Register here to attend in person. Co-sponsored by the Department of Computer Science and the Department of Electrical and Computer Engineering The Arbitrum blockchain protocol started as a Princeton University research project, and has grown into a robust community hosting hundred of applications and over 600,000 monthly users. Along the way, the system has evolved through at least three generations to meet the needs of developers and users. This talk will provide a technical description of how Arbitrum works, as an example of a modern blockchain protocol, along with a perspective on the history and future of blockchain technology. Bio: Ed Felten is the co-founder and chief scientist at Offchain Labs, Inc. He is the Robert E. Kahn Professor Emeritus of Computer Science and Public Affairs and the Founding Director of the Center for Information Technology Policy. Felten officially retired from Princeton University and transferred to emeritus status on July 1, 2021 after 28 years on the
CITP Distinguished Lecture Series: Alessandro Acquisti – Who Benefits from the Data Economy? Please register here to attend in person. In collaboration with the Department of Computer Science and the Department of Electrical and Computer Engineering In the public debate around privacy and the data economy, several claims have been made concerning the benefits that multiple stakeholders may accrue from the collection and analysis of consumer data. How many of those claims are empirically validated by independent research? We will review prior work and present a series of ongoing studies that aim at understanding and estimating how the economic value extracted from consumer data is being allocated to different stakeholders, and the way privacy protection may influence those allocations. Bio: Alessandro Acquisti is the Trustees Professor of Information Technology and Public Policy at the Heinz College, Carnegie Mellon University. He is an Andrew Carnegie Fellow (inaugural class), the d
Does conversation online often lead to deeper understanding of important issues? In this talk, research will be presented in the School of Interactive Computing at Georgia Tech about understanding and supporting online discussion of difficult issues. In the first study, we interviewed people who had disagreements with others on Facebook. We find that conflict often results not from disagreement but from violation of expectations. Design recommendations for social media platforms will be presented that could help mitigate disagreements, and ideas to help people have productive, hard conversations. In the second study, we interviewed people who discuss guns and gun policy on Reddit, from both a pro- and anti- gun perspective. We find that members of pro- and anti- gun groups rarely interact. However, many people who post to highly partisan groups admit to actually holding more moderate views on some issues. Unfortunately, they would not feel comfortable posting about moderate views for
CITP Distinguished Lecture Series: Thomas Ristenpart – Mitigating Technology Abuse in Intimate Partner Violence and Encrypted Messaging Please register here to attend in person. In collaboration with the Department of Computer Science and the Department of Electrical and Computer Engineering Computer security is traditionally about the protection of technology, whereas trust and safety efforts focus on preventing technology abuse from harming people. In this talk, we’ll explore the interplay between security and tech abuse, and make the case that trust and safety represents an important frontier for computer security researchers. To do so, we will draw on examples from two lines of my recent work. First, an overview our work on technology abuse in the context of intimate partner violence (IPV) will be presented. IPV is a widespread social ill affecting about one in four women and one in ten men at some point in their lives. Via interviews with survivors and professionals, online
Please register here to attend in person. In collaboration with the Department of Computer Science and the Department of Electrical and Computer Engineering Online platforms have a wealth of data, run countless experiments and use industrial-scale algorithms to optimize user experience. Despite this, many users seem to regret the time they spend on these platforms. One possible explanation is that incentives are misaligned: platforms are not optimizing for user happiness. We suggest the problem runs deeper, transcending the specific incentives of any particular platform, and instead stems from a mistaken foundational assumption. To understand what users want, platforms look at what users do. This is a kind of revealed-preference assumption that is ubiquitous in user models. Yet research has demonstrated, and personal experience affirms, that we often make choices in the moment that are inconsistent with what we actually want: we can choose mindlessly or myopically, behaviors that feel