Threads, Meta’s social media platform, is testing a feature called “Dear algo” that enables users to directly request changes to their recommendation algorithm by posting specific messages. Announced by Conor Hayes on December 3, the AI-driven tool aims to personalize feeds through user-initiated adjustments lasting up to three days.
The “Dear algo” feature operates by allowing users to create posts prefixed with “dear algo” followed by their preferences for content visibility. This mechanism provides a straightforward interface for influencing the algorithm’s recommendations without navigating complex settings. Users can specify desires for increased exposure to particular topics or reduced visibility of others, thereby tailoring their experience on the platform.
Examples of such requests illustrate the feature’s flexibility. One possible post reads, “Dear algo, show me more book recommendations,” directing the system to prioritize literary suggestions in the user’s feed. Another example is, “Dear algo, stop showing me basketball updates my team is bad and it makes me sad,” which instructs the algorithm to limit sports-related content to avoid negative emotional triggers. A further instance mentioned in coverage is, “Dear algo, show me more Mashable content,” highlighting how users might seek additional material from specific sources like the tech and culture publication.
Conor Hayes, who serves as the head of Threads, detailed the initiative in a post on the platform dated December 3. He stated that Threads is “testing a new AI feature to help you personalize your feed.” This announcement underscores the platform’s commitment to enhancing user control over content curation through artificial intelligence.
Upon posting a “Dear Algo” message, the user’s feed undergoes a temporary modification, incorporating the requested adjustments for a period of up to three days. This duration ensures short-term personalization without permanent alterations to the overall algorithm. Hayes explained that the change facilitates greater engagement with preferred content, as users interact more with aligned material, which in turn contributes to the algorithm’s refinement over extended periods.
Visibility of these posts depends on the user’s profile settings. For public profiles, the requests become accessible to others on the platform. This openness allows individuals to view the messages, initiate connections with the poster regarding shared interests, or repost the content to amplify its reach. Consequently, friends and followers gain insight into the poster’s content preferences, fostering potential discussions or community interactions around algorithmic choices.
Hayes emphasized the experimental nature of the rollout in his post, noting, “This is just a test, so not everyone will have access now, but we’re working on rolling it out more broadly soon.” This phased approach indicates Threads’ strategy to gather feedback and iterate on the feature before wider implementation.
The concept for “Dear algo” originated from organic user behavior on Threads. Mark Zuckerberg, head of Meta, attributed the inspiration to early adopters who began submitting informal requests phrased as “dear threads algo.” He wrote that the new feature was “inspired” by people on the app “who started ‘dear threads algo’ requests.” This user-driven evolution reflects how platform innovations can emerge from community practices.
The development aligns with broader efforts in social media to empower users in shaping their digital environments. Threads, as part of Meta’s ecosystem, continues to explore AI integrations for improved personalization. The feature’s public aspect also introduces social dimensions to algorithmic tweaks, potentially influencing how users express and share their online preferences.
This article draws from reporting by Christianna Silva, a senior culture reporter at Mashable. Silva covers social platforms and the creator economy, focusing on the intersections of social media, politics, and economic systems. Since joining Mashable in 2021, she has reported on meme creators, content moderation, and online creation dynamics under capitalism. Prior roles include editing at NPR and MTV News, reporting at Teen Vogue and VICE News, and working as a stablehand at a mini-horse farm. She can be followed on Bluesky at @christiannaj.bsky.social and on Instagram at @christianna_j.
