ask questions to obtain goal-relevant details.…

CHI '26Human-LLM Collaboration +3

Reactive Writers: How Co-Writing with AI Changes How We Engage with Ideas

Emerging evidence shows that writing with AI assistance can change both the views people express and the opinions they hold. Yet, we lack a substantive understanding of behavioral and process-level changes in co-writing with AI that underlie the opinion-shaping power of these tools. We conducted a mixed-methods study,…

CHI '26Explainable AI (XAI) +2

"Having Confidence in My Confidence Intervals": How Data Users Engage with Privacy-Protected Wikipedia Data

In response to calls for open data and growing privacy threats, organizations are increasingly adopting privacy-preserving techniques that add noise to published datasets. These techniques seek to protect privacy of data subjects while enabling useful analyses. With expert feedback, we developed empirically-driven doc…

CHI '26Human-Robot Collaboration (HRC) +2

Towards Considerate Embodied AI: Co-Designing Situated Multi-Site Healthcare Robots from Abstract Concepts to High-Fidelity Prototypes

Co-design is essential for grounding embodied artificial intelligence (AI) systems in real-world contexts, especially high-stakes domains such as healthcare. While prior work has explored multidisciplinary collaboration, iterative prototyping, and support for non-technical participants, few have interwoven these into…

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At a Glance

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Cornell Tech

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United States · North America

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#129

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2018-2026

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32 researchers · 4 collaborators

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AI & Machine Learning Interaction

AI Ethics, Fairness & Accountability

Privacy, Security & Trust

Privacy by Design & User Control

Research Methods & Design Practice

Participatory Design

Ethics, Fairness, Social Justice & Inclusion

Empowerment of Marginalized Groups

Social Media & Online Communities

Content Moderation & Platform Governance