We implement AutoBot, across three downstream applications targeting different web stakeholders: (1) a local browser extension providing users with real-time feedback, (2) a Lighthouse audit to inform developers of potential deceptive patterns on their sites, and (3) as a measurement tool designed for researchers and regulators.

This paper systematically explores the potential of automation apps to be used for surveillance and harassment in IPV scenarios.

This Emerging Ideas report explores families’ (parents and their children) uses and gratification for ChatGPT.

We conducted user studies (N=21) and found that participants were unaware to both what the models output and when the models were used in Instagram and TikTok, two major social media platforms. In response to being exposed to the models’ functionality, we observed long term behavior changes in 8 participants. Our analysis uncovers the challenges and opportunities in providing transparency for machine learning models that interact with local user data.

In this work, we compare the currently deployed models for both Instagram and TikTok to their public statements about internal AI governance practices to see if these models live up to their reported standards. We found that Instagram’s model may exhibit undesirable biases in concepts that their other internal models (eg, DINOv2) may lack.