Twitter details plan to understand if its algorithms are causing ‘unintentional harms’
- Twitter’s algorithms have been accused of racial bias in the past.
- The social networking service has also come under attack from people of different political ideologies of favouring one over the other.
- The company has set up a META team that will study the issues and implement solutions.
The plan – dubbed as the “Responsible Machine Learning Initiative” – will study Twitter’s existing algorithms that offer content recommendations and crop images on the platform.
“We’re conducting in-depth analysis and studies to assess the existence of potential harms in the algorithms we use,” the company noted in its blog post.
So, what exactly is “Responsible Machine Learning”?
Responsible machine learning consists of assigning responsibility, achieving equity and being transparent about the way Twitter’s machine learning-driven algorithms function.
In essence, the intended outcome of this study is to ensure Twitter users better understand these algorithms and how these algorithms shape the content that they see on the platform.
Twitter has formed what it calls a META team – ML Ethics, Transparency and Accountability – that is tasked with undertaking this study and improving the user experience based on the findings of the study.
Why does Twitter need Responsible Machine Learning?
Twitter has faced backlash in the past for several issues, and one of them includes the image cropping algorithm which has been found to have a racial bias in favour of people with lighter skin.
Trying a horrible experiment...Which will the Twitter algorithm pick: Mitch McConnell or Barack Obama? https://t.co/bR1GRyCkia— Tony “Abolish ICE” Arcieri (@bascule) 1600553103000
Another example highlights the problem even better – wherein Twitter’s algorithms pick up Obama’s face with a lighter tone over a darker one.
These images in particular, comparing low contrast to high contrast Obama, are much more telling. The algorithm see… https://t.co/5Lgt5QV8vK— Tony “Abolish ICE” Arcieri (@bascule) 1600721615000
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