>We worked on ways to improve our toxic-speech-identification algorithms so they would not discriminate against African-American Vernacular English as well as forms of reclaimed speech. All of this depended on rank-and-file employees. Messy as it was, Twitter sometimes seemed to function mostly on goodwill and the dedication of its staff. But it functioned. > >Those days are over. From the announcement of Musk’s bid to the day he walked into the office holding a sink, I watched, horrified, as he slowly killed Twitter’s culture. Debate and constructive dissent was stifled on Slack, leaders accepted their fate or quietly resigned, and Twitter slowly shifted from being a company that cared about the people on the platform to a company that only cares about people as monetizable units. The few days I spent at Musk’s Twitter could best be described as a Lord of the Flies–like test of character as existing leadership crumbled, Musk’s cronies moved in, and his haphazard management—if it could be called that—instilled a sense of fear and confusion. > >Unfortunately, Musk cannot simply be ignored. He has purchased a globally influential and politically powerful seat. We certainly don’t need to speculate on his thoughts about algorithmic ethics. He reportedly fired a top engineer earlier this month for suggesting that his engagement was waning because people were losing interest in him, rather than because of some kind of algorithmic interference. (Musk initially responded to the reporting about how his tweets are prioritized by posting an off-color meme, and today called the coverage “false.”) And his track record is far from inclusive: He has embraced far-right talking points, complained about the “woke mind virus,” and explicitly thrown in his lot with Donald Trump and Ye (formerly Kanye West). > >Devaluing work on algorithmic biases could have disastrous consequences, especially because of how perniciously invisible yet pervasive these biases can become. As the arbiters of the so-called digital town square, algorithmic systems play a significant role in democratic discourse. In 2021, my team published a study showing that Twitter’s content-recommendation system amplified right-leaning posts in Canada, France, Japan, Spain, the United Kingdom, and the United States. Our analysis data covered the period right before the 2020 U.S. presidential election, identifying a moment in which social media was a crucial touch point of political information for millions. Currently, right-wing hate speech is able to flow on Twitter in places such as India and Brazil, where radicalized Jair Bolsonaro supporters staged a January 6–style coup attempt. > >Musk’s Twitter is simply a further manifestation of how self-regulation by tech companies will never work, and it highlights the need for genuine oversight. We must equip a broad range of people with the tools to pressure companies into acknowledging and addressing uncomfortable truths about the AI they’re building. Things have to change.

This was an interesting perspective from someone who experienced this shift firsthand. It's certainly worth taking heed of the warning of algorithmic biases that are already baked into many systems. Further, self regulation though laudable, has proven at least in most tech sectors, to be ineffective at best. What we need are regulators who are familiar with key issues that are facing technology as it relates to broader society, but not beholden to tech companies or platforms. This will be tricky going forwards, but if properly administered can bring lasting benefits not just to the platforms, but also to the rest of society as well.