A working notebook on Algorithmic Collective Action (ACA) and Protective Optimization Technologies (POTs) — tracing how communities can push back on data-driven systems, and sharing updates from our research.
This blog explores Algorithmic Collective Action (ACA) and Protective Optimization Technologies (POTs) — sharing updates from our research, drawing on Hardt et al. (2023), Kulynych et al. (2018), and Vincent et al. (2020).
We've heard over and over how we're living in a data-driven world and how algorithms are part of our everyday lives. What does that actually mean? Whenever we interact with algorithmic systems — a search engine, a social platform, a recommendation feed — we aren't just passive users. We're actively contributing data that these algorithms use to learn and adapt.
But living with algorithms doesn't have to be a one-way street. Because users contribute data to the system, that contribution can itself be a form of leverage. That's where the work of Vincent et al. (2020) gets interesting.
"By reducing, stopping, redirecting, or otherwise manipulating data contributions, the public can reduce the effectiveness of many lucrative technologies." — Vincent et al. (2020)
This idea explores how individuals and groups can use their data contributions strategically — not just passively — to shape the behavior and incentives of data-driven systems.
"The collective pools the data of participating individuals and executes an algorithmic strategy by instructing participants how to modify their own data to achieve a collective goal." — Hardt et al. (2023)
ACA emphasizes coordination and strategy among groups of individuals to influence the behavior of learning algorithms — especially those deployed by large-scale platforms.
"POTs provide means for affected parties to address the negative impacts of systems in the environment, expanding avenues for political contestation." — Kulynych et al. (2018)
POTs are techniques designed to mitigate or adapt to unintended consequences of optimization systems. They operate externally and do not require changes to the systems themselves.
Some portions of this blog were edited using AI writing tools (ChatGPT-4, Grammarly, Quillbot) to improve flow, grammar, clarity, and structure. All content has been carefully reviewed and manually validated for accuracy, alignment with the cited sources, and consistency with the research context.