
Nicholas Vincent
Assistant Professor · School of Computing Science, Simon Fraser University
Human activity is upstream of (many) AI capabilities; any system with data dependence creates potential governance and bargaining power; this has major implications for AI safety and for understanding how AI allocates power and delivers value to the world.
Data Value
Public AI
Evaluation and Social Simulation
Short bio
Prof. Nick Vincent is an Assistant Professor in Computing Science at Simon Fraser University and directs the People- and Data-centric Computing Research Group (PadComp). He studies the content ecosystems and data supply chains that fuel data-dependent technologies like search engines, recommender systems, and generative AI. This involves exploring avenues for people to control how data flows and participate in the governance of AI systems. The overarching goal of this research is to work towards highly capable and widely beneficial AI technologies that mitigate—rather than exacerbate—inequalities in wealth and power. His dissertation received the 2024 ACM SIGCHI Outstanding Dissertation Award.
Long bio

Nick Vincent is an Assistant Professor in Computing Science at Simon Fraser University and director of the People- and Data-centric Computing Research Group (PadComp). He studies the content ecosystems and data supply chains that fuel data-dependent technologies like search engines, recommender systems, and generative AI. This involves exploring avenues for people to control how data flows and participate in the governance of AI systems. The overarching goal of this research is to work towards highly capable and widely beneficial AI technologies that mitigate—rather than exacerbate—inequalities in wealth and power.
His work is published in responsible AI venues like ACM FAccT and human-computer interaction venues like ACM CHI. His dissertation on data leverage received the 2024 ACM SIGCHI Outstanding Dissertation Award.
Prof. Vincent was previously a postdoc working with the Computational Communication Research Lab at UC Davis and the Social Futures Lab at the University of Washington. He received his PhD from Northwestern University's Technology and Social Behavior program (a joint degree in computer science and communication), where he worked in the People, Space, and Algorithms Research Group.
During graduate school, he was a research intern at Snap and Microsoft. Before graduate school, he studied electrical engineering at UCLA, interned at Cisco, and conducted research at SPAWAR via the NREIP program.
- I am based in the School of Computing Science at Simon Fraser University and direct the People- and Data-centric Computing Research Group (padcomp).
Other affiliations
Public AI Network, ixLab, Digital Democracies Institute, Metagov, and SFU School of Public Policy - Online:BlueskyGitHubLinkedInX
- Papers:Google ScholarSemantic ScholarDBLP
- Writing:Digital GardenData Leverage Newsletter
Publications
Peer Reviewed
AI still has a vocabulary problem: toward terminological accountability in artificial intelligence
Position: If Open Source Is to Win, It Must Go Public
Overreliance in Writing Tasks: Exploring Similarity-Based Measures of AI Influence on Writing and Proposing a Reflective Writing Interface Intervention
Mechanism Plausibility in Generative Agent-Based Modeling
How Creatives Approach GenAI Image Generation: Tensions Between Structured Guidance, Self-Experimentation, and Creative Autonomy
Tracing Everyday AI Literacy Discussions at Scale: How Online Creative Communities Make Sense of Generative AI
Are We Horses? Rethinking Data as Labor
Collective Bargaining in the Information Economy Can Address AI-Driven Power Concentration
An Audit and Analysis of LLM-Assisted Health Misinformation Jailbreaks Against LLMs
Responsible AI in the OSS: Reconciling Innovation with Risk Assessment and Disclosure
Algorithmic Collective Action with Two Collectives
Push and Pull: A Framework for Measuring Attentional Agency on Digital Platforms
A Canary in the AI Coal Mine: American Jews May Be Disproportionately Harmed by Intellectual Property Dispossession in Large Language Model Training
Pika: Empowering Non-Programmers to Author Executable Governance Policies in Online Communities
Peer Produced Friction: How Page Protection on Wikipedia Affects Editor Engagement and Concentration
The Dimensions of Data Labor: A Road Map for Researchers, Activists, and Policymakers to Empower Data Producers
Behavioral Use Licensing for Responsible AI
CEAM: The Effectiveness of Cyclic and Ephemeral Attention Models of User Behavior on Social Platforms
Addressing "Documentation Debt" in Machine Learning: A Retrospective Datasheet for BookCorpus
AdverTiming Matters: Examining User Ad Consumption for Effective Ad Allocations on Social Media
Can "Conscious Data Contribution" Help Users to Exert "Data Leverage" Against Technology Companies?
A Deeper Investigation of the Importance of Wikipedia Links to Search Engine Results
Data Leverage: A Framework for Empowering the Public in its Relationship with Technology Companies
How Do People Change Their Technology Use in Protest?: Understanding Protest Users
Measuring the Importance of User-Generated Content to Search Engines
"Data Strikes": Evaluating the Effectiveness of a New Form of Collective Action Against Technology Companies
Women (Still) Ask For Less: Gender Differences in Hourly Rate in an Online Labor Marketplace
Examining Wikipedia With a Broader Lens: Quantifying the Value of Wikipedia's Relationships with Other Large-Scale Online Communities
Workshop / Pre-print
IDP-Bench: Benchmarking ability of LLMs to protect personal information in interdependent privacy contexts
WikiGap: Promoting Epistemic Equity by Surfacing Knowledge Gaps Between English Wikipedia and Minority Language Editions
Empowering Users Together: Connecting Algorithmic Collective Action and Explainable AI
Benchmarks 101
Sync or Sink: Bounds on Algorithmic Collective Action with Noise and Multiple Groups
Open WebUI: An Open, Extensible, and Usable Interface for AI Interaction
Epistemic Authority in AI Fact-Checking: A Human and Data Centric Perspective
Step-By-Step Reasoning with Meta Cognitive Prompts to Reduce Contextual Hallucination
Canada as a Champion for Public AI: Data, Compute and Open Source Infrastructure for Economic Growth and Inclusive Innovation
AI for Just Work: Constructing Diverse Imaginations of AI beyond "Replacing Humans"
Responsible AI in Open Ecosystems: Reconciling Innovation with Risk Assessment and Disclosure
A step forward in tracing and documenting dataset provenance
Designing an open-source LLM interface and social platforms for collectively driven LLM evaluation and auditing
The Need for Flexible Interfaces for Text-to-Image Auditing: A Case Study of DALL·E 2 and DALL·E 3
An Alternative to Regulation: The Case for Public AI
Sharing the Winnings of AI with Data Dividends: Challenges with 'Meritocratic' Data Valuation
Retracted Articles about COVID-19 Vaccines Enable Vaccine Misinformation on Twitter
Misleading Tweets and Helpful Notes: Investigating Data Labor by Twitter Birdwatch Users
Collaborative Design of Contribution Tracking Systems for Decentralized Organizations
Online Engagement with Retracted Articles: Who, When, and How?
Preview of "Data and its (dis)contents: A survey of dataset development and use in machine learning research"
From My Data to Our Data: A Proposal to Equitably Distribute Wealth in a Digital Economy
A Data Dividend that Works: Steps Toward Building an Equitable Data Economy
Mapping the Potential and Pitfalls of 'Data Dividends' as a Means of Sharing the Profits of Artificial Intelligence
Deep learning of tissue fate features in acute ischemic stroke
Detection of hyperperfusion on arterial spin labeling using deep learning
Other Writing
Writing hubs:Digital GardenData Leverage Newsletter
Hitting The Right Note: What AI Can Learn from Music Royalties
Oct 2026 — Centre for International Governance Innovation
How We Might Build “Augment, Don’t Replace” AI
Oct 2026 — Data Leverage Substack
The AI "Evaluation Crisis" Is an Opportunity to Get Data Flow Right
May 2026 — Data Leverage Substack
Attestation across the AI Supply Chain
Apr 2026 — Data Leverage Substack
"People First" Policy Ideas that Complement Each Other (through better data flow)
Apr 2026 — Data Leverage Substack
AI is driving the cost of polish down; some musings on fancy versus terse artifacts
Apr 2026 — Data Leverage Substack
Two natural allies of a "Data Transparency" agenda: capabilities forecasters and social simulators
Mar 2026 — Data Leverage Substack
A Short Guide to Data Strikes and Conscious Data Contribution in the Context of 2026 Frontier AI
Mar 2026 — Data Leverage Substack
The Paradox of Reuse in 2026: A Case of Quasi-Enclosure, or "Subsidized Club Goods that Sort of Look Like Public Goods"
Feb 2026 — Data Leverage Substack
The Coding Agent Data Deal
Jan 2026 — Data Leverage Substack
Coding agents are (1) a big deal, (2) very relevant to data leverage, and (3) able to help build tools that support data leverage!
Jan 2026 — Data Leverage Substack
Almost Everybody -- Including Both Data Creators and AI Companies -- Stands to Benefit from Clearer "Data Rules".
Nov 2025 — Data Leverage Substack
How collective bargaining for information, public AI, and HCI research all fit together
Oct 2025 — Data Leverage Substack
Which datasets should we assume are "in all the AI models"?
Sep 2025 — Data Leverage Substack
Algorithmic Collective Action With Two Collectives [crosspost]
Jun 2025 — Data Leverage Substack
On AI-driven Job Apocalypses and Collective Bargaining for Information
Jun 2025 — Data Leverage Substack
How do we know our AI output is good? Double checks, bar charts, vibes, and training data.
May 2025 — Data Leverage Substack
Each Instance of "AI Utility" Stems from Some Human Act(s) of Information Recording and Ranking
May 2025 — Data Leverage Substack
Google and TikTok rank bundles of information; ChatGPT ranks grains.
May 2025 — Data Leverage Substack
[microblog] One book is worth "0.06%" benchmark points to AI; is "no different from noise". What gives?
Apr 2025 — Data Leverage Substack
Public AI, Data Appraisal, and Data Debates
Apr 2025 — Data Leverage Substack
Evaluation Data Leverage: Advances like "Deep Research" Highlight a Looming Opportunity for Bargaining Power
Mar 2025 — Data Leverage Substack
Tipping Points for Content Ecosystems
Feb 2025 — Data Leverage Substack
AI Labs Should Open Source Data Protection Technologies
Jan 2025 — Data Leverage Substack
Live by the free-content-for-training sword, die by the free-content-for-training sword
Jan 2025 — Data Leverage Substack
Selling AGI like AG1: Will Consumers Push Back Against Proprietary Blends of Herbs and of Data?
Dec 2024 — Data Leverage Substack
Perplexity CEO's Interaction with Striking New York Times Workers Does Not Reflect Well on the AI Industry
Nov 2024 — Data Leverage Substack
Is Zuckerberg right to say that your specific creative work has no value to AI?
Sep 2024 — Data Leverage Substack
"Many Models" and "Track Changes" for AI: Some Thoughts on LLM Interfaces
Aug 2024 — Data Leverage Substack
Where Biden’s AI policies fall short in protecting workers
Feb 2024 — The Bulletin of the Atomic Scientists
Project Spotlight: CollectiveVoice
Feb 2024 — Metagov News
Building a Data Pipeworks for Democratic AI: From Human Knowledge to Records to AI Systems
Nov 2023 — Data Leverage Substack
How creatives can stop AI from stealing their work
Oct 2023 — The Bulletin of the Atomic Scientists
Will the New York Times Data Strike Have a Large Impact on ChatGPT?
Sep 2023 — Data Leverage Substack
A Harbinger of the Future of Content? The New York Times Starts a Data Strike
Aug 2023 — Data Leverage Substack
A roadmap toward empowering the labor force behind AI
Jul 2023 — Montreal AI Ethics Institute Research Summaries
The WGA Strike is a Canary in the Coal Mine for AI Labor Concerns
May 2023 — Data Leverage Substack
Reddit, StackOverflow, and Europe: All Trending Towards Data Dignity
May 2023 — Data Leverage Substack
Data Leverage Recap: December 2022 - April 2023
Apr 2023 — Data Leverage Substack
Bing Rewards for the AI Age
Mar 2023 — Data Leverage Substack
Plural AI Data Alignment
Mar 2023 — Data Leverage Substack
AI Technologies are System Maps, and You are a Cartographer
Feb 2023 — Data Leverage Substack
ChatGPT Stole Your Work. So What Are You Going to Do?
Jan 2023 — Wired
AI Artist or AI Art Thief? Innovation, Public Mandates, and the Case for Talking in Terms of Leverage
Dec 2022 — Data Leverage Substack
ChatGPT is Awesome and Scary: You Deserve Credit for the Good Parts (and Might Help Fix the Bad Parts)
Dec 2022 — Data Leverage Substack
The Paradox of Reuse, Language Models Edition
Dec 2022 — Data Leverage Substack
Apple Now Lets You Opt-Out of Tracking: Will This Give You More Influence Over Tech Companies?
Jul 2021 — Technically Social
GitHub Copilot and the Exploitation of "Data Labor": A Wake-Up Call for the Tech Industry
Jul 2021 — PSA Computing Blog
Apple's New Tracking Settings: A 'Data Strike by Default'?
May 2021 — PSA Computing Blog
Powerful Technologies and Their Power Laws: Estimating Machine Learning Systems' Data Leverage Vulnerabilities
Apr 2021 — Observable Notebook
Why You're an Expert "Language Model Trainer"!
Mar 2021 — PSA Computing Blog
What if we could check Big Tech?: The collective voice of millions of users could be as effective as regulation
Mar 2021 — Northwestern Now
Don’t give OpenAI all the credit for GPT-3: You might have helped create the latest “astonishing” advance in AI too
Sep 2020 — Data Leverage Substack
Don't give OpenAI all the credit for GPT-3: You might have helped create the latest 'astonishing' advance in AI too
Sep 2020 — PSA Computing Blog
"Data Strikes": A New Form of Leverage for Tech Users?
Sep 2020 — Data Dividend Project Blog
Talks & Conversations
Towards a 'Fully Attested' AI Supply Chain: Developments in AI Evaluation and Implications for a More Human-Centered Data Ecosystem
Sep 2026 — Pepperdine University, Malibu, CA (Talk)
Panelist, Responsible AI Track
May 2026 — Simon Fraser University, Burnaby, BC (Panel)
Panel: Designing Collective Technology Governance
May 2026 — Grande Halle, Brussels, Belgium (Panel)
Panel: Can Decentralists Cooperate? Rethinking Commons and Collective Action in the Age of Platforms and AI
Mar 2026 — AMS Student Nest, University of British Columbia, Vancouver, BC (Panel)
Collective action strategies in the age of AI w/ Nick Vincent from Data Leverage
Mar 2026 — The Blockchain Socialist (Podcast)
Collective Bargaining in the Information Economy Can Address AI-Driven Power Concentration
Dec 2025 — San Diego, CA (Poster Presentation)
A Data Flow Perspective on "AI Social Simulation": Will Recent AI Advances Enable New Social Science, Destroy Ecosystems for Knowledge, or Something More Subdued?
Nov 2025 — Simon Fraser University, Burnaby, BC (Talk)
A Data Flow Perspective on "AI Social Simulation": Will Recent AI Advances Enable New Social Science, Destroy Ecosystems for Knowledge, or Something More Subdued?
Oct 2025 — Seattle, WA (Talk)
Data Leverage and AI Safety
Aug 2025 — Singapore AI Safety Hub (Talk)
Data and Public AI
Jul 2025 — San Jose, CA (Talk)
AI as a Public Good with Jake Hirsch-Allen and Nicholas Vincent
Jun 2025 — BrainTrainr Podcast (Podcast)
Canada as Champion for Public AI
Mar 2025 — McMaster Digital Society Lab (Talk)
Emerging Concerns with the Generative AI Data Paradigm (and how academic research and “Public AI” can help)
Mar 2025 — UBC NLP (Talk)
Human-Centered AI Research and New Paradigms for Generative AI Data
Sep 2024 — Human-Centered AI Conference @ Pepperdine University (Talk)
Economic Concentration and Dispossessive Data Use: Can HCI Solve Challenges from and to AI?
May 2024 — Honolulu, HI (Talk)
A New Grand Data Bargain for Public Interest AI
Feb 2024 — SFU DDI (Talk)
Responsive LLM Development
Jan 2024 — University of Toronto Data Sciences Institute: Fairness - ChatGPT Workshop (Panel)
Can We Solve Emerging Problems in Technology and AI By Giving Communities Data Leverage?
Mar 2023 — (Talk)
Human-centered data and language models -- Privacy, data as labor, and licensing
Feb 2023 — Stanford Social NLP Reading Group Talks (Talk)
Algorithmic Contestability
Jan 2023 — Center for Advancing Safety of Machine Intelligence, Toward a Safety Science of AI (Talk)
Does the rise of AI need us to adopt new data licensing policies?
Dec 2022 — Open Health Data and AI Summit 2022 (Panel)
Should Tech Companies Be Paying Us for Our Data?
Nov 2021 — Things Have Changed Podcast (Podcast)
The Importance of Wikipedia to Search Engines and Other Systems
May 2021 — Wikimedia Research Showcase (Talk)
Public interest technologies for the ML age
May 2021 — 3rd Obfuscation Workshop (Talk)
On Data Dividends
May 2021 — RadicalxChange Podcast (Podcast)
Data Agency: Individual or Shared?
Jan 2021 — RadicalxChange Panels (Panel)
Data Driven Economy for All
Jun 2020 — RadicalxChange 2020 Conference (Panel)
The Critical Relationship of Volunteer-Created Wikipedia Content to Large-Scale Online Communities
Apr 2018 — Wikimedia Research Showcase (Talk)
Media Coverage
Pepperdine Hosts Two-Day Human-Centered AI Conference
Pepperdine Graphic · Marcos Lizarraga · Sep 2026
New Research Challenges Tech Giants to Recognize Users as Laborers, Not Byproducts
Carnegie Mellon University Tepper School of Business · John Miller · Feb 2026
Should the public sector build its own AI?
Financial Times · Gideon Lichfield · Sep 2025
AI as 'teammate'? Not so fast, say experts warning it could be 'dangerous'
Canadian HR Reporter · Stacy Thomas · Jul 2025
Can Wikipedia survive the rise of AI and the age of Donald Trump?
Australian Broadcasting Corporation · Rhiannon Stevens · May 2025
‘Trial and error’: Over half of AI redundancies a mistake, say leaders
Canadian HR Reporter · Stacy Thomas · May 2025
Inside Meta's secret experiments that improve its AI models
Business Insider · Alistair Barr, Pranav Dixit · Apr 2025
OpenAI is reaping what it sowed with DeepSeek. What's that old saying about karma?
Business Insider · Alistair Barr · Jan 2025
Is data supply AI’s Achilles’ heel?
UBS · Richard Mylles · Jun 2024
Is this AI? See if you can spot the technology in your everyday life
The Washington Post · Kevin Schaul · Apr 2024
Jews have always been prolific writers. Has AI wound up with too much of their work?
Jewish Telegraphic Agency · Asaf Elia-Shalev · Mar 2024
Nicholas Vincent explains why robots.txt is no longer enough to protect against web scraping
IT Brew · Tom McKay · Mar 2024
AI is killing the grand bargain at the heart of the web. 'We're in a different world.'
Business Insider · Alistair Barr, Kali Hays · Jan 2024
Newspapers want payment for articles used to power ChatGPT
The Washington Post · Nitasha Tiku · Oct 2023
'Data leverage' and the Harry Potter test: How much is a single book worth to a giant AI model?
Business Insider · Alistair Barr · Aug 2023
Wikipedia’s Moment of Truth
New York Times Magazine · Jon Gertner · Jul 2023
We are all AI’s free data workers
MIT Technology Review · Melissa Heikkilä · Jun 2023
Internet users are 'poisoning' their personal data in the fight against online surveillance
Le Monde · Aurélien Defer · Apr 2022
Got the same name as a serial killer? Google might think you’re the same person
Vox · Rebecca Heilweil · Jun 2021
Facebook and Others Should Pay Us for Our Data. Here’s One Way
Bloomberg · Peter Coy · May 2021
How to poison the data that Big Tech uses to surveil you
MIT Technology Review · Karen Hao · Mar 2021
Your data is a weapon that can help change corporate behavior
Fortune · Jonathan Vanian, Jeremy Kahn · Feb 2021
Is it time for Netflix subscribers to go on strike?
Quartz · Nicolás Rivero · Jul 2020
YouTube May Add to the Burdens of Humble Wikipedia
New York Times · John Herrman · Mar 2018
Web Projects
DataLicenses.org
LiveA community-curated catalog of initiatives shaping AI data access, licensing, controlled retrieval, and enforcement.
VisitSep 2025Interactive memos, toy grids, and related-work maps for reasoning about what changes when training, evaluation, or governance data worlds change.
VisitMar 2026Data Napkin Math
LiveA beta interactive page for exploring back-of-the-envelope estimates about training data value and the distribution of AI proceeds and benefits.
VisitJan 2024Data Lava Lamp
LiveAn interactive AI-literacy installation that turns fragments of open training and post-training datasets into drifting streams of text.
VisitJul 2026
Workshops & Meetings
Workshops, conferences, and recurring meetings I have organized, facilitated, or supported.
PoliSim@CHI 2026: LLM Agent Simulation for Policy
Apr 2026 · ACM CHI 2026 · Organizer
Co-organized the PoliSim workshop at ACM CHI 2026.
Workshop on Algorithmic Collective Action @ NeurIPS 2025
Dec 2025 · NeurIPS 2025 · Organizer
Activism in the Age of AI
Mar 2025 · IATSE 891 AI Day of Learning · Session Facilitator / Panelist
Facilitated an interactive session on activism in the age of AI and participated in the afternoon panel.
Workshop on Creativity & Generative AI @ NeurIPS 2024
Dec 2024 · NeurIPS 2024 · Advisor / Panel Host
Advised the workshop and hosted a panel connecting machine learning researchers and creative professionals.
ICWSM 2024 Data Challenge
Jun 2024 · Co-chair
Co-chaired the Data Challenge track at ICWSM 2024 (Buffalo, June 3, 2024) with Onur Varol and Ronald Robertson.
Can Licensing Mitigate the Negative Implications of Commercial Web Scraping?
Oct 2023 · ACM CSCW 2023 · Co-organizer
Epistemic Injustice in Online Communities: Unpacking the Values of Knowledge Creation and Curation within CSCW Applications
Oct 2023 · ACM CSCW 2023 · Co-organizer
AI Palace Conference/Residency
2023–2024 · Organizer
Organized the AI Palace conference/residency in Bückeburg, Germany, in summer 2023 and summer 2024.
Ethical Tensions, Norms, and Directions in the Extraction of Online Volunteer Work
Nov 2022 · ACM CSCW 2022 · Co-organizer
California Data Dividends Working Group
2019–2022 · Organizer
Northwestern University Artificial Intelligence Journal Club
2019–2021 · Organizer
Organized the Northwestern University Artificial Intelligence Journal Club.
InfoSocial Graduate Student Conference
Jan 2018 · Co-chair
Served as one of two co-chairs for the InfoSocial graduate student conference.
What this site is for
This site is a searchable companion to my CV: a list of papers, talks, writing, workshops, meetings, and other research artifacts, with filters and the links attached to each project. Like some other academics, I occasionally use my own static site to find a paper link before sending it to someone. I also group the work into 9 research topics, though they are really different angles on data leverage.