Save the date for CONNECT’s next event, a free, half-day workshop focusing on big data, bias, and health justice. The workshop will take place on July 19, 2019 from 11:00 am – 5:00 pm at the Institute for Sexual and Gender Minority Health and Wellbeing, 625 N Michigan Avenue, 14th floor.
Lunch will be provided with a reception to follow. Invited speakers and registration details are all forthcoming. The event will be available to livestream, details to follow.
Contact CONNECT@northwestern.edu to learn more.
About the event:
In the name of efficiency, our society increasingly relies on data to guide all forms of decision making. This cost-effective, data-led decision making, particularly when guided by unsupervised analytical methods, is often assumed to be free of human bias. However, there is growing concern about the potential misuse of these methods to further oppress already marginalized populations. From hiring decisions, to predictive policing, to auto insurance premiums, poor black and brown populations have been shown to be disproportionately impacted across a wide variety of domains. Less is known however about the impact of these systems on sexual and gender minority (SGM) populations.
Human biases emerge in these systems through various mechanisms. First, data can only mirror the existing social world – therefore analytical techniques which utilize existing data to predict the future will inevitably replicate and often amplify existing biases. Furthermore, decisions about what data are collected and what questions are important enough to be asked are also shaped by societal biases. Finally, those learning, developing, and deploying data science techniques are often are rarely connected to the communities most harmed by these practices. What results are data systems which function in ways to not only replicate but amplify existing biases and disproportionately hurt the least powerful populations.
Our workshop aims to bring together a diverse group of scientists, students, and community leaders at the intersection of technology, data science, and health equity to discuss bias in big data, how bias impacts all marginalized populations, and how bias may specifically impact sexual and gender minority communities.
Organizing the workshop will be Dr. Michelle Birkett, Assistant Professor of Medical Social Sciences and Director of the CONNECT Research Program on Complex Systems and Health Disparities at Northwestern University. CONNECT’s research focuses on understanding how multi-level mechanisms drive health disparities in stigmatized populations, with an emphasis on approaches using big data and network science, and on applying complex, cutting-edge methods to advance health equity research. Featured in this conversation will be Yeshimabeit Milner, Founder and Executive Director of Data 4 Black Lives, an organization which connects and mobilizes scientists to combat the oppressive application of big data. In addition to Dr. Birkett, Dr. Gregory Phillips (Director of the EDIT Research Program) and Dr. Lauren Beach (Associate Director of the EDIT Research Program), both faculty in Medical Social Sciences at Northwestern University, will provide featured talks. Specific topics to be discussed include how artificial intelligence and machine learning techniques perpetuate bias, how to best promote the inclusion of diverse voices in the fields of big data and data science, and what the specific challenges and opportunities are within data on sexual and gender minorities.
As we aim to utilize this workshop to build community around how bias in big data may impact SGM populations – the workshop will be livestreamed, as we’re mindful to not limiting this conversation to only the folks who can attend our event in person. Furthermore, all workshop materials and resources will be hosted online.
The workshop is sponsored by the Institute for Sexual and Gender Minority Health and Wellbeing, the Health Equity Hub within the Department of Medical Social Sciences, the Center for Health Equity Transformation, the Northwestern Institute on Complex Systems, and the Northwestern Data Science Initiative.