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Factors Affecting Trust Among Vulnerable Populations

Rajasi Desai, Graduate Student Researcher, School of Information, UC Berkeley
Varshine Chandrakanthan, Graduate Student Researcher, School of Information, UC Berkeley
This project aims to understand the trust dynamics and the factors affecting trust for vulnerable populations like human rights defenders, activists, and journalists who document and upload sensitive media, as well as people who receive this media in order to use it as evidence. The researchers will work to understand...

Crafting Public Policy for Reinforcement Learning Applications

Thomas Gilbert, PhD Candidate, Sociology, UC Berkeley
Sarah Dean, PhD Student, Department of Electrical Engineering and Computer Sciences, UC Berkeley
Tom Zick, PhD Candidate, College of Letters & Science, UC Berkeley
McKane Andrus, Graduate Student Researcher, Berkeley Artificial Intelligence Research, UC Berkeley
A team of graduate students, Graduates for Engaged and Extended Scholarship around computing and Engineering (GEESE), will build on their prior CLTC-funded project and develop suggested interventions in the design, training, and deployment of reinforcement learning (RL) systems that can be integrated into social infrastructure. These deliverables will include a...

Coordinated Entry System Research and Development for Alameda County’s Continuum of Care

Zoe Kahn, PhD Student, School of Information, UC Berkeley
Mahmoud Hamsho, Researcher, Center for Long-Term Cybersecurity, UC Berkeley
Amy Turner, Graduate Student Researcher, School of Information, UC Berkeley
Yuval Barash, Graduate Student Researcher, School of Information, UC Berkeley
Michelle Chen, Graduate Student Researcher, School of Information, UC Berkeley
Governments are increasingly using technology to allocate scarce social service resources, like housing services. In collaboration with Alameda County’s Continuum of Care, this project will use qualitative research methods (i.e. interviews, participatory design, and usability testing) to conduct a needs assessment and system recommendation around “matching” unhoused people to appropriate...

Re-imagining Password Management for Low-Technology Proficiency Users

Ching-Yi Lin, Graduate Student Researcher, School of Information, UC Berkeley
Ayo Animashaun, Graduate Student Researcher, School of Information, UC Berkeley
Jing Wu, Graduate Student Researcher, School of Information, UC Berkeley
Amy Huang, Graduate Student Researcher, School of Information, UC Berkeley
Passwords and login information control access to some of the most important aspects of life, such as banking and finances, medical services, and other sensitive personal information. According to Pew Research, 44% of online adults ages 30 to 64 say they have a hard time keeping track of their passwords....

Examining The Third-Party Tracking Ecosystem

Serge Egelman, Research Director, International Computer Science Institute, UC Berkeley
Primal Wijesekera, Postdoctoral Researcher, International Computer Science Institute, UC Berkeley
Ahmad Bashir, Postdoctoral Researcher, International Computer Science Institute, UC Berkeley
Many mobile apps and online services use “third-party trackers,” which send data about specific user behaviors to various other companies. The purposes of these transmissions can include profiling individual users to target them with specific ads, amassing personal information to sell to data brokers, or monitoring activities to identify how...

Engaging Expert Stakeholders about the Future of Menstrual Biosensing Technology

Noura Howell, PhD Candidate, School of Information, UC Berkeley
Richmond Wong, PhD Candidate, School of Information, UC Berkeley
Sarah Fox, Postdoctoral Scholar, Department of Communication and The Design Lab, UC San Diego
Franchesca Spektor, Undergraduate Student Researcher, UC Berkeley
Networked sensor technologies are increasingly present in daily life. While promising improved health and efficiency, they also introduce far-reaching issues around cybersecurity, privacy, autonomy, and consent that can be difficult to predict or resist. This project will examine menstrual tracking technologies as a case for understanding the current and near-future...

A Cryptographic Study of Data Protection Laws

Prashant Vasudevan, Postdoctoral Researcher, Department of Electrical Engineering and Computer Science, UC Berkeley
We live in the age of data—every day, data is collected about us by websites we visit, devices we wear, etc.; and this data has effects on various aspects of our life, from shopping recommendations to credit scores. Consequently, laws that seek to regulate the processing of individuals’ personal data...

Towards Efficient Data Economics: Decentralized Data Marketplace and Smart Pricing Models

Dawn Song, Professor, Department of Electrical Engineering and Computer Science, UC Berkeley
Ruoxi Jia, Postdoctoral Researcher, Department of Electrical Engineering and Computer Science, UC Berkeley
Advances in machine learning and artificial intelligence have demonstrated enormous potential for building intelligent systems and growing knowledge bases. However, the current data marketplaces are not efficient enough to facilitate long-term technological and economic advancements. An efficient data market would allow participants to strategically sell or purchase data and get...

The Cybersecurity of “Smart Infrastructure”

Alison Post, Associate Professor, Department of Political Science and Global Metropolitan Studies, UC Berkeley
Karen Trapenberg Frick, Associate Professor, College for Environmental Design, UC Berkeley
Kenichi Soga, Chancellor's Professor, Civil and Environmental Engineering, UC Berkeley
Marti Hearst, Professor, School of Information, UC Berkeley
Urban infrastructure, such as water and sanitation systems, subways, power grids, and flood defense systems, are crucial for social and economic life, yet are vulnerable to natural hazards that could disrupt services, such as earthquakes or floods. New sensor systems can potentially provide early warnings of problems, and thus help...

Detecting Images Generated by Neural Networks

Alexei Efros, Associate Professor, Department of Electrical Engineering and Computer Science
Recent years have seen great advances in computer vision and machine learning. But with these advances comes an ethical dilemma: as our methods get better, so do the tools for malicious image manipulation. While these malicious uses were once only the domain of well-resourced dictators, spy agencies, and unscrupulous photojournalists,...
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