| 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 | 1233* | 2021 |
| Art and the science of generative AI Z Epstein, A Hertzmann, Investigators of Human Creativity, M Akten, ... Science 380 (6650), 1110-1111, 2023 | 419* | 2023 |
| Risking your life without a second thought: Intuitive decision-making and extreme altruism DG Rand, ZG Epstein Plos one 9 (10), e109687, 2014 | 235 | 2014 |
| 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 | 191 | 2022 |
| Understanding and Combating Misinformation Across 16 Countries on Six Continents AA Arechar, J Allen, AJ Berinsky, R Cole, Z Epstein, K Garimella, A Gully, ... | 145* | 2023 |
| 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 | 123 | 2020 |
| 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 | 116 | 2021 |
| Who gets credit for ai-generated art? Z Epstein, S Levine, DG Rand, I Rahwan iScience 23 (9), 101515, 2020 | 114* | 2020 |
| Digital literacy is associated with more discerning accuracy judgments but not sharing intentions N Sirlin, Z Epstein, AA Arechar, DG Rand Shorenstein Center for Media, Politics, and Public Policy, 2021 | 93 | 2021 |
| The social media context interferes with truth discernment Z Epstein, N Sirlin, A Arechar, G Pennycook, D Rand Science Advances 9 (9), eabo6169, 2023 | 78 | 2023 |
| 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 | 50 | 2018 |
| 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 | 42 | 2022 |
| 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 | 36 | 2016 |
| 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 | 34 | 2022 |
| Human detection of machine-manipulated media M Groh, Z Epstein, N Obradovich, M Cebrian, I Rahwan Communications of the ACM 64 (10), 40-47, 2021 | 31 | 2021 |
| 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 | 23 | 2016 |
| 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 | 19 | 2018 |
| What label should be applied to content produced by generative AI? Z Epstein, AA Arechar, D Rand PsyArXiv, 2023 | 18 | 2023 |
| How many others have shared this? Experimentally investigating the effects of social cues on engagement, misinformation, and unpredictability on social media Z Epstein, H Lin, G Pennycook, D Rand arXiv preprint arXiv:2207.07562, 2022 | 18 | 2022 |
| Labeling AI-Generated Content: Promises, Perils, and Future Directions C Wittenberg, Z Epstein, AJ Berinsky, DG Rand MIT, 2024 | 16 | 2024 |
David G. RandErwin H. Schell Professor, MIT Sloanmit.edu의 이메일 확인됨
