Navigating Controversy in Computing Research: A Historical View of Data Ethics Work
Both data privacy and machine learning technologies/artificial intelligence have been behind a lot of attention-grabbing controversies. According to Katie Shilton, associate professor and program co-director of the BS in social data science at the College of Information Studies, a few have angered the public and shaken technology development communities: the Cambridge Analytica and PrePol scandals.
In 2013, A UK-based researcher collected data about 270,000 Facebook users using a Facebook app he created. The Facebook users were told the data collection was for research, but the researcher sold that data to commercial firm Cambridge Analytica. The firm then used the research data to target advertising for the Trump campaign.
In 2016, ProPublica–an independent, nonprofit newsroom–investigated PrePol, a prediction algorithm that calculated “recidivism scores” for use in sentencing and parole decisions. ProPublica found that, because of systemic biases in the data PredPol was trained on, the algorithm was twice as likely to falsely identify a Black defendant as a future offender than a white defendant.
“I just made a timeline of digital data research controversies for CITI training modules I’m developing, and there has been one or more a year since the early 2010s. (And that’s just in the digital research data space!),” Shilton says.
In a recent paper, “Ethics Governance Development: Bridging Ethics Work and Governance in the Menlo Report,” Shilton looks at how researchers have historically navigated such controversies. Beginning in 2009, a group of computer scientists, lawyers, and government officials made and sustained an effort to set ethical guidelines for information and communication technology (ICT) research, which culminated in the 2012 release of the Menlo Report in the United States’ Federal Register. Shilton (with her coauthor Megan Finn from the University of Washington) interviewed report participants to find out why and how the report and its guidelines came to be. We sat down with Shilton to discuss her experience working on this paper and where she thinks data ethics governance is going.
The following is a Q&A with Shilton, an associate professor of information studies and co-PI of TRAILS
What motivated you to write this paper?
Megan Finn and I both teach courses in information ethics, and as part of our teaching, we teach ethical guidelines that have been created for information technology. The 2012 Menlo Report stood out to us because it was created by computer scientists for computer scientists, and it was written before big data and AI scandals were so publicly recognized. We wondered what inspired the Menlo authors to create computing ethics guidelines at a time when technology research and the technology industry was still in hype rather than “techlash” mode. And we wondered what today’s efforts to govern the ethics of information technologies could learn from this earlier effort.
What is ethics governance and what is its current state in ICT research?
Ethics governance is the attempt to steer the moral standards of a field or area by both enrolling people (in this case, researchers) into consensus norms, as well as “cutting” or excluding researchers who don’t agree with those norms. Right now, ethics governance in ICT research is, I would say, midstream. There’s growing agreement that computing researchers need ethical standards, and there have been lots of attempts to write those standards in small and large ways. But we’re still working out how to get consensus about the right standards to adhere to, how to build those standards into everyday technology research practices, and what it looks like to “cut” research that doesn’t fall into those standards (or even if “teeth” should be a part of ethics practice in the field).
Read the rest of the article by the University of Maryland College of Information Studies.