| Encounters with visual misinformation and labels across platforms: An interview and diary study to inform ecosystem approaches to misinformation interventions E Saltz, CR Leibowicz, C Wardle Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing …, 2021 | 76 | 2021 |
| Building human values into recommender systems: An interdisciplinary synthesis J Stray, A Halevy, P Assar, D Hadfield-Menell, C Boutilier, A Ashar, ... ACM Transactions on Recommender Systems 2 (3), 1-57, 2024 | 72 | 2024 |
| Misinformation interventions are common, divisive, and poorly understood E Saltz, S Barari, C Leibowicz, C Wardle Harvard Kennedy School (HKS) Misinformation Review 2 (5), 2021 | 39 | 2021 |
| The deepfake detection dilemma: A multistakeholder exploration of adversarial dynamics in synthetic media CR Leibowicz, S McGregor, A Ovadya Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 736-744, 2021 | 28 | 2021 |
| When is it appropriate to publish high-stakes AI research C Leibowicz, S Adler, P Eckersley Partnership on AI blog post, 2019 | 11 | 2019 |
| It matters how platforms label manipulated media. Here are 12 principles designers should follow E Saltz, T Shane, V Kwan, C Leibowicz, C Wardle The Partnership on AI, 2020 | 7 | 2020 |
| Personhood credentials: Artificial intelligence and the value of privacy-preserving tools to distinguish who is real online S Adler, Z Hitzig, S Jain, C Brewer, W Chang, R DiResta, E Lazzarin, ... arXiv preprint arXiv:2408.07892, 2024 | 6 | 2024 |
| Creating ai art responsibly: A field guide for artists C Leibowicz, E Saltz, L Coleman Diseña, 5-5, 2021 | 5 | 2021 |
| Misinformation interventions are common, divisive, and poorly understood. Harvard Kennedy School Misinformation Review (Oct. 2021) E Saltz, S Barari, C Leibowicz, C Wardle | 5 | 2021 |
| Making AI Art Responsibly: A Field Guide E Saltz, L Coleman, C Leibowicz Partnership on AI 16, 2020 | 5 | 2020 |
| Student privacy: The next frontier-emerging & future privacy issues in K-12 learning environments PL Haduong, ZE Wood, SC Cortesi, LA Plunkett, DT Ritvo, U Gasser Berkman Center Research Publication Series, 2015 | 4 | 2015 |
| From deepfakes to TikTok filters: How do you label AI content? T Shane, E Saltz, C Leibowicz Nieman Lab, May 12, 2021 | 2 | 2021 |
| Manipulated Media Detection Requires More Than Tools: Community Insights on What’s Needed C Leibowicz, J Stray, E Saltz Partnership on AI, blog post, July 13, 2020 | 2 | 2020 |
| Urgent Considerations for the Automated Categorization of Manipulated Media E Saltz, P Noel, C Leibowicz, C Wardle, S Gregory | 2 | 5 |
| From Principles to Practices: Lessons Learned from Applying Partnership on AI's (PAI) Synthetic Media Framework to 11 Use Cases CR Leibowicz, CH Cardona arXiv preprint arXiv:2407.13025, 2024 | 1 | 2024 |
| Who Supports Online Misinformation Interventions? S Barari, E Saltz, C Leibowicz OSF, 2021 | 1 | 2021 |
| Regulating Reality: Exploring Synthetic Media Through Multistakeholder AI Governance CR Leibowicz arXiv preprint arXiv:2502.04526, 2025 | | 2025 |
| Recommender Systems HA Rahmani, M Naghiaei, Y Deldjoo, J Stray, A Halevy, P Assar, ... ACM Transactions on 2 (3), 2024 | | 2024 |
| Building Human Values into Recommender Systems: An Interdisciplinary Synthesis and Open Problems J Stray, A Halevy, P Assar, D Hadfield-menell, C Boutilier, A Ashar, ... | | 2023 |