10 papers · 1 filter
Explaining Too Much? Understanding How Large Language Model Reasoning Traces Influence Performance and Metacognition
Daniela Fernandes, Daniel Buschek, Lev Tankelevitch +2
Large Language Model interfaces are increasingly verbose, exposing intermediate reasoning traces alongside final answers. Traces are framed as transparency mechanisms, yet it is un…
Nudging Attention to Workplace Meeting Goals: A Large-Scale, Preregistered Field Experiment
Lev Tankelevitch, Ava Elizabeth Scott, Nagaravind Challakere +2
Ineffective meetings are pervasive. Thinking ahead explicitly about meeting goals may improve effectiveness, but current collaboration platforms lack integrated support. We tested…
Metacognition and Confidence Dynamics in Advice Taking from Generative AI
Clara Colombatto, Sean Rintel, Lev Tankelevitch
Generative Artificial Intelligence (GenAI) can aid humans in a wide range of tasks, but its effectiveness critically depends on users being able to evaluate the accuracy of GenAI o…
Understanding, Protecting, and Augmenting Human Cognition with Generative AI: A Synthesis of the CHI 2025 Tools for Thought Workshop
Lev Tankelevitch, Elena L. Glassman, Jessica He +7
Generative AI (GenAI) radically expands the scope and capability of automation for work, education, and everyday tasks, a transformation posing both risks and opportunities for hum…
What Does Success Look Like? Catalyzing Meeting Intentionality with AI-Assisted Prospective Reflection
Ava Elizabeth Scott, Lev Tankelevitch, Payod Panda +3
Despite decades of HCI and Meeting Science research, complaints about ineffective meetings are still pervasive. We argue that meeting technologies lack support for prospective refl…
Are We On Track? AI-Assisted Active and Passive Goal Reflection During Meetings
Xinyue Chen, Lev Tankelevitch, Rishi Vanukuru +3
Meetings often suffer from a lack of intentionality, such as unclear goals and straying off-topic. Identifying goals and maintaining their clarity throughout a meeting is challengi…