Random Acts of Architecture

Wisdom for the IT professional, focusing on chaos that is IT systems and architecture.

Twitter will never outsource its algorithm

Elon Musk sparked controversy with this recent attempt to take over Twitter. Many support him, citing Twitter’s relatively poor revenue and Musk’s success in turning seemingly unprofitable ventures, like electric vehicles and space exploration, into successes.

However, his recent Twitter poll caught my interest, where 82% of over one million responses voted that Twitter should open source its algorithm.

Musk explained further during interviews at the TED 2022 conference. The “Twitter algorithm” refers to how tweets are selected then ranked for different people. While some human intervention occurs, social networks like Twitter replace a human editorial team’s accountable moderation with automation. Humans cannot practicality and economically manage and rank the estimated 500 million tweets sent per day.

By “open source”, Musk means “the code should be on Github so people can look through it”. Hosting software code on github.com is common practice for software products. Third parties can examine the code to ensure it does what it claims to. Some open sourced products also allow contributions from others, leveraging the community’s expertise to collectively build better products.

Musk says “having a public platform that is maximally trusted and broadly inclusive is extremely important to the future of civilization.” People frequently demonize social networks for heavy-handed or lax “censorship”, depending on their side in a debate. Pundits claim social networks limit “free speech”, conveniently forgetting “free speech” means no government intervention. Pundits cite examples of the algorithm prioritizing or deprioritizing tweets, authors or topics. They also cite account suspensions and cancellations, sometimes manual and sometimes automated.

Musk assumes that explaining this algorithm will increase trust in Twitter. He called Twitter “a public platform”, implying not just public access but collective ownership and responsibility. If people understand how tweets are included and prioritized, the focus can move from social networks to the conversations they host.

Unfortunately, understanding and trust are two different things. Well understood and transparent processes, like democracies’ elections or justice systems, are not universally trusted. No matter the intentions or execution of a system, some people will accuse it of bias. These accusations may be made in ignorant but good faith, observe real but rare failures or be malicious and subversive.

Twitter’s algorithm is not designed to give equal exposure to conflicting perspectives. It is designed primarily to maximize engagement and, therefore, revenue. It is not designed to be “fair”. Social networks are multibillion dollar companies that can profit from the increased exposure controversy brings. Politicians alienate few and resonate with many when they point the finger of blame at Twitter.

Designing an algorithm for fairness is practically impossible. You can test for statistical bias in a numeric sample set but not across the near entirety of human expression. Like the philosophers opposing the activation of Deep Thought in Douglas Adams’ Hitch Hiker’s Guide the Galaxy, debating connotation, implication and meaning across linguistic, moral, political and all other grounds is an almost endless task.

Assuming transparency can assure trust and fairness is possible, open sourcing the Twitter algorithm assumes the algorithm is readable and understandable. The algorithm likely relies on complex, doctorate-level logic and mathematics. The algorithm likely includes machine learning, which uses no defined algorithm. The algorithm likely depends on custom databases and communication mechanisms, which may also have to be open sourced and explained.

This complexity means few will be able to understand and evaluate the algorithm. Those that can may be accused of bias just like the algorithm. Some may have motivations beyond judging fairness. For example, someone may exploit a weakness in the algorithm to unfairly amplify or suppress a tweet, individual or perspective.

Musk’s plan assumes Twitter has a single algorithm and that algorithm takes a list of tweets and ranks them. It is likely a combination of different algorithms, instead. Some work when tweets are displayed. Some run earlier for efficiency when tweets are posted, liked or viewed. Different languages, countries or markets may have their own algorithms. To paraphrase, J.R.R. Tolkein, there may not be one algorithm to rule them all.

Having multiple algorithms means each must be verified, usually independently. It multiplies the already large effort and problems of ensuring fairness.

Musk’s plan also assumes the algorithm changes infrequently. Once verified, it is trusted and Twitter can move on. However, experts continue to improve algorithms, making them more efficient or engaging. Hardware improves, providing more computation and storage. Legal and political landscapes shift. Significant events like elections, pandemics and wars force tweaks and corrections.

Not only do we need to have a group of trusted experts evaluating multiple complex algorithms, they need to do so repeatedly.

Ignoring potentially reduced revenue from algorithm changes, open sourcing Twitter’s algorithm also threatens Twitter’s competitive advantage. Anyone could take that algorithm and implement their own social network. Twitter has an established brand and user base in the West, but its market share is far from insurmountable.

There are other aspects to open sourcing. For example, if Twitter accepts third party code contributions, it must review and incorporate them. This could leverage a broader pool of contributors than Twitter’s employees but Twitter probably does not need the help. Silicon Valley tech companies attract good talent easily. Some contributions could contain subtle but intentional security flaws or weaknesses.

If the goal is to have a choice of algorithms, is this choice welcome or does it place more cognitive load on people just wanting a dopamine hit or information? TikTok succeeded by giving users zero choice, just a constant stream of engaging videos.

Evaluating an algorithm’s effectiveness is more than just understanding the code. It requires access to large volumes of test data, preferably actual historical tweets. Only Twitter has access to such data. Ignoring the difficulty of disseminating such a huge data set, releasing it all would violate privacy laws. Providing open access to historical blocked or personal tweets would also erode trust.

Elon Musk has demonstrated an uncanny ability to succeed at previously unprofitable enterprises like electronic vehicles and space travel. Perhaps there is more to Elon’s Twitter plan than is apparent. Perhaps he is saying what he needs to say to ensure public support for his Twitter takeover.

While open sourcing Twitter’s algorithm appeals to the romantic notion that information is better free, increased transparency will not create a “maximally trusted and broadly inclusive” Twitter. Social networks like Twitter coalesce almost unbelievable amounts of data almost instantly into our hands. They have difficulty with contentious issues and, therefore, trust because they reflect existing contention back at us. It is easier to blame the mirror than ourselves.

The image is a cropped version of https://commons.wikimedia.org/wiki/File:Programming_code.jpg. Used under Creative Commons Attribution-Share Alike 4.0 International license.

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