Abstract

Black residents make up approximately 80% of Detroit, Michigan's population and earned a median household income under $35K per year, pre-pandemic. Since COVID-19, nearly half of the residents in Detroit have lost their jobs and nearly 2,000 residents have loss their lives. In 1965, Dr. King urged America not to prioritize "machines and computers, profit motives and property rights," over people, and warned that if it did, "the giant triplets of racism, materialism, and militarism were "incapable of being conquered." Detroit has invested millions of dollars in various forms of artificial intelligence and surveillance in the city since 2016. Will these investments lead to a better quality of life and safety for Detroiters, or are there other ways to think about innovation in the city? How can data and technology be leveraged to intervene in the looping cycle of injustice?

• Video

Abstract

The online far right ecosystem is heterogeneous, dynamic, and complex, as is the online ecosystem about covid-19. These two ecosystems are intimately intertwined. I will discuss some of the features of each together with their connections, viewed through the lens of network science and data science. In particular, I will discuss a "sentinel node" approach for examining online structure of the far right and covid ecosystems, and use this approach to examine how covid misinformation propagates within and between communities.

• Video

Abstract

The US public has a constitutional right to access criminal trial proceedings. In practice, it is difficult to exercise this right as well as to quantitatively study federal sentencing disparities. We have assembled a public database of criminal sentence decisions made in federal district courts called JUSTFAIR: Judicial System Transparency through Federal Archive Inferred Records. This large-scale database links information about defendants with information about their federal crimes and sentences, and, crucially, with the identity of the sentencing judge. In this talk, we discuss challenges associated with assembling this database as well as preliminary work and observations from studying sentencing equity and patterns of individual judges.

• Video

Abstract

In this talk, we discuss our approach to looking at science and mathematics policy documents as public records of attitudes towards equity and inclusion in science education. In particular, we examine how such reports change over time - and what that says about how the revision process enhances or dilutes attention to equity and justice for STEM. We also invite broader collaboration to encompass a wider range of policy documents.

Abstract

Women constitute approximately 50% of the population and have been an active part of the U.S. workforce for over half a century. Yet women continue to be poorly represented in leadership positions within business, government, medical, and academic hierarchies. As of 2018, less than 5% of Fortune 500 chief executive officers are female, 20% of the U.S. Congress is female, and 34% of practicing physicians are female. The decreasing representation of women at increasing levels of power within hierarchical professions has been called the “leaky pipeline” effect, but the main cause of this phenomenon remains contentious. Using a mathematical model of gender dynamics within professional hierarchies and a new database of gender fractionation over time, we quantify the impact of the two major decision-makers in the ascension of people through hierarchies: those applying for promotion and those who grant promotion. We quantify the degree of homophily (self-seeking) and gender bias in a wide range of professional hierarchies and demonstrate that intervention may be required to reach gender parity in some fields. We also preview an in-progress effort to extend the model to quantify racial bias and homophily in professional hierarchies.

• Video
• Slides

Abstract

The Voting Rights Act of 1965 requires that our electoral systems safeguard the opportunity for minority groups to elect candidates of choice. In over 55 years since its appearance on the scene, the VRA has been repeatedly refined and expanded, and a whole system of statistical methods has been built to support its enforcement. Today it's teetering on the edge of oblivion in the face of a turbocharged conservative Court. This might require adaptation and modernization, either to save or replace it. I'll describe two computational redistricting projects that look at futures for the VRA. Collaborators include Doug Spencer, Parker Rule, Gabe Schoenbach, Amy Becker, Dara Gold, and Sam Hirsch.

Abstract

The US political system is built on representatives chosen by geographically localized regions. This presents the government with the problem of designing these districts. Every ten years, the US census counts the population and new political districts must be drawn. The practice of harnessing this administrative process for partisan political gain is often referred to as gerrymandering. How does one identify and understand gerrymandering? Can we really recognize gerrymandering when we see it? If one party wins over 50% of the vote, is it fair that it wins less than 50% of the seats? What do we mean by fair? How can math help illuminate these questions? How does the geopolitical geometry of the state (where which groups live and the shape of the state) inform these answers? For me, these questions began with an undergraduate research program project in 2013 and has led me to testify twice in two cases: Common Cause v. Rucho (that went to the US Supreme Court) and Common Cause v. Lewis. This work has partially resulted in the redrawing of the NC State Legislative district maps and NC congressional maps. The resulting new maps will be used in our upcoming 2020 elections. In the remedy phase of North Carolina v. Covington, Greg Herschlog from the Duke group addresses the question if attempts to satisfy the VRA alone explained the observed level political packing and cracking. This is a story of interaction between lawyer, mathematicians, and policy advocates. The legal discussion has been increasingly informed by the mathematical framework. And the mathematics has been pushed to better include to the policy. The back and forth has been important to find ways to effectively inform the policy makers and courts to the insite the analyses provide. The problem of understanding gerrymandering has also prompted the development of a number of new computational algorithms which come with new mathematical questions. The next round of redistricting analysis will necessarily need to be more refined and nuanced. There is also the opportunity to be less reactive. There are opportunities to try to influence the process by which new maps are drawn before turning to the courts. There is also the possibility to direct the conversation by showing the effect more fully considering factors such as communities of interest, incumbency or proposed procedural elements of laws. This presentation reflects joint work Gregory Herschlag and a number of other researchers including many undergraduates, graduate students, and a few high school students.

• Video

Abstract

Our society remains profoundly unequal. This talk presents several vignettes about how data science and machine learning can be used to reduce inequality in healthcare and public health, focusing on applications in women's health, COVID-19, policing, and pain.

• Video

Abstract

In the United States, there are serious and persistent disparities in health outcomes. For example, socioeconomic status is predictive of mortality and disease, with low-SES households disproportionately experiencing the poorest health outcomes. This inequality is due in large part to the social determinants of health—social, physical, and economic conditions that make it more challenging to achieve wellness in low-SES communities. Disruptive innovations are sorely needed to reduce health disparities. Information and communication technologies (ICTs), with their growing ubiquity and ability to provide engaging, informative, and empowering experiences for people, present exciting opportunities for health equity research. This talk will overview a set of case studies demonstrating work the Wellness Technology Lab has done to design, build, and evaluate how novel interactive computing experiences can address issues of health equity. These case studies investigate how social, mobile, and civic technology can help low-SES communities to both cope with barriers to wellness and address these barriers directly. Using findings from this research, I will articulate opportunities and challenges for community wellness informatics—research that explores how ICTs can empower collectives to collaboratively pursue health and wellness goals.