X Introduces "Community Annotations" Feature: Contradicting Musk's Statements! Unveiling the Mechanism behind Collaborative Truth Restoration.

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Last week, Ethereum's founder, Vitalik Buterin, published a lengthy blog post titled "How Do I Regard Community Annotations?" In the post, he discussed the journey of X (formerly known as Twitter) through multiple small-scale tests, leading to the recent launch of a new feature - Community Notes.

Community Annotations is an inherent feature of X, yet its content remains independent of X's control, and it can even directly contradict statements made by Musk. This led Vitalik to applaud Community Annotations as one of the mainstream world's most Web3-spirited use cases. This article will first introduce how Community Annotations operate and then delve into its design philosophy and its commonalities with Web3.

Debunking Tweets

Have you ever blocked someone on a social media platform? Last week, the "Tesla Silicon Valley Owners' Club" tweeted on Twitter, asking their followers under what circumstances they would block others or turn off notifications. This tweet elicited a response from Musk, as astonishing as ever: "In the future, the platform will remove the 'block' function, except for direct messages."

Reaching this point, everyone's initial reaction was, "Huh?"

Musk, in his characteristic fashion, announced a major decision out of the blue. This has been his consistent style, and it's the content that the media loves to cover the most. Ever since Musk took over Twitter, everything from the brand name, logo, to the blue verification checkmark mechanism has been subject to change at his whim. People have grown accustomed to Musk's grand declarations, but probably no one would question his ability to remove the "block" button.

However, not long after, a explanatory text and two hyperlinks appeared below Musk's tweet:

Readers were directed to related content they might be interested in: "If the ability to block users is removed, X will violate the policies of the App Store and Google Play Store. This could lead to X being removed from these platforms. However, web applications are not subject to such policies."

https://developer.apple.com/app-store/review/guidelines/

https://support.google.com/googleplay/android-developer/answer/9876937」

This text is a system-generated informational note appended below the post, providing a sense of being a gentle reminder concerning the content of the tweet.

Although it's just a few lines of text, with this information in place, the media that was ready to sensationalize the matter might be disappointed. Because everyone is more aware of the full picture - Musk was probably talking nonsense; it's unlikely that he would actually remove the block button, as it could lead to Twitter's app being taken down by Apple and Google. This reversal of narrative, along with the explanatory text that redirects people's attention, is precisely the function of Community Annotations.

Community Annotations

"Community Annotations" is the updated name. In 2021, it had a more fitting title, "Birdwatch," which Twitter positioned as a community-driven approach to combat misinformation:

People seek to obtain the latest and most reliable information through Twitter. Hence, we add labels and background context to tweets, but we don't want to intervene only in cases of violations or societal concerns. We aim to extend the application of this mechanism through collaborative efforts of the community.

Birdwatch allows individuals to write notes for misleading tweets, offering helpful context. We believe this approach can become an instantaneous response mechanism to misinformation. Ultimately, our goal is to establish consensus among global Twitter users. When a broad and diverse set of contributors achieve consensus, the notes will be directly displayed on the tweets.

Indeed, Community Annotations aims to do more than just fact-checking; it also strives to provide users with comprehensive background information for reference. This is a tool that is highly essential in the "post-truth era." The book "The Post-Truth Era," published in 2018, mentions:

"The post-truth" does not signify that truth and reliability have vanished from this era. Instead, it points to people's diminishing emphasis on and contemplation of the authenticity of events. In the age of the internet, information is at our fingertips, yet most individuals prefer to stay within their comfort zones, consuming news that aligns with their perspectives, or readily believing various stories encountered online or heard from others. Subsequently, they easily judge and divide these events into starkly opposing categories.

However, within any event, scenario, or story, there exists a "contradictory truth" – narrators extract the aspects of truth that favor their own stance from the diverse facets of reality, influencing your attitude and behavior to achieve their objectives. This mechanism of truth operation has subtly altered your choices. Only by understanding the array of choices available can you genuinely possess the right to choose.

Using Musk's tweet as an example, Musk might genuinely want to remove the block button from his platform, and he certainly has the authority to alter features on his platform. Naturally, people are easily swayed by his tweets: What would happen if the block button were removed?

Fortunately, Community Annotations offered an immediate helping hand, and the direction of public opinion changed accordingly. This Community Annotation did not provide a verdict on the authenticity of the content but rather supplemented background knowledge. It was Musk's own statement, and unless he was hacked, there wasn't really an authenticity issue. Sometimes, providing context is more valuable than determining authenticity. Everyone can judge Musk's statement based on the information they have.

But who is so audacious as to challenge the leader, risking their job? The answer lies in a mechanism of collaborative, machine-filtered truth restoration. Collaborating is straightforward. The challenge is how to produce high-quality Community Annotations with minimal human intervention. This is where the power of the algorithms behind Community Annotations shines, and it's a key reason why Vitalik praises its alignment with the spirit of Web3.

Restoring the Truth

According to Vitalik's account:

Community Annotations are not composed by a small group of pre-selected experts; on the contrary, they are created through contributions and votes from anyone. The determination of which content is displayed or not is entirely governed by an open-source algorithm. There is a comprehensive explanation on the Twitter website about how the algorithm functions. Individuals can download notes and voting data that have been published, execute the algorithm locally, and verify if the output matches the content seen on the Twitter website.

This description brings to mind the theoretical basis of the blockchain consensus mechanism - the Byzantine Generals Problem.

Imagine a group of generals besieging a castle, with each general commanding their own army positioned at different points around the castle. The generals must reach a consensus on whether to attack or retreat, otherwise, the operation would fail. However, the challenge lies in the fact that communication among the generals can be disrupted by spies. How can consensus be achieved in an unreliable communication environment to win the war? This is the classic Byzantine Generals Problem in computer science, which blockchain also faces.

Every node (miner) on a blockchain acts like a general. Each time a block is added, it's akin to a decision on attack or retreat. Aside from ensuring accurate information propagation, efficiency must also be considered. This was a thorny issue in 1982, but by 2023, every blockchain has developed its consensus algorithm to address disagreements. Similarly, Twitter's Community Annotations feature also relies on a consensus algorithm to coordinate the content produced by individuals, striving to filter out the best outcomes to help people reach consensus.

Although multiple sets of Community Annotations can coexist under each tweet, which ones contribute to people's understanding of the whole picture and reaching consensus? Whether chosen by humans or AI, it might not be the most effective approach. The uniqueness of this consensus algorithm lies in its ability to rely on random sampling of evaluation feedback from people, ultimately having a chance to produce satisfactory results. Vitalik provides an example of one of the rules:

The rating mechanism is what sets this algorithm apart, making it exceptional. The Community Annotations' rating algorithm gives priority to the common intersection of various perspectives. In other words, if individuals who often disagree happen to reach a consensus on a particular note, that note's score will be notably high.

In other words, this algorithm not only anticipates people's stances but also prioritizes displaying Community Annotations that assist individuals with differing perspectives in reaching consensus. Operating information becomes strategically beneficial. While previous social media platforms' algorithms often relied on sparking conflicts to attract attention, the Community Annotations' algorithm is precisely the opposite; it favors consensus achievement, thereby helping people grasp the bigger picture.

Furthermore, this algorithm is entirely open-source. Users can download the Community Annotations left on Twitter along with pseudonymous evaluation feedback, execute it on their local computers, and independently verify that the Community Annotations displayed on Twitter haven't been manipulated and are entirely rule-based and unbiased. This closely resembles the operation of blockchain, and Vitalik calls this "Credible Neutrality."

The mechanism treats all results equally, leaving a trace for every outcome. If Musk is dissatisfied with attached Community Annotations, he can raise an appeal or propose modifications to the mechanism. Every outcome can be independently verified by individuals, alleviating concerns about being in a black box. This transition from centralization to decentralization is a tangible manifestation. It's somewhat similar to the situation last year when multiple exchanges exhibited their "proof of reserves" after the collapse of FTX. Users can finally verify whether platforms that were originally opaque have misappropriated assets or manipulated truths through an open mechanism (Merkle Tree, algorithms, and data).

I have more faith in human nature. People who spread false information may not necessarily be troublemakers; they might simply lack the context of events, turning them into victims of manipulated information. Community Annotations employ technological means to juxtapose tweets with factual information, enabling the speed of clarification to match the speed of rumor propagation. In essence, Community Annotations are like what people did years ago when they added "Fact-Checker Aunty" to LINE family groups, automatically fact-checking internet rumors upon receipt.

However, even the most remarkable technological tools have weaknesses. At the time, many elders, citing concerns about surveillance, kicked the "Fact-Checker Aunties" out of conversations. The Fact-Checker Aunties couldn't dispel their own rumors. Consequently, if you open LINE groups now, rumors still run rampant. Although Community Annotations attempt to restore the truth for people, they can't guarantee that in the future, rumors about themselves won't emerge, potentially undermining the whole mechanism.

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