Publications
Below is a list of publications from our lab. Alternatively, please refer to
Google Scholar
.
Experimental Evidence for Efficiency Gains on Trust via AI-Mediated Communication
Preregistration
Materials
Purcell, Z., Jakesch, M., Dong, M., Nussberger, A. M., & Köbis, N. |
iScience
| 2025
Bias in AI Autocomplete Suggestions Leads to Attitude Shift on Societal Issues
PDF/preprint
Materials
Williams-Ceci, S., Jakesch, M., Bhat, A., Kadoma, K., Zalmanson, L., & Naaman, M. |
Preprint
| 2025
People have different expectations for their own versus others' use of AI-mediated communication tools
Preregistration
Materials
Purcell, Z. A., Dong, M., Nussberger, A. M., Köbis, N., & Jakesch, M. |
British Journal of Psychology
| 2024
AHA!: Facilitating AI Impact Assessment by Generating Examples of Harms
PDF/preprint
Buçinca, Z., Pham, C. M., Jakesch, M., Ribeiro, M. T., Olteanu, A., & Amershi, S. |
arXiv
| 2024
Human Heuristics for AI-Generated Language Are Flawed
Preregistration
Materials
Jakesch, Maurice, Jeffrey T. Hancock, and Mor Naaman |
PNAS 120.11
| 2023
Effects of Algorithmic Trend Promotion: Evidence from Coordinated Campaigns in Twitter's Trending Topics
PDF/preprint
Jospeh Schlessing, Kiran Garimella, Maurice Jakesch, and Dean Eckles |
AAAI ICWSM
| 2023
Comparing Sentence-Level Suggestions to Message-Level Suggestions in AI-Mediated Communication
Liye Fu, Benjamin Newman, Maurice Jakesch, Sarah Kreps |
CHI
| 2023
Co-Writing with Opinionated Language Models Affects Users' Views
PDF/preprint
Maurice Jakesch, Advait Bhat, Daniel Buschek, Lior Zalmanson and Mor Naaman |
ACM CHI
| 2023
Can AI communication tools increase legislative responsiveness and trust in democratic institutions?
Sarah Kreps and Maurice Jakesch |
Government Information Quarterly 40.3: 101829
| 2023
AI Writing Assistants Influence Topic Choice in Self-Presentation
PDF/preprint
Ritika Poddar, Rashmi Sinha, Mor Naaman, Maurice Jakesch |
CHI Extended Abstracts
| 2023
How Different Groups Prioritize Ethical Values for Responsible A.I.
PDF/preprint
Maurice Jakesch, Zana Buçinca, Saleema Amershi and Alexandra Olteanu |
ACM FAccT
| 2022
Belief in partisan news depends on favorable content more than on a trusted source
PDF/preprint
Materials
Maurice Jakesch, Mor Naaman, and Michael Macy |
PsyArXiv
| 2022
Trend Alert: A Cross-Platform Organization Manipulated Twitter Trends in the Indian General Election
PDF/preprint
Maurice Jakesch, Kiran Garimella, Dean Eckles, and Mor Naaman |
ACM CSCW
| 2021
How Partisan Crowds Affect News Evaluation
Materials
Maurice Jakesch, Moran Koren, and Mor Naaman |
ACM TTO
| 2020
The Role of Source, Headline, and Expressive Responding in Political News Evaluation
PDF/preprint
Materials
Maurice Jakesch, Moran Koren, Anna Evtushenko, and Mor Naaman |
Computation + Journalism Symposium
| 2019
AI-Mediated Communication: The Perception That Profile Text Was Written by A.I. Affects Trustworthiness
Materials
Maurice Jakesch, Megan French, Xiao Ma, Jeffrey Hancock, and Mor Naaman |
ACM CHI
| 2019