| Shifting attention to accuracy can reduce misinformation online G Pennycook, Z Epstein, M Mosleh, AA Arechar, D Eckles, DG Rand Nature 592 (7855), 590-595, 2021 | 361* | 2021 |
| Risking your life without a second thought: Intuitive decision-making and extreme altruism DG Rand, ZG Epstein PloS one 9 (10), e109687, 2014 | 180 | 2014 |
| Will the crowd game the algorithm? Using layperson judgments to combat misinformation on social media by downranking distrusted sources Z Epstein, G Pennycook, D Rand Proceedings of the 2020 CHI conference on human factors in computing systems …, 2020 | 51* | 2020 |
| Closing the AI Knowledge Gap Z Epstein, BH Payne, J Shen, A Dubey, B Felbo, M Groh, N Obradovich, ... arXiv preprint arXiv:1803.07233, 2018 | 31 | 2018 |
| Developing an accuracy-prompt toolkit to reduce COVID-19 misinformation online Z Epstein, AJ Berinsky, R Cole, A Gully, G Pennycook, DG Rand Shorenstein Center for Media, Politics, and Public Policy, 2021 | 24 | 2021 |
| Using clinical data to predict high-cost performance coding issues associated with pressure ulcers: a multilevel cohort model WV Padula, RD Gibbons, PJ Pronovost, D Hedeker, MK Mishra, ... Journal of the American Medical Informatics Association 24 (e1), e95-e102, 2016 | 24 | 2016 |
| Who gets credit for ai-generated art? Z Epstein, S Levine, DG Rand, I Rahwan Iscience 23 (9), 101515, 2020 | 22* | 2020 |
| The good, the bad, and the unflinchingly selfish: Cooperative decision-making can be predicted with high accuracy when using only three behavioral types Z Epstein, A Peysakhovich, DG Rand Proceedings of the 2016 ACM Conference on Economics and Computation, 547-559, 2016 | 19 | 2016 |
| Deepfake detection by human crowds, machines, and machine-informed crowds M Groh, Z Epstein, C Firestone, R Picard Proceedings of the National Academy of Sciences 119 (1), e2110013119, 2022 | 17* | 2022 |
| Human detection of machine manipulated media M Groh, Z Epstein, N Obradovich, M Cebrian, I Rahwan arXiv preprint arXiv:1907.05276, 2019 | 11 | 2019 |
| TuringBox: An experimental platform for the evaluation of AI systems Z Epstein, BH Payne, JH Shen, CJ Hong, B Felbo, A Dubey, M Groh, ... IJCAI 2018, 5826-5828, 2018 | 11 | 2018 |
| Interpolating GANs to scaffold autotelic creativity Z Epstein, O Boulais, S Gordon, M Groh International Conference on Computation Creativity, 2020 | 6 | 2020 |
| Understanding and reducing online misinformation across 16 countries on six continents AA Arechar, JNL Allen, R Cole, Z Epstein, K Garimella, A Gully, JG Lu, ... PsyArXiv, 2022 | 4 | 2022 |
| Towards a new social laboratory: an experimental study of search through community participation at burning man Z Epstein, M Epstein, C Almenar, M Groh, N Pescetelli, E Moro, ... arXiv preprint arXiv:1903.04125, 2019 | 2 | 2019 |
| Using Machine Learning To Populate A Markov Model By Mining Big Data Directly From Hospital Ehrs–An Application To Dynamically Predict Hospital-Acquired Pressure Ulcers W Padula, MB Makic, Z Epstein, J Gemmell, MK Mishra, D Meltzer Value in Health 18 (7), A694, 2015 | 2 | 2015 |
| Digital literacy is associated with more discerning accuracy judgments but not sharing intentions N Sirlin, Z Epstein, AA Arechar, DG Rand Harvard Kennedy School Misinformation Review, 2021 | 1 | 2021 |
| Social media sharing reduces truth discernment Z Epstein, N Sirlin, AA Arechar, G Pennycook, D Rand PsyArXiv, 2021 | 1* | 2021 |
| Co-creation and ownership for AI radio S Gordon, R Mahari, M Mishra, Z Epstein arXiv preprint arXiv:2206.00485, 2022 | | 2022 |
| When happy accidents spark creativity: Bringing collaborative speculation to life with generative AI Z Epstein, H Schroeder, D Newman arXiv preprint arXiv:2206.00533, 2022 | | 2022 |
| Do explanations increase the effectiveness of AI-crowd generated fake news warnings? Z Epstein, N Foppiani, S Hilgard, S Sharma, E Glassman, D Rand Proceedings of the International AAAI Conference on Web and Social Media 16 …, 2022 | | 2022 |
David G. RandErwin H. Schell Professor, Massachusetts Institute of TechnologyVerified email at mit.edu
