Below are the collaborative projects for the 2017-2018 cycle.
Below are the collaborative projects for the 2017-2018 cycle.
CRISPR-Cas gene editing has the potential to increase individual and community wellness through the development of agricultural products and treatments for genetic diseases. Debates held in the 1970’s about recombinant DNA technology (rDNA) are frequently used as a model of successful governance for emergent technologies. Using these debates as models reinforces information boundaries between scientists and the public by having scientists with technical expertise lead decision-making that influences local, national and global communities.
This project aims to understand the democratic governance of novel technologies. How have scientists constructed the boundaries of public engagement in deliberations around new technologies in genetic engineering? How do these boundaries shape the potential of new technologies to improve individual and community wellness and healthcare? To address these concerns, we are comparing the process of public involvement and expert decision-making surrounding rDNA and CRISPR-Cas9 technologies.
Citizen Technologist blog series: “Backstage Decisions, Front-stage Experts”
A piece on the project in the UC Berkeley Department of Plant and Microbiology News: “Berkeley conference illuminates scientific history and its applications”
Fellows: Dan Sholler
The scientific community is adopting technologies and practices to support “open science.” Open science refers to the process of documenting the components of the research enterprise (e.g., data collection protocols, datasets, software source code, and publications) and making the outputs accessible for reuse. Proponents argue that open research processes enable replication and reproducibility of scientific studies and, in turn, foster transparency and accountability. Advocates also argue that taxpayers have a right to access publicly-funded research products. Opponents, though, doubt the promise of open science or begrudge the time-consuming documentation and distribution practices. This study seeks to document government policies in the United States that promote and coordinate open science efforts. I will interview and survey scientists to assess how they perceive the policies’ influence on their work. I will then develop recommendations for government agencies (and other regulatory bodies) on how to incorporate best-practices for open science into regulatory frameworks.
With mobile technologies and Internet access become increasingly prevalent across diverse contexts in Africa, multinational technology companies have set their sights on the continent as the next frontier for new users and testing grounds for their technologies. Companies like IBM Research and Facebook have announced their plans to work towards “solving Africa’s problems.” However, as technology companies continue to headquarter their core design and engineering teams in the United States, it is unclear how the designers and engineers conceive of the “everyday African” users for whom they are purportedly designing and building technology. Building on critical design scholarship and social studies of science and technology, this project seeks to understand the production of the “African technology user” imaginary. It also asks how and why User Experience (UX) and Human Computer Interaction (HCI) methods, in particular, are assumed to enable full understanding of end-users around the world?
Maternal and perinatal deaths are a cause of serious concern in the underserved regions of developing countries. As governments and development organizations have established programs to deliver better healthcare for women in such areas, access to accurate and timely information has become imperative for impact measurement, program evaluation, and resource allocation. In Nepal, One Heart Worldwide (OHW) is one such organization committed to delivering data-driven maternal and neonatal mortality prevention programs, but face several challenges due to the country’s transitioning government structure, limited infrastructure, low literacy, and lack of human resources in rural areas. Through human-centered and value-sensitive design, we aim to assist OHW by exploring potential socio-technical information systems that would best meet the needs and respect the values of the organization and its stakeholders. While we expect our findings to be highly particular to Nepal, we intend to understand how addressing these challenges may apply to other contexts.
The Achilles heel of many major democracies is the eternal need for sufficient engagement and attention from the community. Hence, major efforts have been put towards increasing these attributes of the community. We believe this is a fallacy. Our goal should be to make democracy work with minimal engagement. The ideal governance system is one where citizens do not have to be constantly involved but the system still acts as the citizens would like it to. We explore this fundamentally different approach: For a fixed level of community attention, how can we optimize the allocation of this attention to maximize productivity? We propose a novel “statistical quorum”, derived using first principles, as one metric the community can use to focus attention, in turn making the entire decision-making process dynamic. In developing and testing a web application centered around this metric, we will study how a community can simultaneously improve the legitimacy and efficiency of their decision-making process.
From the Bill and Melinda Gates Foundation to the Chan Zuckerberg Initiative (CZI), tech billionaires have undertaken development projects that address poverty, disease, education, global climate change, gender inequality, and other urgent social issues. This project seeks to understand how development is framed as a global “skills problem” through the lens of Silicon Valley logics and characterized as a problem of moral and humanitarian concern in need of technological intervention. This interdisciplinary, collaborative team proposes to understand how implicit, explicit, and sometimes contested desires for “scale”, “standardization”, and “sustainability” inform programming, funding, and evaluation in and of technologically-oriented foundations and firms. The project will leverage ethnographic insights derived from participant observation at relevant events in the Bay area and Los Angeles, in-depth interviews with key stakeholders working on technology and education/training, and textual analysis of artifacts and materials including training manuals, academic rubrics, blog posts, and reports.
Fellows: Michelle Carney
MLUX (“Machine Learning and User Experience”) is a professional meetup group focused on building a community around the emerging field of human-centered machine learning, meeting in San Francisco for monthly tech talks. We are professional UX Designers and Researchers, Data Scientists, PMs, Developers and everyone in between, and we aim to organize a community that helps foster cooperation, creativity, and learning across the UX and Data Science disciplines. One of the key areas of interest in this field is understanding how to design and use data science effectively and ethically. By partnering with CTSP and AFOG, we are excited to host an event centered around “Designing and using Data Science Ethically,” aimed at Tech professionals to share best practices and lessons learned from the field.
Machine learning has undergone a renaissance of methods in the last six years, and is being quietly introduced into nearly every aspect of our daily lives. In many instances, though, this is handled by private companies deploying proprietary software with little oversight. This results in a widespread impression that machine learning is a ‘black box’ with little hope for supervision or regulation.
With this project, we aim to join a growing community of researchers focused on unpacking this black box. First, we seek to map the disconnect between public conceptions and the actual processes of machine learning to illuminate how contemporary machine learning is done. Second, we seek to intervene in the process of defining and tuning machine learning models themselves, using the framework of value-sensitive design as a point of departure, to understand the values-related challenges in the design of machine learning systems.
Fellows: Kate M. Miltner
In the past two decades, Silicon Valley has come to occupy a position of political, economic, and cultural dominance in the United States. Since 2012, this dominance has resulted in an intense focus on “learning to code”. Corporations, politicians, and educators alike have positioned computer programming as essential for individual job success, the overall economic health of the nation, and the future of work. In particular, teaching “underrepresented minorities” to code is also frequently offered as a solution for the often-problematic gender and racial politics of Silicon Valley corporations. This project examines the power relations of the learn-to-code trend, particularly in terms of race and gender politics. By studying this phenomenon in both theory and practice—and placing it in relevant historical context—this project interrogates the popular belief that mass technological skills training will necessarily make good result in increased equity within Silicon Valley corporations.
Biosensing technologies are increasingly present, predicting bodily or emotional health and offering promises of improved efficiency or personal wellness. Menstrual tracking apps, for example, encourage users to report intimate details, from the duration of periods, cervical mucus texture, emotional state, to sexual behavior. In the best cases, these apps offer period predictions, fertility planning, or pair with IoT devices to monitor the fullness of a tampon, but they also pose risks in the case of a security breach or as practices of sharing health data become more prominent in the workplace. Responding to these concerns over privacy and autonomy, we will conduct a review of existing menstrual biosensing technologies, their data policies, and users’ existing data practices to outline this rapidly shifting field, help users protect their intimate data privacy, and rethink assumptions of how these apps configure their users.
Experts predict that a mega-earthquake is likely to happen in California in the next 30 years. Not everyone is equally prepared for the occurrence of an earthquake. There hasn’t been a deadly (magnitude of 8 or higher) earthquake for many decades, and earthquake drills are offered infrequently and are often not mandatory. ARWave uses augmented reality to show people how an earthquake might affect their personal surroundings. After understanding how devastating an earthquake can be, people will learn the recommended ways of preparing their homes for earthquakes. ARWave will also promote earthquake safety by gamifying the “drop, cover, and hold” protocol, discouraging common, yet risky instincts (such as running) during an earthquake. Through the hyper-realistic and personalized training provided by our phone app, the earthquake-prone cities like Berkeley will become more aware of their vulnerability to earthquakes and will be motivated to take preventative actions.
This project involves developing a reciprocal collaboration between School of Information students and members of the Kashia (Kashaya) and Manchester Bands of the Pomo Indians on digital technology projects that can support the cultural heritage reclamation efforts of tribal members. Rooted in rural Sonoma and Mendocino counties of Northern California, this project will be based in ongoing conversation about community needs. Potential outputs include a mobile language learning application, an AR or VR community and environmental experience, and digitization of archival materials held on the UC Berkeley campus.