Twitter Reveals Algorithmic Fairness Initiative As Part Of “Responsible Machine Learning”

Twitter revealed its algorithmic fairness initiative as part of its initiative on “responsible machine learning”.

Twitter on Wednesday officially revealed its algorithmic fairness initiative as part of its initiative on “responsible machine learning”.

Twitter Algorithmic Fairness Initiative
Photo source: 9to5Mac

In a report on GMA News Online, Twitter said that it was launching an initiative on “responsible machine learning” – including reviews of algorithmic fairness on the platform.

According to Twitter, the said plan aimed to discuss the “potential harmful effects of algorithmic decisions” and to offer more transparency in its artificial intelligence.

The said move came amidst heightened concerns over algorithms used by online services, which some said can promote violence, extremist content, reinforce racial, or gender bias.

According to the researchers, the said initiative called for taking responsibility for their algorithmic decisions with the aim of “equity and fairness of outcomes”.

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Responsible technological use includes studying the effects it can have over time. When Twitter uses (machine learning), 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. We’re also building explainable ML solutions so you can better understand our algorithms, what informs them, and how they impact what you see on Twitter,” Rumman Chowdhury and Jutta Williams of Twitter’s ethics and transparency team said in a blog post.

Chowdhury and Williams also said that the team would be sharing what it learned with outside researchers in order to “improve the industry’s collective understanding of this topic, help us improve our approach, and hold us accountable.”

Based on a report on GMA News Online, the Twitter move followed a series of controversies at Google’s AI ethics team which resulted in the resignation of a high-ranking scientist and the firing of two top researchers.

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