Leveraging Sociotechnical Security and Privacy to Address Online Abuse Miranda Wei University of Washington hosted by Krishna Gummadi , - Kaiserslautern building G26, room Abstract: The prevalence and severity of online abuse are on the rise, from toxic content on social media to image-based sexual abuse, as new technologies are weaponized by people who do harm.
Further, this abuse disproportionately harms people already marginalized in society, creating unacceptable disparities in safety and reinforcing oppression. I conclude by outlining how sociotechnical security and privacy can work towards a world where all people using technology feel safe and connected. Previously, she received a M. Notably, a large part of the promise of autonomous robots depends on long-term operation in domains shared with humans and other agents.
These environments are typically highly complex, semantically rich, and highly dynamic with agents frequently moving through and interacting with the scene.
This talk presents an autonomy pipeline combining perception, prediction, and planning to address these challenges. We first present methods to detect and represent complex semantics, short-term motion, and long-term changes for real-time robot perception in a unified framework called Khronos. We then show how Dynamic Scene Graphs DSGs can represent semantic symbols in a task-driven fashion and facilitate reasoning about the scene, such as the prediction of likely future outcomes based on the data the robot has already collected.
Lastly, we show how robots as embodied agents can leverage these actionable scene representations and predictions to complete tasks such as actively gathering data that helps them improve their world models, perception, and action capabilities fully autonomously over time. The presented methods are demonstrated on-board fully autonomous aerial, legged, and wheeled robots, run in real-time on mobile hardware, and are available as open-source software. Roland Siegwart, where he also obtained his M.
