Misinformation has been the focus of significant public attention following a spate of volatile civic events including elections and national referendums that surfaced the prevalence of influence operations. The persistence of misinformation on online platforms is a testament to the inadequacy of existing solutions. With the democratization of generative models for text, images, and videos that immediately enter online distribution channels, it is important to develop safer governance mechanisms via policies that draw on lessons learned from practitioners, and from research in social science and machine learning. We provide a platform to discuss and present research in these areas, and encourage members to develop collaborative early-stage research ideas by tapping into the community.
A sample of topics that are of interest to us include:
- Generative Models
- Social Network Analysis
- Fake News
- Hate Speech
- Online Toxicity
- Causal Effects and Interventions
- Natural Language Processing
- Agent-based Models
- Multiagent Systems
- Reinforcement Learning
- Transparency and Ethics
- Recommender Systems
- Algorithmic Auditing
- Psychosocial Analysis
This reading group is a space to introduce beginners to research in these fields. It will provide a platform to continue the conversation with a cross-functional community to foster nuanced discussions on how to address the challenges created by global misinformation through the ethical use of technology and effective governance.
Organizers
The AI, Misinformation, and Policy (AMPol) Seminar is organized by Swapneel Mehta (CDS Ph.D. candidate) and Megan Brown (CSMAP Sr. Research Engineer)
Spring 2023
Date & Title: Friday, March 31, 11:15am
Speaker & Title: Kiran Garimella, “Data donation systems for platform research”
Bio: Kiran Garimella is an Assistant Professor in the School of Communication and Information at Rutgers University. His research deals with using large-scale data to tackle societal issues such as misinformation, political polarization, and hate speech. Prior to joining Rutgers, Dr. Garimella was the Michael Hammer postdoc at the Institute for Data, Systems and Society at MIT and a postdoc at EPFL, Switzerland. His work on studying and mitigating polarization on social media won the best paper awards at top computer science conferences. Kiran received his Ph.D. in computer science at Aalto University, Finland, and Masters & Bachelors from IIIT Hyderabad, India. Prior to his Ph.D., he worked as a Research Engineer at Yahoo Research, Barcelona, and QCRI, Doha.
Abstract: Data donation systems are emerging as a new way to facilitate research on social media platforms, where access to user data can be restricted due to privacy concerns. These systems allow users to voluntarily donate their data for research purposes, providing researchers with valuable insights into user behavior and platform dynamics. In this talk, I will discuss the potential benefits and challenges of data donation systems for platform research. I will explore the different models of data donation systems, including opt-in and opt-out approaches, and examine the ethical considerations involved in such systems. I will also discuss the technical challenges of implementing data donation systems, including data quality control, data security, and data anonymization. Finally, I will highlight some of the recent research studies that have been conducted using data donation systems and the potential impact of such studies on our understanding of social media platforms. Overall, data donation systems have the potential to provide researchers with unprecedented access to user data, while also protecting user privacy and autonomy. However, the design and implementation of such systems must be carefully considered to ensure that they are transparent, ethical, and technically feasible.
Date & Time: Monday, March 6th, 2:30 pm
Speaker & Title: Emily Saltz, Jigsaw. “Using mixed methods to understand the effects of online information interventions: Lessons from UX research in industry”
Recording: View Emily Saltz Lecture Recording (Form to Request Password to Emily Saltz Lecture)
Slides: View Emily Saltz Lecture Slides
Bio: Emily Saltz is a UX Researcher at Google Jigsaw, working on tools for platforms and moderators to address online harms. Before that, she was a UX Researcher at the New York Times R&D Lab, conducting research on topics ranging from media credibility (the News Provenance Project), to NLP Q&A tools. She was a 2020 Fellow at the Partnership on AI, and holds a Master’s in Computer-Interaction from Carnegie Mellon, and a BA in Linguistics from UC Santa Cruz.
Abstract: This talk will provide a glimpse into the experience of studying online harms and information interventions in industry R&D groups such as Google Jigsaw and the New York Times, and how this research is used to inform product decisions deployed at scale. It will also describe the process of working with cross-functional product teams, using in-depth qualitative research alongside larger scale surveys and lab studies to answer questions relevant to both industry and academia, such as user attitudes towards credibility labels across platforms.