Twitter launched an initiative on “responsible machine learning” yesterday, that will include reviews of algorithmic fairness on the social media platform.
The initiative called Responsible Machine Learning (ML), consists of the four pillars: taking responsibility for algorithmic decisions; equity and fairness of outcomes; transparency about decisions and how Twitter arrived at them and enabling agency and algorithmic choice.
According to the statement released by Twitter’s Staff Product Manager ML Ethics, Transparency & Accountability (META), Jutta Williams and Director., Software Engineering, Rumman Chowdhury, r responsible technological use includes studying the effects it can have over time and when Twitter uses ML, it can impact hundreds of millions of Tweets per day and sometimes, the way a system was designed to help could start to behave differently than was intended.
“These subtle shifts can then start to impact the people using Twitter and we want to make sure we’re studying those changes and using them to build a better product,” Jutta and Rumman said.
The initiative will be led by Twitter’s ML Ethics, Transparency and Accountability (META) team, a dedicated group of engineers, researchers, and data scientists collaborating across the company to assess downstream or current unintentional harms in the algorithms the platform uses and to help it prioritise which issues to tackle first.
“We’re conducting in-depth analysis and studies to assess the existence of potential harms in the algorithms we use,” Jutta and Rumman said.
In the announcement, Twitter also listed down some analyses Twitter users will have access to in the upcoming months:
- A gender and racial bias analysis of Twitter’s image cropping (saliency) algorithm
- A fairness assessment of Twitter’s Home timeline recommendations across racial subgroups
- An analysis of content recommendations for different political ideologies across seven countries
This move by Twitter follows a series of controversies at Google’s AI ethics team which resulted in the firing of two top researchers and the resignation of a high-ranking scientist