Maurice Jakesch
Maurice Jakesch
Assistant Professor @ Bauhaus-University Weimar
Verified email at - Homepage
Cited by
Cited by
AI-Mediated Communication: How the Perception that Profile Text was Written by AI Affects Trustworthiness
M Jakesch, M French, X Ma, JT Hancock, M Naaman
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2019
Co-writing with opinionated language models affects users’ views
M Jakesch, A Bhat, D Buschek, L Zalmanson, M Naaman
Proceedings of the 2023 CHI conference on human factors in computing systems …, 2023
Human heuristics for AI-generated language are flawed
M Jakesch, JT Hancock, M Naaman
Proceedings of the National Academy of Sciences 120 (11), e2208839120, 2023
How different groups prioritize ethical values for responsible AI
M Jakesch, Z Buçinca, S Amershi, A Olteanu
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022
The Role of Source, Headline and Expressive Responding in Political News Evaluation
M Jakesch, M Koren, A Evtushenko, M Naaman
Computation and Journalism Symposium 2019, 2019
Trend alert: A cross-platform organization manipulated Twitter trends in the Indian general election
M Jakesch, K Garimella, D Eckles, M Naaman
Proceedings of the ACM on Human-computer Interaction 5 (CSCW2), 1-19, 2021
Aha!: Facilitating ai impact assessment by generating examples of harms
Z Buçinca, CM Pham, M Jakesch, MT Ribeiro, A Olteanu, S Amershi
arXiv preprint arXiv:2306.03280, 2023
Comparing Sentence-Level Suggestions to Message-Level Suggestions in AI-Mediated Communication
L Fu, B Newman, M Jakesch, S Kreps
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems …, 2023
AI Writing Assistants Influence Topic Choice in Self-Presentation
R Poddar, R Sinha, M Naaman, M Jakesch
Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing …, 2023
Can AI communication tools increase legislative responsiveness and trust in democratic institutions?
S Kreps, M Jakesch
Government Information Quarterly 40 (3), 101829, 2023
Fears about AI-mediated communication are grounded in different expectations for one's own versus others' use
ZA Purcell, M Dong, AM Nussberger, N Köbis, M Jakesch
arXiv preprint arXiv:2305.01670, 2023
Effects of Algorithmic Trend Promotion: Evidence from Coordinated Campaigns in Twitter’s Trending Topics
J Schlessinger, K Garimella, M Jakesch, D Eckles
Proceedings of the International AAAI Conference on Web and Social Media 17 …, 2023
How Partisan Crowds Affect News Evaluation
M Jakesch, M Koren, A Evtushenko, M Naaman
Proceedings of the 2020 Conference for Truth and Trust Online, 2020
Bias in AI Autocomplete Suggestions Leads to Attitude Shift on Societal Issues
S Williams-Ceci, M Jakesch, A Bhat, K Kadoma, L Zalmanson, M Naaman, ...
OSF, 2024
Belief in partisan news depends on favorable content more than on a trusted source
M Jakesch, M Naaman, M Michael
PsyArXiv, 2022
Trust in AI in Under-resourced Environments: Lessons from Local Journalism
MA Le Quéré, M Jakesch
CHI'22 TRAIT: Workshop on Trust and Reliance in AI-Human Teams, 2022
AI-based Text Recommendation's Impact on Profile Writing
R Poddar, R Sinha, M Naaman, M Jakesch
OSF, 2021
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