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Documented Cases of Algorithmic Collective Action

This is an ongoing list of algorithmic collective action cases. We encourage you to contribute to it by creating a markdown file with the case and opening a pull request.

For more background and related work see Sigg et al. (2024).

Note that some of the strategies described here no longer work, e.g. due to changes in the algorithm. For many strategies it is unclear how successful and effective they are or were or how many people participated. Lastly, some strategies described here are more like prototypes or proof-of-concepts, but they nevertheless provide value by their ideas.

We group the cases by the mechanism they apply as a lever. This can be:

  • Collective information sharing
    Digital platforms are often characterized by a high degree of information asymmetry between platform participants and platform owners. Workers have started to engage in information sharing strategies of different kind to counter this information balance. Examples include building up knowledge how the algorithm works, exchanging individual strategies to make them available to a larger group of users, or aggregating data as part of a data cooperative.

  • Collective strategizing
    This refers to cases where people agree upon and execute a joint strategy which often requires coordination as it might happen at a dedicated time or place. This can be viewed as a collective strategy during deployment time as it leverages certain aspects of the algorithm when deployed.
    Moreover, the reliance of machine learning powered platforms on human-generated data during training time offers an additional lever for workers to exploit, e.g. by manipulating, poisoning or withholding training data.

case ↓ short case description participants area category benefit for participants coordination aspects (if known)
Amazon Mechanical Turk – TurkerView & Co. collecting/averaging ratings on requester, sharing individual strategies on how to accomplish tasks workers gig economy collective information sharing more accurate information about tasks and requesters forum, websites
Uber Surge Verification Groups drivers notify each other to verify accuracy and profitability of surge areas workers gig economy collective information sharing information can save each other time and money messenger
John Deere Tractorhacking collective effort to hack and share tractor software tractor-owner, software-hacker, mechanics collective information sharing reduced costs open source code platforms, e.g. GitHub
Truck Drivers Facing Surveillance electronic logging devices: brute-force destruction, exchanging of individual strategies, sharing log-in information, slow rolls, collaboration between drivers and truck stops mainly workers collective information sharing , collective strategizing evading surveillance
Instagram Joint Sensemaking influencers collectively decipher the logics of the algorithm by reporting which experiments worked out content-providers social media collective information sharing better/faster knowledge about the Instagram algorithm messenger
Upwork Joint Sensemaking upwork freelancers using forums etc. to jointly making sense of the algorithms logic on e.g. account-visibility, customer ratings etc. workers gig economy collective information sharing better/faster knowledge about algorithm forum
MozillaRally browser extension (no longer active) where participants could donate their data for web-based studies browser users collective information sharing different from study to study centrally organized, not user-driven
Food Delivery in China – WeChat groups drivers share information about individual strategies, trying to collectively unpack the platforms’ algorithm, messenger groups act as informal unions, sharing information on temporary subsidies, newcomer help etc. workers gig economy collective information sharing better/faster knowledge about algorithm, individual strategies messenger invites via QR-codes on drivers' bags
Workers Info Exchange – Pooling Data provide support for workers to make a data request from the gig platform, conducting research with that data workers gig economy collective information sharing expose unfair algorithmic decision making
Driver’s Seat Cooperative driver-owned data collection/analytics service, providing performance data for drivers, sell data to cities and transportation agencies workers gig economy collective information sharing performance data insights app
WeClock self-tracking app for workers, quantifying the workday; also addressing unions to support their campaigns workers gig economy collective information sharing performance data insights app
Postmates BlitzUp one-day protest as reaction to change in pricing policy; only accepting "Blitz" offers (higher paying orders) workers gig economy collective strategizing protesting and still earning money campaign website with registration + action plan
Amazon Flex Treephones drivers placing phones in trees + syncing them with their phones, gives advantage over location-dependent offers workers gig economy collective strategizing getting offers before others do without the need to be physically close to the store potentially onsite
Uber Surge Club collective log-out to trigger supply- and demand-based surge pricing, logging back after a few minutes yields higher pay workers gig economy collective strategizing getting higher payment for a ride messenger
Youtube – Fix Community Poll Feature campaign to extensively use community polls (which apparently reached users beyond measure) in order to 'fix the broken feature' content-providers social media collective strategizing getting fair conditions for everybody video
Spotify – 31 Seconds of Silence the band 'Vulfpeck' made money by asking their fans to listen to songs that consist of 31 seconds of silence during nighttime users collective strategizing band gets money, fans get concerts financed by that money
Spotify – Song Ranking singer 'Anitta' pushed her song to the first place on Spotify charts by asking her fans to listen to it repeatedly, create playlists and use multiple accounts users collective strategizing fans could win a spotify subscription, singer gets fame + money
DoorDash – #DeclineNow drivers reject low-paying orders, hypothesizing that the algorithm will increase pay on that order for fellow driver workers gig economy collective strategizing increased income facebook groups
FoggySight – Facial Recognition Privacy enhancing user privacy in facial lookup settings by producing ambiguous images to obfuscate another user’s identity users (e.g. of social media) social media collective strategizing protecting (other) users' identities
Instacart – 22 cent Tips tipping 22 cent upfront as a signal that more tips will be paid later workers, consumers/clients gig economy collective strategizing workers: more money, consumers: tipping the driver (not Instacart)" campaign website, flyers
Instacart – #DeleteInstacart workers asked customers to delete the app workers, consumers/clients gig economy collective strategizing unclear hashtag, open letter
Food Delivery in China – Restaurant-Driver Cooperation drivers cooperating with restaurants, placing artificial orders to meet bonus pay requirements workers, restaurants gig economy collective strategizing using the bonus-feature of the app to make more money workers: money, restaurants: unclear, probably visibility
Instagram Engagement Pods peer community to mutually engage with each others content content-providers social media collective strategizing improve their ranking or account visibility
Instagram Loop Giveaways multiple accounts collaborate to offer a gift for their followers, requiring participants to follow all collaborating accounts content-providers social media collective strategizing increase followers, improve ranking or account visibility private messenger groups
Upwork – Evaluation Metrics workers are asking clients to give them specific ratings to enhance their scores workers, clients gig economy collective strategizing better job score
Upwork – Off-Platform Work workers use the platform for matching with customers, then suggest to continue off-platform to earn more workers, clients Gig Economy collective strategizing private messages
Twitter – Screenshotting posting screenshots of other posts to avoid a forced connection content-providers social media collective strategizing not getting unwanted attention, avoiding forced connection common knowledge, hints and comments about the strategy on Twitter itself
Twitter – Voldemorting not mentioning words or names in a post (instead inventing new names) in order to avoid a forced connection content-providers (+ content-consumers) social media collective strategizing not getting attention, avoiding forced connection
Facebook – Remote Geotagging collective remote check-in to obfuscate geolocation data allegedly monitored by police Facebook users social media collective strategizing hide the true location data
Google Bombs heavy linking of search terms and websites to rank them higher users collective strategizing push the website's ranking
Waze – Traffic Routing pseudo-collective: individuals creating bots to influence crowd-sourced navigation systems pseudo-collective data poisoning
Fan Fiction Writers – Irreverent Stories fan fiction writers produce fake stories to poison data collection services workers collective strategizing
AdNauseam browser extension to obfuscate browsing and ad data aiming at protecting own privacy, protecting other users' privacy as a side effect browser users data poisoning/obfuscation hide true user profiles
Impact app prototype app to organize supporters to promote political messages on social media social media users social media collective strategizing steer attention on social media app

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