A new book by Kyle Chayka titled "Filterworld" examines the profound influence of algorithmic recommendations on user experiences in the constantly changing social media platform landscape.
He examines how algorithms on Facebook, Twitter, and Instagram have filtered post views from chronological to curated. He argues these algorithms shape consumers' music, news, diet, and other interests, per NPR.
According to the author, the omnipresence of algorithmic curation has turned users into passive recipients, "flattening" their tastes. This influence is not limited to users alone; content creators, especially in fields like music, feel compelled to tailor their work to align with algorithms. For musicians on platforms such as Spotify or TikTok, crafting attention-grabbing hooks at the start of a song becomes crucial to maximizing user engagement.
(Photo : Chris McGrath/Getty Images)
In this photo illustration, social media apps are seen on a mobile phone on July 29, 2020 in Istanbul, Turkey.
Despite the overwhelming presence of algorithms, Chayka suggests that increased regulation of social media companies could help mitigate their impact. One proposal involves the potential spin-off of platforms like Instagram or WhatsApp from Meta, Facebook's parent company, fostering a more competitive landscape that empowers users with diverse choices.
Algorithm is King
Reflecting on the dynamics of the internet, the author notes that while it allows widespread publication, creators are subject to the influence of algorithmic ecosystems. Digital engagement metrics frequently replace traditional gatekeepers like magazine editors or record executives as a measure of success in this era.
Moreover, Kyle Chayka, a staff writer for The New Yorker, raises concerns about the lack of visibility into others' algorithms, creating a sense of isolation within a seemingly communal digital experience. Users cannot gauge what others are exposed to, hindering the formation of shared cultural experiences.
The technology writer also points out how algorithms encourage passive consumption, limiting critical engagement with culture. He fears that the pursuit of easily digestible content might lead to neglecting challenging masterpieces that don't immediately captivate audiences.
Chayka's investigation raises concerns about the delicate balance between convenience and depth in cultural consumption in a world where algorithmic curation dominates. He said that he worries about the "passivity of consumption that we've been pushed into, the ways that we're encouraged not to think about the culture we're consuming, to not go deeper and not follow our own inclinations."
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Meanwhile, a Harvard Business Review article noted that algorithms face limitations stemming from a crucial constraint: their reliance on users' behavior, predominantly clicks, views, and purchases. It stated that the utilization of "revealed preferences" as the basis for learning is considered incomplete and occasionally misleading, falling short of accurately understanding users' genuine goals and values.
This discrepancy between revealed preferences and "normative preferences" poses challenges, impeding algorithms from fulfilling their commitment to enriching lives across various domains, including social media curation, healthcare allocation, and insurance pricing.
Government Looking Into Harmful Impacts
Researchers have long voiced concerns about the algorithms governing prominent social media platforms like Facebook and Instagram and shaping content visibility on user feeds.
In 2021, former Facebook employee Frances Haugen, acting as a whistleblower, brought further attention to these algorithms. Haugen shared internal documents with lawmakers and the media, testifying in Congress that Facebook's algorithm was exposing teenagers to increased anorexia content and fueling ethnic violence, particularly in regions like Ethiopia.
In response to these revelations, lawmakers, including Senators Amy Klobuchar (D-Minnesota) and Cynthia Lummis (R-Wyoming), introduced bills aimed at studying or imposing restrictions on these algorithms. However, as of now, none of these legislative initiatives have successfully progressed into law, per The New York Times.
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