Publications (26)
A Canary in the AI Coal Mine: American Jews May Be Disproportionately Harmed by Intellectual Property Dispossession in Large Language Model Training
Heila Precel, Allison McDonald, Brent Hecht +1
Systemic property dispossession from minority groups has often been carried out in the name of technological progress. In this paper, we identify evidence that the current paradigm…
Algorithmic Collective Action with Two Collectives
Aditya Karan, Nicholas Vincent, Karrie Karahalios +1
Given that data-dependent algorithmic systems have become impactful in more domains of life, the need for individuals to promote their own interests and hold algorithms accountable…
Push and Pull: A Framework for Measuring Attentional Agency on Digital Platforms
Zachary Wojtowicz, Shrey Jain, Nicholas Vincent
We propose a framework for measuring attentional agency, which we define as a user's ability to allocate attention according to their own desires, goals, and intentions on digital…
A Deeper Investigation of the Importance of Wikipedia Links to the Success of Search Engines
Nicholas Vincent, Brent Hecht
A growing body of work has highlighted the important role that Wikipedia's volunteer-created content plays in helping search engines achieve their core goal of addressing the infor…
Mechanism Plausibility in Generative Agent-Based Modeling
Patrick Zhao, David Huu Pham, Nicholas Vincent
Large language models (LLMs) can generate high-level diverse phenomena without explicitly programmed rules. This capability has led to their adoption within different agent-based m…
Mapping the Potential and Pitfalls of "Data Dividends" as a Means of Sharing the Profits of Artificial Intelligence
Nicholas Vincent, Yichun Li, Renee Zha +1
Identifying strategies to more broadly distribute the economic winnings of AI technologies is a growing priority in HCI and other fields. One idea gaining prominence centers on "da…
WikiGap: Promoting Epistemic Equity by Surfacing Knowledge Gaps Between English Wikipedia and other Language Editions
Zining Wang, Yuxuan Zhang, Dongwook Yoon +3
With more than 11 times as many pageviews as the next largest edition, English Wikipedia dominates global knowledge access relative to other language editions. Readers are prone to…
Behavioral Use Licensing for Responsible AI
Danish Contractor, Daniel McDuff, Julia Haines +5
With the growing reliance on artificial intelligence (AI) for many different applications, the sharing of code, data, and models is important to ensure the replicability and democr…
Addressing "Documentation Debt" in Machine Learning Research: A Retrospective Datasheet for BookCorpus
Jack Bandy, Nicholas Vincent
Recent literature has underscored the importance of dataset documentation work for machine learning, and part of this work involves addressing "documentation debt" for datasets tha…
Responsible AI in Open Ecosystems: Reconciling Innovation with Risk Assessment and Disclosure
Mahasweta Chakraborti, Bert Joseph Prestoza, Nicholas Vincent +1
The rapid scaling of AI has spurred a growing emphasis on ethical considerations in both development and practice. This has led to the formulation of increasingly sophisticated mod…
Online Engagement with Retracted Articles: Who, When, and How?
Henry K. Dambanemuya, Rod Abhari, Nicholas Vincent +1
Retracted research discussed on social media can spread misinformation. Yet we lack an understanding of how retracted articles are mentioned by academic and non-academic users. Thi…
Retracted Articles about COVID-19 Vaccines Enable Vaccine Misinformation on Twitter
Rod Abhari, Esteban Villa-Turek, Nicholas Vincent +2
Retracted scientific articles about COVID-19 vaccines have proliferated false claims about vaccination harms and discouraged vaccine acceptance. Our study analyzed the topical cont…
If open source is to win, it must go public
Joshua Tan, Nicholas Vincent, Katherine Elkins +5
Open source projects have made incredible progress in producing widely usable machine learning models and systems, but open source alone will face challenges in fully democratizing…
Sync or Sink: Bounds on Algorithmic Collective Action with Noise and Multiple Groups
Aditya Karan, Prabhat Kalle, Nicholas Vincent +1
Collective action against algorithmic systems provides an opportunity for a small group of individuals to strategically manipulate their data to get specific outcomes, from classif…
AI for Just Work: Constructing Diverse Imaginations of AI beyond "Replacing Humans"
Weina Jin, Nicholas Vincent, Ghassan Hamarneh
"why" we develop AI. Lacking critical reflections on the general visions and purposes of AI may make the community vulnerable to manipulation. In this position paper, we explore th…
An Alternative to Regulation: The Case for Public AI
Nicholas Vincent, David Bau, Sarah Schwettmann +1
Can governments build AI? In this paper, we describe an ongoing effort to develop ``public AI'' -- publicly accessible AI models funded, provisioned, and governed by governments or…
Open WebUI: An Open, Extensible, and Usable Interface for AI Interaction
Jaeryang Baek, Ayana Hussain, Danny Liu +2
While LLMs enable a range of AI applications, interacting with multiple models and customizing workflows can be challenging, and existing LLM interfaces offer limited support for c…
The Dimensions of Data Labor: A Road Map for Researchers, Activists, and Policymakers to Empower Data Producers
Hanlin Li, Nicholas Vincent, Stevie Chancellor +1
Many recent technological advances (e.g. ChatGPT and search engines) are possible only because of massive amounts of user-generated data produced through user interactions with com…
Tracing Everyday AI Literacy Discussions at Scale: How Online Creative Communities Make Sense of Generative AI
Haidan Liu, Poorvi Bhatia, Nicholas Vincent +1
Developing AI literacy is increasingly urgent as generative AI reshapes creative practice. Yet most AI literacy frameworks are top-down and expert-driven, overlooking how literacy…
Data Leverage: A Framework for Empowering the Public in its Relationship with Technology Companies
Nicholas Vincent, Hanlin Li, Nicole Tilly +2
Many powerful computing technologies rely on implicit and explicit data contributions from the public. This dependency suggests a potential source of leverage for the public in its…
How Creatives Approach GenAI Image Generation: Tensions Between Structured Guidance, Self-Experimentation, and Creative Autonomy
Haidan Liu, Isabelle Kwan, Taiga Okuma +3
As generative AI tools increasingly influence creative practice, they raise longstanding HCI questions about how creatives learn complex software and how they can be better support…
Overreliance in Writing Tasks: Exploring Similarity-Based Measures of AI Influence on Writing and Proposing a Reflective Writing Interface Intervention
Vitor H. A. Welzel, Nicholas Vincent
As generative AI (GenAI) systems become increasingly proficient at simulating human-like and well-reasoned text, users may attribute authority to AI outputs, shaping how they engag…
An Audit and Analysis of LLM-Assisted Health Misinformation Jailbreaks Against LLMs
Ayana Hussain, Patrick Zhao, Nicholas Vincent
Large Language Models (LLMs) are a double-edged sword capable of generating harmful misinformation -- inadvertently, or when prompted by "jailbreak" attacks that attempt to produce…
Measuring the Importance of User-Generated Content to Search Engines
Nicholas Vincent, Isaac Johnson, Patrick Sheehan +1
Search engines are some of the most popular and profitable intelligent technologies in existence. Recent research, however, has suggested that search engines may be surprisingly de…
IDP-Bench: Benchmarking ability of LLMs to protect personal information in interdependent privacy contexts
Ayana Hussain, Soumya Sharma, Golnoosh Farnadi +3
Large language models (LLMs) are becoming widely deployed as personal AI assistants with access to sensitive user data, making privacy a major challenge for their design and evalua…
Collective Bargaining in the Information Economy Can Address AI-Driven Power Concentration
Nicholas Vincent, Matthew Prewitt, Hanlin Li
This position paper argues that there is an urgent need to restructure markets for the information that goes into AI systems. Specifically, producers of information goods (such as…