Fall 2016 Talk Schedule

September 20: Dr. Steven Johnson

Dr. Steven Johnson

Steven L. Johnson is an Associate Professor of Commerce at U. of Virginia McIntire School of Commerce. His research interests include innovation communities as a form of social media that support organizational knowledge management. He is particularly interested in social exchange, group dynamics and emergent leadership. His research has appeared in top-tier management journals of Management Information Systems QuarterlyOrganization Science, and Information Systems Research. He received a PhD from the U. of Maryland Robert H. Smith School of Business in 2008. Before pursuing his doctoral studies, he worked in the information technology industry for 15 years. While teaching at Temple U. Fox School of Business from 2008-2015 he was a pioneer in the use of gamification in the classroom in a course he developed on Social Media Innovation.

Revisiting Traditional Behavioral Research Practice in the Era of Big Data

Through building and testing theory, the practice of research animates data for human sensemaking about the world. Behavioral research began in an era when research data was scarce; in today’s age of big data, it is now abundant. Yet, traditional behavioral Information Systems researchers often enact methodological assumptions developed in a time of data scarcity, and many remain uncertain how to systematically take advantage of new opportunities afforded by big data. How should we adapt our research norms, traditions, and practices to reflect newfound data abundance? How can we leverage the availability of big data to generate cumulative and generalizable knowledge claims that are robust to threats to validity? In our opinion, many benefits of big data will be realized only with a thoughtful understanding of the implications of data abundance and, increasingly, a deliberate shift in research practices. We advocate for a need to re-visit and extend—not discard—the traditional hypothetico-deductive model that is commonly used to guide quantitative behavioral research. We propose a research approach that incorporates consideration of big data—and associated implications such as data abundance—into a classic approach to building and testing theory.
October 4: Karen Boyd
Karen is a PhD student in the University of Maryland’s iSchool studying values and ethics in design with Dr. Katie Shilton. She’s interested in understanding how we can make work and its products better for the humans involved. Before pursuing research, she earned an MBA from the Rady School at UCSD and spent 5 years in the software industry doing mostly project management and marketing research.
Who is Responsible for User Privacy? Professional Discourse and Responsibility in Software Development
Software can have broad social consequences: our social networks, political voices, and natural environment can all be influenced by software, even software we don’t use ourselves. Who is responsible for the impacts? How can we understand the cultures in which those ethical decisions are made? I’ll discuss a view of occupational culture and a discourse about user privacy that can help us better understand and address ethical decisions made in software development.
October  18: Melissa Kenney
Melissa Kenney is an Assistant Research Professor in Environmental Decision Support Science, at the University of Maryland, Earth System Science Interdisciplinary Center. Dr. Kenney conducts research in decision support science to understand and improve the processes and tools to support evidenced-based decision-making. She was a lead author of the Decision Support Chapter of the 2014 U.S. National Climate Assessment and is currently a AAAS Leshner Leadership Institute Public Engagement Fellow. She received her Ph.D. from the Duke University. http://indicators.umd.edu
Effective Scientific Information Translation to Support Environmental Decision-making
Environmental management decisions are hard because they involve uncertain science, and multiple objectives that involve trade-offs, and varying risk preferences by stakeholders. Additionally, engagement with the public and decision-makers is a necessary component for understanding the important environmental and societal system components and their interactions.  Thus, effective environmental decision support systems include both decision support tools as boundary objects and boundary processes to enable evidenced-based policymaking. I will illustrate, through examples, how we have increased understanding and improved the processes and tools that aid decisions at the nexus of the environment, technology, and society.


November 1: Anna Lauren Hoffman

headshot2Anna Lauren Hoffmann is a postdoctoral scholar at the UC Berkeley School of Information, where conducts research and teaches at the intersections of data, technology, culture, and ethics. In particular, her work considers the ways in which the design and use of information technology can promote or hinder the pursuit of important human values like respect and justice. In addition, she employs discourse analysis to explore the values and biases that underwrite understandings of technology, privacy, and ethics as promoted by various stakeholders.


Toward a Conception of Data Violence
The lives and experiences of trans people and other gender minorities challenge our understandings of “big data,” gender, and technology in important ways. In particular, they lay bare the limits of rigid or fixed categories for capturing fluid or multifaceted identities, urging further examinations into the ways data subjects are constrained by biases and assumptions in scientific and technological development. To account for these challenges, the author draws on work in information ethics, surveillance studies, and critical trans politics to articulate a conception of “data violence” that captures the harm inflicted on trans people and other gender minorities by the many information systems that permeate our everyday social lives.
November 15: Priya Kumar
dsc_5043_2-1Priya Kumar is a doctoral student at the University of Maryland’s iSchool, where she studies the intersection of privacy, families, and technology use. Her research has been referenced on NPR, Buzzfeed, Slate, the Washington Post, the Financial Times, Time, and the Brooklyn Quarterly. Before joining the doctoral program she worked on the Ranking Digital Rights project, which evaluates the world’s largest technology companies on their respect for users’ rights to freedom of expression and privacy. Priya holds a master’s degree in information from the University of Michigan and bachelor’s degrees in journalism and government and politics from the University of Maryland.
Privacy Policies and Their Lack of Clear Disclosure Regarding the Life Cycle of User Information
Companies, particularly those in the information and communications technology sector, collect, aggregate, and store immense amounts of information about billions of people around the world. Privacy policies represent the primary means through which companies articulate to the public how they manage this user information. Extensive research has documented the problems with such policies, including that they are difficult to understand. This paper presents an analysis of 23 policies from 16 of the world’s largest internet and telecommunications companies and shows the specific ways that vague or unclear language hinders comprehension of company practice. It argues that the lack of clarity in such policies presents a significant barrier toward empowering people to make informed choices about which products or services to use. The incoherent language in privacy policies can also hinder the widespread adoption of machine learning or other techniques to analyze such policies. Clearer disclosure from companies about how they use, share, and retain all types of information they collect will shed light on what the life cycle of user information looks like.
 November 29: Anne Bowser

annebowserAnne Bowser is a Senior Program Associate with the Science and Technology Innovation Program at the Woodrow Wilson International Center for Scholars, a public policy think tank in Washington, DC that was recently ranked the #1 transdisciplinary think tank in the world. At the Wilson Center, Anne conducts research and other forms of capacity building to support open science by encouraging citizen science and open data initiatives. Dr.Bowser received her PhD from the University of Maryland’s iSchool in December 2015. Her dissertation research explored the cooperative design of Floracaching, a gamified mobile application for biodiversity data collection to support climate change research.

Research and Other Forms of “Capacity Building” to Support Citizen Science

Citizen science is a tool for improving the scientific research process, and an innovative governance model that offers the public expanded opportunities to drive research and decision-making. My personal research focuses on exploring cross-cutting issues, such as technology design and ethics, which alternatively advance and constrain this growing field. Beyond empirical research I conduct other forms of capacity building including directing studies and building communities, ranging from informal working groups to professional Associations. The first half of this talk will focus on two of my research projects, which aim to (1) understand technological appropriation in citizen science, and (2) asses the privacy concerns of citizen science volunteers. The second half of this talk will unpack the vague notion of “capacity building” to explore what it means to work in a public policy think tank, and live and work in the gray area between academia and the larger world.