Matt Groh
@mattgroh
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Assistant professor @NorthwesternU @KelloggSchool | PhD @MIT @medialab | human AI collaboration | computational social science | cognitive science
Cambridge, MA
Joined May 2012
🚨 New paper in @NatureComms 🚨. We created deepfakes of the current & former @POTUS giving speeches (w/ voices from voice actors & @elevenlabsio) to study what drives how well people can tell fake speeches from real ones. Time to update the "Seeing is Believing" narrative.👇.
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How do should we measure the value of an explanation?. First, we need a goal of what the explanation should do. Then, we need to evaluate how the explanation is moving a decision maker towards that goal. Must read for thinking about human-AI collaboration.
Explainable AI has long frustrated me by lacking a clear theory of what explanations should do. Improve use of a model for what? How? Given a task what's max effect explanation can have? It's complicated bc most methods are functions of features & prediction but not true state 1/.
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The human touch matters a great deal for empathic support! Awesome new research to check out.
🚨New paper Alert! So many people ask AI for emotional support – but is it like support from a human? Our new paper published in @NatureHumBehav explores whether people value #AI - generated #empathy as much as human empathy, in 9 preregistered studies with 6,282 participants.🧵.
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RLCF: Reinforcement Learning with Community Feedback. This is an awesome Human-AI Collaboration research agenda.
🚨🚨 Excited to share a new paper led by @Li_Haiwen_ with the @CommunityNotes team!. LLMs will reshape the information ecosystem. Community Notes offers a promising model for keeping human judgment central but it's an open question how to best integrate LLMs. Thread👇
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RT @Diyi_Yang: Our study led by @ChengleiSi reveals an “ideation–execution gap” 😲. Ideas from LLMs may sound novel, but when experts spend….
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How do we reliably judge if AI companions are performing well on subjective, context-dependent, and deeply human tasks? 🤖. Excited to share the first paper from my postdoc (!!) investigating when LLMs are reliable judges - with empathic communication as a case study 🧐. 🧵👇
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What is Claude's EQ?. Awesome look into affective convos w/ LLMs. Highlights:. - 3% of all convos are affective.- Claude pushes back 10% of time.- People on avg express more positivity over course of convo. Related q: How well do LLMs recognize effective empathic support? See 👇.
New Anthropic Research: How people use Claude for emotional support. From millions of anonymized conversations, we studied how adults use AI for emotional and personal needs—from navigating loneliness and relationships to asking existential questions.
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"My survival as an artist will depend on whether I’ll be able to offer something that A.I. can’t: drawings that are as powerful as a birthday doodle from a child.". Epic visual story by @abstractsundayby in NYT Magazine
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Awesome work showing the metaphors the general public use to describe AI. And interesting to juxtapose this to the popular metaphors described by Melanie Mitchell
How does the public conceptualize AI? Rather than self-reported measures, we use metaphors to understand the nuance and complexity of people’s mental models. In our #FAccT2025 paper, we analyzed 12,000 metaphors collected over 12 months to track shifts in public perceptions.
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When are LLMs-as-judge reliable? . That's a big question for frontier labs and it's a big question for computational social science. Excited to share our findings (led by @aakriti1kumar!) on how to address this question for any subjective task & specifically for empathic comms.
How do we reliably judge if AI companions are performing well on subjective, context-dependent, and deeply human tasks? 🤖. Excited to share the first paper from my postdoc (!!) investigating when LLMs are reliable judges - with empathic communication as a case study 🧐. 🧵👇
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Awesome tutorial!.
Curious how to build agents that can control a browser? I just wrote up a full tutorial on how to do it completely from scratch and with Magentic-UI. My goal is to demystify browser-use and CUA agents, it's fun to follow along!. Link: Jupyter notebook:
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Veo3 represents a paradigm shift in AI capabilities for realistic media that tells provocative, fabricated stories. This video + thread offer a quick tutorial of the capabilities and limitations (like malformed text & character consistency) that are easy to creatively bypass.
I decided to use my lunch time to show you how easy it is to make a fake news story in 30 minutes with Veo3 (I didn't try to perfect it). First: the footage. A mayor comes with a crazy idea and people hate it: (1/10) #verification #ai
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RT @JessicaHullman: Decision studies appear in HCI, vis, & AI/ML, but how “good decision” is defined is often ad-hoc. My #CHI2025 talk to….
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If you're curious about learning more, say hi to @n3gRain at #CHI2025 and see links below. Awesome collaboration with @frogspitsimulat, @aakriti1kumar, @chatzimparmpas.@JessicaHullman. Video: Preprint: CHI:
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This taxonomy offers a shared language (and see our how to guide on arXiv for many examples) to help people better communicate what looks or feels off. It's also a framework that can generalize to multimedia. Consider this, what do you notice at the 16s mark about her legs?
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Based on generating thousands of images, reading the AI-generated images and digital forensics literatures (and social media and journalistic commentary), analyzing 30k+ participant comments, we propose a taxonomy for characterizing diffusion model artifacts in images
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Scene complexity, artifact types, display time, and human curation of AI-generated images are play significant roles in how accurately people distinguish real and AI-generated images.
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