This move by Twitter is seen as a step in the right direction by many, as it allows users to scrutinize and improve the company’s algorithm. While many doubt that the code itself is truly open for inspection, this move provides transparency into how Twitter recommends tweets to users, and helps to foster trust among its user base.
The repositories, which are available on GitHub and Twitter’s official developer site, include code for the algorithm that determines which Tweets appear in a user’s For You timeline and for their engagement features. These features help Twitter keep people who are active on the platform more visible to their followers. By releasing this code, Twitter is taking another step towards being more transparent with its users and protecting itself from potential risks.
SpaceX CEO and Tesla CEO Elon Musk clarified on Twitter that Tesla will not be starting to produce vehicles inalienably powered by AI. They plan to first focus on building self-driving capabilities for their vehicles.
Similar to how the Linux operating system is open source, Tesla’s social media algorithm will also be made available to the general public in order for users to inspect and report any exploits found. This way, Tesla can quickly update their algorithm in order to maintain a high level of security for their users.
While the open source releases of Twitter’s code may be helpful to developers, they do not offer a complete picture of how the platform works. For instance, the releases do not include code that powers Twitter’s ad recommendations or the data used to train its recommendation algorithm. Moreover, there are few instructions on how to inspect or actually use this code – reinforcing the idea that these releases are strictly developer-focused. In light of this lack of transparency and accessibility, it is difficult for individuals and organizations outside of Twitter to understand exactly what effects their actions have on the platform – an essential factor in ensuring risk isn’t taken on unnecessarily.
Twitter included a policy of not including code that compromises user safety and privacy, as well as measures to protect the platform from bad actors. Inclusion of such code could have negative consequences, including undermining their efforts at combating child sexual exploitation and manipulation. By excluding these risks, Twitter leverages its community and brands to create a safe environment for users.
One of the big hot topics on the internet these days is code reviewers and code management. Groups like Stack Overflow, GitHub, and CodePlex have become a go-to for people looking for help completing projects. Twitter’s recent announcement of a new tool to manage code suggestions from its community is definitely welcome news! This will make it much easier for users to find and use good coding practices without having to search through innumerable sources.
This algorithm is designed to optimize different aspects of Twitter. For example, it’s designed to prevent users from seeing content that is harmful or inappropriate. It’s also meant to improve the quality of tweets by hiding certain ones if they might not comply with Twitter’s guidelines. Additionally, the algorithm is programmed to help increase user trust by downranking abusive and illegal tweets.
Twitter’s recommendation engine is a critically important part of the social media site. According to Twitter, the recommendation pipeline runs approximately five billion times per day and makes recommendations based on a user’s past interactions with other users and content on the platform. This helps people find information they’re likely to enjoy, which is an essential part of Twitter’s mission.
Twitter has updated their algorithm to include a more even split of tweets from people you don’t follow and those you do. This is supposed to help promote engagement and make Twitter more interesting for users.
The release of the source code comes after controversies involving tweaks to Twitter’s recommendation algorithm, including a call by Tesla CEO Elon Musk to have his tweets recommended more highly. Critics argue that these changes disproportionately favor certain voices, and could skew public opinion.
