Leaders in Academia and Industry Inspire Next Generation of Computational Social Scientists
This blog is part of the 2022 series “The Future of Computational Social Science is Black” about SICSS-Howard/Mathematica, the first Summer Institute in Computational Social Science held at a Historically Black College or University. To learn more about SICSS-H/M’s inaugural start, read last year’s blog “Welcome SICSS-Howard/Mathematica 2021” or our first blog “Uncovering new keys to countering anti-Black racism and inequity using computational social science.” If you are interested in applying to participate in SICSS-H/M 2023, check out our website.
The 2022 Summer Institute in Computational Social Science sponsored by Howard University and Mathematica (SICSS-Howard/Mathematica) hosted four guest speakers, Shawndra B. Hill, PhD, Karen Levy, PhD, Brandeis Marshall, PhD, and Kyla McMullen, PhD. Each pre-recorded a presentation and participated in a live Q&A session during the second week of the institute. Their lectures focused on their research and ideas on data science in marketing, truck driver job prospects, harmful algorithms, and new audio environments while orbiting pivotal themes of technological determinism, bias, and privacy respectively. Guest speakers also addressed the connections between their studies and their thoughts about inclusion, equity, representation, diversity and touched upon how they address or think about the rights of their research subjects.
Monday, June 27th, 2022
Karen Levy
Karen Levy was the first featured speaker at SICSS-Howard Mathematica 2022. An Associate Professor of Information Sciences at Cornell University and associate member of the faculty of Cornell Law School, her work sits on the intersection of labor and technology. Her presentation, entitled “RoboTruckers: The Double Threat of AI for Low-Wage Work,” addressed the narrative of autonomous vehicles taking over truck drivers’ jobs. To learn more about truck drivers’ opinions, she interviewed many about their lived experiences. From these results, she argued that the main concern should be that “what it is to be a driver will be different...” rather than autonomous vehicles replacing jobs. Levy further elaborated that “what we actually see happening is truckers and machines integrating into one another,” like the mandated electronic logging devices that already join drivers inside their trucks. With her focus on truck drivers, she hopes that society will advocate for hard workers who are exploited by the implementation of technology to overwork, work without pay, and work undesirable hours.
During her live Q&A session, Levy answered questions about female truck drivers within a male-dominated field, truckers’ identities, and the ethical research engagement practices she takes on as someone who isn’t a part of the trucking industry. She approaches her work by “speaking with” rather than “speaking for” the truckers and is honest about her position and identity in the research field to reflect that. To protect her subjects, Levy also collects oral consent and has generally declined to learn the names of those she interviewed. In response to a question about immigrant communities, Levy touched upon their tendency to congregate around trucking where working conditions could potentially improve due to the familiar aspect but does not fully eliminate the xenophobia that still occurs at truck stops or with law enforcement.
Tuesday, June 28th, 2022
Brandeis Marshall
Brandeis Marshall, the second featured speaker for SICSS Howard/Mathematica, is a data practices teacher, speaker, writer, and entrepreneur, who founded and is the CEO of DataedX Group. She is driven by a passion to educate others on harmful algorithms and data practices, and emphasized the ignored definition of bias as social injustice rather than statistical errors in code in her presentation. Her talk, entitled “Data Conscience: Algorithmic Siege on our Humanity” (which is also the title of her book), introduced her idea of a “Bias Wheel”: a concept that describes how different types of biases can impact each other in the same fashion as how each side of the wheel has a transference of impact to the other side. She urges the audience to be mindful of how errors and oppression can show up differently for different demographics when interpreting results, as digital systems aren’t transparent about these overflowing impacts of biases on one another. By taking on this position, Marshall hopes that “we can be better stewards of how we are interpreting results.”
Marshall’s Q&A was spent inspiring participants through anecdotes on the bumps and bruises she earned in academia and how she has invested in herself and her dreams. She then led a discussion with Naniette about bell hooks and Black feminist thought and spoke about how it’s often forgotten that many of the great ideas and movements in the history of humanity originated from people of color. The conversation also steered back to the Bias Wheel and relevant examples that support this, such as Apple giving women a lower starting credit limit than men and Covid-19 impacting populations in different ways, at different times throughout the pandemic.
Wednesday, June 29th, 2022
Kyla McMullen
Kyla McMullen, Associate Professor of Computer and Information Science and Engineering Department at the University of Florida talked about “Using Data to Customize the 3D Experience.” Professor McMullen shared her passion for creating 3D audio environments in virtual and augmented reality with SICSS-H/M participants. She shared that it started with a fascination with the importance of sound for experiences like action confirmation, error indication, and later her specialty AR and VR immersion enhancement. McMullen uses a sound filter called Head Related Transfer Function (HRTF), which she described using the example of placing a microphone inside a person’s ear that picks up sounds played at different locations on the left and right side of their head. The end goal is that this information is needed “so that when [a sound] is played back over headphones, it sounds like it is coming from that same measured location.” McMullen uses HRTFs in her studies on improving sound experience and also to explore ways to improve sound in emergency situations, such as “augment[ing] search and rescue tasks with 3D sound so that people can be found quicker.”
During McMullen’s live Q&A, she dove deeper into her experimentation, touching upon how her team took steps to prevent exclusion that could occur due to variations in head shape or hair style. For example, McMullen and her team asked participants to tightly tie their hair back or wear a swim cap to minimize error. After introducing more research gaps that can arise in measuring HRTFs, she expressed her hopes for other researchers to collaborate and find more effective processes from her public HRTF database. McMullen was also inspired to chat with her lab about privacy implications after recognizing that the collected and stored mesh file head scans could be used in facial recognition software as personal identifying information.
Thursday, June 24th, 2021
Shawndra B. HIll
Shawndra B. Hill, a senior lecturer at Columbia Business School, was the last guest speaker for SICSS Howard/Mathematica 2022. Hill’s presentation “Data Science for Marketing” explored the opportunities within the marketing industry for those with computational social science and data science backgrounds. She went in depth about some projects she worked on involving both observational and experimental data from social networks and TV ads to measure impact on online activity and users over time. Hill also introduced the concept of inclusive ads in terms of age, gender, and race and the potential business revenue of such an ad. Through these different examples, she expressed the excitement for this new intersection of work and recognized that there aren’t “ tons of people getting degrees in computational social science that think about…pursuing marketing as an area for data science or computational social science.”
Hill’s Q&A was full of key takeaways, valuable resources, and advice for SICSS-H/M participants interested in utilizing their technical skills in market research. To those interested in her data science research background, Hill addressed her hopes and worries for data science in advertising and her experience with Institutional Review Boards. Moreover, in the spirit of SICSS-Howard/Mathematica’s focus on diversity, equity, and inclusion, Hill touched upon the topics around privacy and inclusion. One of the resources she provided was the Marketing Science journal which has a planned special issue on Diversity, Equity, and Inclusion for participants to learn about upcoming projects on perceived inclusivity within marketing. She then stressed the need to hold oneself morally accountable in advertising by following regulations, considering users’ privacy concerns, and sharing proposed ideas with many people for more input in order to minimize any potential harm.
Across the two years of hosting SICSS-H/M, we have had assistant professors, associate professors, full professors, and people using their doctorates in industry as our guest speakers, with the vast majority being women and/or people of color with topics focusing on the experience of people of color and other marginalized groups. SICSS-Howard/Mathematica welcomed four incredible women - Shawndra B. Hill, PhD, Karen Levy, PhD, Brandeis Marshall, PhD, and Kyla McMullen, PhD - in 2022 to share their research and personal trajectories. They all shared a deep interest in seeing the next generation of computational social scientists rise up to build upon research that they and others have done so far.
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About the authors
Naniette H. Coleman is a PhD candidate in the Sociology Department at the University of California, Berkeley and a UC-National Lab In-Residence Graduate Fellow (Los Alamos National Lab). Her work sits at the intersection of the sociology of culture and organizations and focuses on cybersecurity, surveillance, and privacy in the US context. Specifically, Naniette’s research examines how organizations assess risk, make decisions, and respond to data breaches and organizational compliance with state, federal, and international privacy laws. Since 2016, Naniette has directed the AAC&U award winning Interdisciplinary Research Group on Privacy/Coleman Research Lab at Berkeley. Naniette holds a Master of Public Administration with a specialization in Democracy, Politics, and Institutions from the Harvard Kennedy School of Government, and both an MA in Economics and a BA in Communication from the University at Buffalo, SUNY. A non-traditional student, Naniette’s prior professional experience includes local, state, and federal service, as well as work for two international organizations, and two universities.
Kristina Hiraishi is a fourth-year undergraduate at the University of California, Berkeley, pursuing a degree in Data Science with an emphasis in Economics. She formerly served as a research assistant, project lead, and co-lab manager in the AAC&U award-winning, Berkeley-based Interdisciplinary Research Group on Privacy/Coleman Research Lab. Kristina served as an event Assistant for SICSS-Howard/Mathematica 2021 & 2022 focusing on participant experience, background research, writing, and editing. She plans to either pursue a career in privacy program management or enroll in an information management graduate program in the future.