25 citations · 43 across the 10 of their papers we have counts for
12 papers
Information Discernment in Large Language Models
Joshua Ashkinaze, Laura Kurek, Alina Faisal +4
LLMs are increasingly used with external knowledge sources like the internet. Do they weigh information appropriately -- updating more for reliable sources (source discernment) and…
Follow Nudges without Budges: A Field Experiment on Misinformation Followers Didn't Change Follow Networks
Laura Kurek, Joshua Ashkinaze, Ceren Budak +1
Can digital ads encourage users exposed to inaccurate information sources to follow accurate ones? We conduct a large-scale field experiment (N=28,582) on X, formerly Twitter, with…
Introducing AI to an Online Petition Platform Changed Outputs but not Outcomes
Isabel Corpus, Eric Gilbert, Allison Koenecke +1
The rapid integration of AI writing tools into online platforms raises critical questions about their impact on content production and outcomes. We leverage a unique natural experi…
Deep Value Benchmark: Measuring Whether Models Generalize Deep Values or Shallow Preferences
Joshua Ashkinaze, Hua Shen, Saipranav Avula +2
We introduce the Deep Value Benchmark (DVB), an evaluation framework that directly tests whether large language models (LLMs) learn fundamental human values or merely surface-level…
Outsourcing an Information Operation: A Complete Dataset of Tenet Media's Podcasts on Rumble
Laura Kurek, Kevin Zheng, Eric Gilbert +1
Tenet Media, a U.S.-based, right-wing media company, hired six established podcasters to create content related to U.S. politics and culture during the 2024 U.S. presidential elect…
Capital and CHI: Technological Capture and How It Structures CHI Research
Eric Gilbert
This paper advances a theoretical argument about the role capital plays in structuring CHI research. We introduce the concept of technological capture to theorize the mechanism by…
Wikipedia in Wartime: Experiences of Wikipedians Maintaining Articles About the Russia-Ukraine War
Laura Kurek, Ceren Budak, Eric Gilbert
How do Wikipedians maintain an accurate encyclopedia during an ongoing geopolitical conflict where state actors might seek to spread disinformation or conduct an information operat…
Plurals: A System for Guiding LLMs Via Simulated Social Ensembles
Joshua Ashkinaze, Emily Fry, Narendra Edara +2
Recent debates raised concerns that language models may favor certain viewpoints. But what if the solution is not to aim for a 'view from nowhere' but rather to leverage different…
Seeing Like an AI: How LLMs Apply (and Misapply) Wikipedia Neutrality Norms
Joshua Ashkinaze, Ruijia Guan, Laura Kurek +3
Large language models (LLMs) are trained on broad corpora and then used in communities with specialized norms. Is providing LLMs with community rules enough for models to follow th…
HCC Is All You Need: Alignment-The Sensible Kind Anyway-Is Just Human-Centered Computing
Eric Gilbert
This article argues that AI Alignment is a type of Human-Centered Computing.
The Dynamics of (Not) Unfollowing Misinformation Spreaders
Joshua Ashkinaze, Eric Gilbert, Ceren Budak
Many studies explore how people 'come into' misinformation exposure. But much less is known about how people 'come out of' misinformation exposure. Do people organically sever ties…
How AI Ideas Affect the Creativity, Diversity, and Evolution of Human Ideas: Evidence From a Large, Dynamic Experiment
Joshua Ashkinaze, Julia Mendelsohn, Li Qiwei +2
Exposure to large language model output is rapidly increasing. How will seeing AI-generated ideas affect human ideas? We conducted an experiment (800+ participants, 40+ countries)…