Lunch with Chelsea Manning

By Emma Coleman

On October 25, the Data Science Initiative welcomed Chelsea Manning, acclaimed data analyst, trans activist and whistleblower, to engage in conversation with students, faculty, and staff over lunch. Her visit to Brown was hosted by Brown War Watch and also included a keynote address.

Manning, whose accomplishments range from the 2013 International Peace Bureau’s Sean MacBride Peace Prize to the recent publication of her memoir, “README.txt,” listened intently to the questions and thoughts of students who attended the discussion, including undergraduates, data science and computer science master’s students, and Ph.D. students in computer science and computational biology, and enthusiastically riffed with the attendees on the ethical questions faced by the data science community. 

The conversation centered around the ethical implications of working in data science today. With social media and large corporations like Google, Amazon and Meta reigning supreme, data scientists have been thrown into an arena of ethical ambiguity, with large collections of personal data at their disposal, and inadequate regulation or guidance on safe practices. 

“It alarms me that data scientists aren’t held to the same ethical standards as doctors and lawyers, despite being just as, or even more, influential to people’s lives,” Manning stated, while discussing the implications of the vast amounts of data that corporations and governments can access. “Perhaps we should have some form of Hippocratic Oath.”

“We are the first generation of data scientists,” Manning explained. “There are no mistakes for us to learn from.” Data scientists today are navigating issues of privacy, surveillance, and access that affect everyday lives; Manning deftly explored these conundrums with honesty and insight, admitting to several questions from the audience that she didn’t know the full answer to their questions. “I strongly advocate for data scientists to be asking these questions,” she reinforced emphatically. She made the point that often no data collection can be preferable to any kind of “ethical data collection” that society could come up with. 

Manning also discussed the current climate of “gamification and commodification” that technology has brought to so many of our social interactions, which can lead to exhaustion and burnout. She suggested that the current data science climate was not only a crisis of values, but a crisis of health. 

The discussion circled back often to the values of data scientists. "Where is the vision? What are the goals? What are we trying to do?" Manning suggested it was these questions that first prompted her to expose the unethical data collection practices of the US military in 2010. 

One question posed by a student encapsulated a central theme: “What can one data scientist do,” when asked to go against their own ethics, knowing they can simply be replaced by someone who will do what they won’t? Manning acknowledged the problem, and suggested that unionization and other forms of mutual solidarity amongst ethically-minded scientists is an incomplete but necessary solution. If there are enough people in the industry who are dedicated to creating tools that promote ethical data handling, it is possible to lay out the standards expected by data scientists in the future. Decisions made now are the building blocks of the industry in the future, Manning cautioned.

Leah Rosenbloom, a Ph.D. candidate in computer science whose work addresses issues of social justice in the context of technology, noted that when Manning asked the group, "Why do you want to do data science? What are your values?" not many people responded. Rosenbloom says, “I think we should continue to think about these questions, as students who work in (or are adjacent to) data science.”

Manning’s general approach to addressing the issues raised was to highlight that these discussions need to take place, and the students in the room needed to be engaged as they move into careers as technologists. She was comfortable saying that she didn’t have all the answers, and she was optimistic that we could reach better solutions to problems raised by data and technology.