Twitter Kicks Off Companywide Responsible Machine Learning Initiative

Twitter is reining in the machines. The social network detailed its companywide Responsible Machine Learning initiative last week, saying that it is based on the following pillars: Taking responsibility for algorithmic decisions.Equity and fairness of outcomes.Transparency about decisions and how Twitter arrived at them.Enabling agency and algorithmic choice. Director of software engineering Rumman Chowdhury and staff product manager for ML ethics, transparency and accountability Jutta Williams wrote in a blog post last week, “Responsible technological use includes studying the effects it can have over time. 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.” The Responsible ML initiative is being spearheaded by Twitter’s ML ethics, transparency and accountability team, which is made up of a dedicated group of data scientists, engineers and researchers, and the working group includes Twitter employees from its product, research, technical and trust and safety teams. In-depth analyses currently being conducted with the goal of publicly releasing them in the coming months include: A gender and racial bias analysis of Twitter’s image cropping (saliency) algorithm.A fairness assessment of the social network’s home timeline recommendations across racial subgroups.An analysis of content recommendations for different political ideologies across seven countries. Chowdhury and Williams wrote, “The most impactful applications of responsible ML will come from how we apply our learnings to build a better Twitter,” saying that actions may include changes such as removing an algorithm, giving people more control over images they tweet or new standards for how policies are crafted when one particular community suffers an outsized impact. The company is also building explainable ML solutions with the aim of enabling people to better understand its algorithms, what informs them and how they impact what Twitter users see on the platform. Chowdhury and Williams added, “Similarly, algorithmic choice will allow people to have more input and control in shaping what they want Twitter to be for them. We’re currently in the early stages of exploring this and will share more soon.” Twitter plans to share its learnings and best practices in order to better the industry’s collective understanding of these matters, and it is developing more opportunities for feedback from its users. Chowdhury and Williams concluded, “Responsible ML is a long journey in its early days. We want to explore it with a spirit of openness with the goal of contributing positively to the field of technology ethics. If you have any questions about Responsible ML, or the work META’s doing, feel free to ask us using #AskTwitterMETA. If you’d like to help, join us.”

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Twitter Kicks Off Companywide Responsible Machine Learning Initiative

The social network will do a deep dive on the effects of its algorithms

David Cohen

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David Cohen