What’s making the company look for harmful impacts in their artificial intelligence systems?
Twitter is assessing its artificial intelligence/machine learning systems to assess racial and gender bias. In that attempt, Twitter is starting a new initiative called Responsible Machine Learning. Calling it a long journey in its initial days, the social media platform said the initiative will assess any “unintentional hams” caused by its algorithms.
“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”, said Jutta Williams and Rumman Chowdhury from Twitter.
The duo also added, “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.”
The company’s ‘Responsible ML’ group is interdisciplinary and consists of people from across the company, including technical, research, trust and safety, and product teams.
“Leading this work is our ML Ethics, Transparency and Accountability (META) team: a dedicated group of engineers, researchers, and data scientists collaborating from all domains of the company to analyze downstream or current unintentional harm in the algorithms we use and to help Twitter prioritize which issues to tackle first”, the company explained.
Twitter said it will research and understand the impact of ML decisions, conduct detailed analysis to assess the possibility of potential harms in the algorithms it uses. Some tasks will include looking for gender and racial bias in its image cropping algorithm, a fairness assessment of timeline recommendations across racial subgroups, and checking content recommendations for different political ideologies.
“The most impactful applications of responsible ML will come from how we apply our learnings to build a better Twitter.”
Building a better Twitter will mean changing its product like removing an algorithm and giving people more control over the images they tweet. The company also stated that it will also build explainable ML solutions so people can better understand its algorithms.