Augmented Mind Podcast

Bridging Human-AI Grounding Gaps with Omar Shaikh | AM Podcast #1

Augmented Mind Podcast

Show Notes

Omar Shaikh is a Stanford PhD student, HCI and NLP researcher, and author of the award-winning UIST 2025 paper “Creating General User Models from Computer Use”. Omar’s pioneering work aims to bridge the Human-AI grounding gap.

Outline: 0:00 - Teaser 1:21 - Prelude: Introducing Omar Shaikh 2:07 - Monologue: Better Context for AI 4:22 - Bridging the Human-AI Grounding Gap 6:14 - Confidence scores in General User Models (GUMs) 7:32 - Calibration of General User Models 13:20 - Uses of General User Models 15:01 - Mixed Initiative Interactions 22:10 - Motivation for GUM 25:31 - Tabracadabra: tab everywhere! 27:01 - Design decisions in GUM 28:26 - Designing Interactive Experiences 32:11 - DITTO: https://arxiv.org/abs/2406.00888 33:06 - Work on Domains without Existing Benchmarks 34:45 - Challenges of the GUM Project 37:26 - Privacy and Data Ownership 38:57 - Finetuning a User Model 44:09 - Mindblowing GUM Inferences 49:02 - Social Problems of GUMs 50:27 - GUM as a Reflection Tool

References: Omar Shaikh’s research homepage: https://oshaikh.com/

Creating General User Models from Computer Use: https://arxiv.org/abs/2505.10831

Tabracadabra: https://x.com/oshaikh13/status/1967626897837494479

Aligning Language Models with Demonstrated Feedback: https://arxiv.org/abs/2406.00888

Principles of Mixed-Initiative User Interfaces: https://erichorvitz.com/chi99horvitz.pdf

Verification of Forecasts Expressed in Terms of Probability: https://journals.ametsoc.org/view/journals/mwre/78/1/1520-0493_1950_078_0001_vofeit_2_0_co_2.xml

Podcast Links: Podcast website: https://augmented-mind.github.io/

Apple Podcasts: https://podcasts.apple.com/us/podcast/augmented-mind-podcast/id1868102170

Spotify: https://open.spotify.com/show/40KculkYTe2tOpqJm6TAYr?si=PU_UncsMT4mXjVNCRwoXog

RSS: https://anchor.fm/s/10dbf5b7c/podcast/rss

About the Hosts: The AM Podcast is hosted by Yijia Shao, Shannon Shen, and Michael Ryan, CS PhD students at Stanford University and MIT.

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