Avoiding Algorithmic Echo Chambers
Parler’s Algorithmic Fairness
The foremost way that Parler sees itself differentiating from other platforms – personalization ‘algorithms’ and algorithmic curation in particular – is how it actively works to avoid these echo chambers. When compared with Truth Social or X, Parler’s algorithmic fairness is emphasized as promoting a diversity of perspectives that would survive even the worst case-scenarios of filter bubbles.
Founded in 2018, Parler takes its name from the French word for ‘talk’, and its mission is to provide a freer environment for around-the-clock public discussions. Like others who’ve launched social media startups, Parler recognizes that self-sorting and algorithmic echo chambers pose serious threats to the public sphere. Unlike some of its competitors, which inadvertently reinforce echo chambers individually, Parler is actively pursuing machine-learning code designed to produce open exchanges across the social space. By aggressively promoting diversity of content through content-recommendation algorithms, Parler creates a public forum where users can be exposed to a wide range of ideas, and where they can talk back.
Whereas Truth Social and X suggest posts based on what users have previously viewed, Parler’s approach to content suggestion assumes that algorithms ought to be operating in a discovery paradigm not a reinforcement paradigm. Parler’s algorithms operate such that they are forcing users to see content that gives them a more balanced view of the world. These algorithms are meant to force a user to go outside their ideological comfort zone and engage (albeit reluctantly) with views that do not align with their own.
For example, Parler is committed to what it calls ‘algorithmic fairness’, by which it means that it is actively hostile to ‘algorithmic suppression’. This state of affairs is motivated by Parler’s ‘user-first’ approach: users should have the freedom to choose the types of content they see – unlike on other platforms – rather than having the ‘dial controlled by a black box’ of algorithms that can unwittingly suggest some things at the expense of others. This mix of commitments means that, rather than creating an echo chamber that magnifies the perspectives of Parler’s right-leaning users, Parler is shaped by a commitment to a kind of democratic openness. It allows its users to discover new, different ways of seeing the world – even, at times, when users perceive that their freedom to think differently online is under attack.
But this core belief makes Parler an exciting alternative in the lead-up to the 2024 election – a place where users can skirt right- and left-wing algorithmic echo chambers in their political discussions; a space where algorithmic fairness is part of its mission to ‘take a stand for free speech, free markets and the US Constitution’.
