Mor Naaman
ABSTRACT
From autocomplete and smart replies to video filters and deepfakes, we increasingly live in a world where communication between humans is augmented by artificial intelligence. AI often operates on behalf of a human communicator by recommending, suggesting, modifying, or generating messages to accomplish communication goals. We call this phenomenon AI-Mediated Communication (or AI-MC) [1, 4]. While AI-MC has the potential of making human communication more efficient, it impacts other aspects of our communication in ways that are not yet well understood. Over the last three years, my collaborators and I have been documenting the impact of AI-MC on communication outcomes, language use, interpersonal trust, and more. The talk will outline early experimental findings from this work, mostly led by Cornell and Stanford graduate students Maurice Jakesch, Hannah Mieczkowski, and Jess Hohenstein. For example, the research shows that AI-MC involvement can result in language shifting towards positivity [2, 7]; impact the evaluation of others [2, 4]; change the extent to which we take ownership over our messages [6]; and shift assignment of blame for communication outcomes [3]. Given the impact of AI-MC on interpersonal evaluations, the talk will also cover our recent research examining the (mostly false) heuristics humans use when evaluating whether text was written by AI [5]. Overall, AI-MC raises significant practical and ethical concerns as it stands to reshape human communication, calling for new approaches to the development and regulation of these technologies.
- Jeffrey T Hancock, Mor Naaman, and Karen Levy. 2020. AI-mediated communication: Definition, research agenda, and ethical considerations. Journal of Computer-Mediated Communication 25, 1 (2020), 89–100.Google Scholar
Cross Ref
- Jess Hohenstein, Dominic DiFranzo, Rene F. Kizilcec, Zhila Aghajari, Hannah Mieczkowski, Karen Levy, Mor Naaman, Jeff Hancock, and Malte Jung. 2021. Artificial intelligence in communication impacts language and social relationships. https://arxiv.org/abs/2102.05756.Google Scholar
- Jess Hohenstein and Malte Jung. 2020. AI as a Moral Crumple Zone: The Effects of AI-Mediated Communication on Attribution and Trust. Comput. Hum. Behav. 106, C (may 2020), 13 pages. https://doi.org/10.1016/j.chb.2019.106190Google ScholarDigital Library
- Maurice Jakesch, Megan French, Xiao Ma, Jeffrey T. Hancock, and Mor Naaman. 2019. AI-Mediated Communication: How the Perception That Profile Text Was Written by AI Affects Trustworthiness. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI ’19). Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3290605.3300469Google ScholarDigital Library
- Maurice Jakesch, Jeffrey Hancock, and Mor Naaman. 2022. Human Heuristics for AI-Generated Language Are Flawed. https://arxiv.org/abs/2206.07271.Google Scholar
- Hannah Mieczkowski and Jeffrey Hancock. 2022. Examining Agency, Expertise, and Roles of AI Systems in AI-Mediated Communication. https://osf.io/asnv4.Google Scholar
- Hannah Mieczkowski, Jeffrey T Hancock, Mor Naaman, Malte Jung, and Jess Hohenstein. 2021. AI-Mediated Communication: Language Use and Interpersonal Effects in a Referential Communication Task. Proceedings of the ACM on Human-Computer Interaction 5, CSCW1(2021), 1–14.Google ScholarDigital Library
Index Terms
- “My AI must have been broken”: How AI Stands to Reshape Human Communication
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