# Data Leverage: A Framework for Empowering the Public in its Relationship with Technology Companies

arXiv: https://arxiv.org/abs/2012.09995 · HTML: https://mlsanity.com/paper/2012.09995/

## Key facts

- Cited by 26 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Dec 2020.

## Built on by (most cited first, 26 of 26)

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- [Algorithmic Collective Action in Recommender Systems: Promoting Songs by Reordering Playlists](https://mlsanity.com/paper/2404.04269/) (2024)
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- [Sociotechnical Implications of Generative Artificial Intelligence for Information Access](https://mlsanity.com/paper/2405.11612/) (2024)
- [Statistical Collusion by Collectives on Learning Platforms](https://mlsanity.com/paper/2502.04879/) (2025)
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- [Crowding Out The Noise: Algorithmic Collective Action Under Differential Privacy](https://mlsanity.com/paper/2505.05707/) (2025)
- [FATE in AI: Towards Algorithmic Inclusivity and Accessibility](https://mlsanity.com/paper/2301.01590/) (2023)
- [Towards Data Governance of Frontier AI Models](https://mlsanity.com/paper/2412.03824/) (2024)
- [Data Defenses Against Large Language Models](https://mlsanity.com/paper/2410.13138/) (2024)
- [Look-Ahead Reasoning on Learning Platforms](https://mlsanity.com/paper/2511.14745/) (2025)
- [Addressing Privacy Threats from Machine Learning](https://mlsanity.com/paper/2111.04439/) (2021)
- [FairFare: A Tool for Crowdsourcing Rideshare Data to Empower Labor Organizers](https://mlsanity.com/paper/2502.11273/) (2025)
- [Collective Obfuscation and Crowdsourcing](https://mlsanity.com/paper/2208.06405/) (2022)
- [Promoting User Data Autonomy During the Dissolution of a Monopolistic Firm](https://mlsanity.com/paper/2411.13546/) (2024)
- [Data Enrichment Work and AI Labor in Latin America and the Caribbean](https://mlsanity.com/paper/2501.06981/) (2025)
- [Conscious Data Contribution via Community-Driven Chain-of-Thought Distillation](https://mlsanity.com/paper/2512.18174/) (2025)
- [How Professional Visual Artists are Negotiating Generative AI in the Workplace](https://mlsanity.com/paper/2603.04537/) (2026)
- [A Statistical Framework for Algorithmic Collective Action with Multiple Collectives](https://mlsanity.com/paper/2605.06749/) (2026)
- [Test-Time Collective Action: Proxy-Based Perturbations for Correcting Algorithmic Harms](https://mlsanity.com/paper/2605.27689/) (2026)
- [Modeling Deletion Requests in Machine Unlearning](https://mlsanity.com/paper/2610.04310/) (2026)

## Abstract (arXiv)

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 relationship with technology companies: by reducing, stopping, redirecting, or otherwise manipulating data contributions, the public can reduce the effectiveness of many lucrative technologies. In this paper, we synthesize emerging research that seeks to better understand and help people action this textitdata leverage. Drawing on prior work in areas including machine learning, human-computer interaction, and fairness and accountability in computing, we present a framework for understanding data leverage that highlights new opportunities to change technology company behavior related to privacy, economic inequality, content moderation and other areas of societal concern. Our framework also points towards ways that policymakers can bolster data leverage as a means of changing the balance of power between the public and tech companies.