Nicholas Vincent

Research in: Responsible Artificial Intelligence, Human-computer Interaction, Human-centered Machine Learning, and Social Computing


Assistant Professor in the School of Computing Science at Simon Fraser University.



9241 TASC 1, SFU Burnaby




Scholarly profiles

google scholar

semantic scholar





Hello! I'm Nick. In short, I use HCI and ML to study the ecosystems and supply chains that provide the data flow that makes AI work. Below, you can find a short bio and links to artifacts I've helped to produce.

Quick bio: Prof. Nick Vincent is a researcher in human-centered artificial intelligence. Much of his research focuses on understanding how data records -- including works that we produce and logs of our behavior -- provide value to AI systems such as search engines, recommender systems, and new "generative AI" systems, and how the benefits of data-dependent AI might flow back to the public. A key idea motivating his work is that because human activities are upstream of the data contributions that make AI work, organized groups can exert "data leverage" to bargain for larger shares of the profits of AI or for more voice in how AI systems are governed. The overarching goal of this research is to develop frameworks, build tools, and present empirical results that help work towards an ecosystem of highly capable and widely beneficial AI technologies that mitigate -- rather than exacerbate -- inequalities in wealth and power.
Additional background info: I was previously a postdoc working with the Computational Communication Research Lab at UC Davis and the Social Futures Lab at the University of Washington. I received my PhD from Northwestern University's Technology and Social Behavior program (a joint degree in computer science and communication), where I worked in the People, Space, and Algorithms Research Group. During graduate school, I was a research intern at Snap and Microsoft. Before graduate school, I studied electrical engineering at UCLA and interned at Cisco and SPAWAR via the NREIP program.
Recent news: | 2 CHI preprints on arxiv | Presented in Prof. Shilad Sen's Collective Intelligence course | Received a SIGCHI Outstanding Dissertation Award (coverage). | Spoke at the Digital Democracies Institute. | Panelist at University of Toronto Fairness - ChatGPT workshop put on by the Data Sciences Institute. |

Op-eds and invited writing

News Coverage

Selected Blog Posts


Peer-reviewed Publications

  • Heila Precel, Allison McDonald, Brent Hecht, Nicholas Vincent. 'A Canary in the AI Coal Mine: American Jews May Be Disproportionately Harmed by Intellectual Property Dispossession in Large Language Model Training'. ACM CHI 2024.

    | arxiv |
  • Leijie Wang, Nicholas Vincent, Julija Rukanskaitė, Amy X. Zhang. 'Pika: Empowering Non-Programmers to Author Executable Governance Policies in Online Communities'. ACM CHI 2024.

    | arxiv |
  • Leah Ajmani, Nicholas Vincent, Stevie Chancellor. 'Peer Produced Friction: How Page Protection on Wikipedia Affects Editor Engagement and Concentration'. ACM CSCW 2023.

  • Hanlin Li, Nicholas Vincent, Stevie Chancellor, Brent Hecht. 'The Dimensions of Data Labor: A Road Map for Researchers, Activists, and Policymakers to Empower Data Producers'. ACM FAccT 2023.

  • Danish Contractor, Daniel McDuff, Julia Katherine Haines, Jenny Lee, Christopher Hines, Brent Hecht, Nicholas Vincent, Hanlin Li". 'Behavioral Use Licensing for Responsible AI'. ACM FAccT 2022.

  • Farhan Asif Chowdhury, Yozen Liu, Koustuv Saha, Nicholas Vincent, Leonardo Neves, Neil Shah, Maarten W Bos". 'CEAM: The Effectiveness of Cyclic and Ephemeral Attention Models of User Behavior on Social Platforms'. AAAI ICWSM 2021.

    | pdf |
  • Jack Bandy, Nicholas Vincent. 'Addressing "Documentation Debt" in Machine Learning Research: A Retrospective Datasheet for BookCorpus'. NeurIPS 2021 Datasets and Benchmarks Track.

  • Koustuv Saha, Yozen Liu, Nicholas Vincent, Farhan Asif Chowdhury, Leonardo Neves, Neil Shah, Maarten W Bos. 'AdverTiming Matters: Examining User Ad Consumption for Effective Ad Allocations on Social Media'. ACM CHI 2021.

    | pdf |
  • Nicholas Vincent, Brent Hecht. 'A Deeper Investigation of the Importance of Wikipedia Links to Search Engine Results'. ACM CSCW 2021.

  • Nicholas Vincent, Brent Hecht. 'Can "Conscious Data Contribution" Help Users to Exert "Data Leverage" Against Technology Companies?'. ACM CSCW 2021.

    | pdf | code |
  • Nicholas Vincent, Hanlin Li, Nicole Tilly, Stevie Chancellor, Brent Hecht. 'Data Leverage: A Framework for Empowering the Public in its Relationship with Technology Companies'. ACM FAccT 2021.

    | pdf | arxiv |
  • Hanlin Li, Nicholas Vincent, Janice Tsai, Jofish Kaye, Brent Hecht. 'How Do People Change Their Technology Use in Protest?: Understanding “Protest Users”'. ACM CSCW 2019.

    | pdf |
  • Nicholas Vincent, Isaac Johnson, Patrick Sheehan, Brent Hecht. 'Measuring the Importance of User-Generated Content to Search Engines '. AAAI ICWSM 2019.

    | pdf | code |
  • Nicholas Vincent, Brent Hecht, Shilad Sen. '“Data Strikes”: Evaluating the Effectiveness of a New Form of Collective Action Against Technology Companies'. ACM The Web Conference 2019.

  • Eureka Foong, Nicholas Vincent, Brent Hecht, Elizabeth M Gerber. 'Women (still) ask for less: Gender differences in hourly rate in an online labor marketplace'. ACM CSCW 2018.

    | pdf |
  • Nicholas Vincent, Isaac Johnson, Brent Hecht. 'Examining Wikipedia With a Broader Lens: Quantifying the Value of Wikipedia's Relationships with Other Large-Scale Online Communities'. ACM CHI 2018.

    | pdf | code |

Workshop Papers

  • Clare Provenzano, Parsa Rajabi, Diana Cukierman, Nicholas Vincent. The Need for Flexible Interfaces for Text-to-Image Auditing: A Case Study of DALL·E 2 and DALL·E 3. .

  • Nicholas Vincent, David Bau, Sarah Schwettmann, Joshua Tan. An Alternative to Regulation: The Case for Public AI. RegML 2023 (NeurIPS 2023 Workshop).

    | arxiv |
  • Nicholas Vincent, Brent Hecht. Sharing the Winnings of AI with Data Dividends: Challenges with 'Meritocratic' Data Valuation. EAAMO 2023.

    | pdf |
  • Nicholas Vincent, Christine Vandevoorde. Collaborative Design of Contribution Tracking Systems for Decentralized Organizations. CESC 2022.

    | pdf |
  • Isaiah Jones, Brent Hecht, Nicholas Vincent. Misleading Tweets and Helpful Notes: Investigating Data Labor by Twitter Birdwatch Users. ACM CSCW 2022 Posters.

    | pdf |
  • Noah Stier, Nicholas Vincent, David Liebeskind, Fabien Scalzo". Deep learning of tissue fate features in acute ischemic stroke. BIBM 2015 Workshop on Biomedical Visual Search and Deep Learning.

    | ieee |
  • Nicholas Vincent, Noah Stier, Songlin Yu, David S Liebeskind, Danny JJ Wang, Fabien Scalzo". Detection of hyperperfusion on arterial spin labeling using deep learning. BIBM 2015 Workshop on Biomedical Visual Search and Deep Learning.

    | ieee |

Other Preprints

  • Rod Abhari, Nicholas Vincent, Henry K Dambanemuya, Herminio Bodon, Emőke-Ágnes Horvát". Twitter Engagement with Retracted Articles: Who, When, and How?

    | arxiv |
  • Yakov Feygin, Hanlin Li, Chirag Lala, Brent Hecht, Nicholas Vincent, Luisa Scarcella, Matthew Prewitt". A Data Dividend that Works: Steps Toward Building an Equitable Data Economy

  • Nicholas Vincent, Yichun Li, Renee Zha, Brent Hecht. Mapping the Potential and Pitfalls of 'Data Dividends' as a Means of Sharing the Profits of Artificial Intelligence.

    | arxiv |