
Abstract While AI technologies and tools offer various potential benefits to their users, it is not clear whether opportunities to access these benefits are equally accessible to all. We examine this gap between availability and accessibility as it relates to the adoption of AI-Mediated Communication (AI-MC) tools, which enable interpersonal communication where an intelligent agent operates on behalf of a communicator. Upon defining six functional AI-MC types (voice-assisted communication, language correction, predictive text suggestion, transcription, translation, personalized language learning) we conducted an online survey of 519 U.S. participants that combined closed- and open-ended measures. Our quantitative results revealed how AI-MC adoption is related to software, device, and internet access for tools such as voice-assisted communication; demographic factors such as age, education and income in the case of translation and transcription tools; and some components of AI-MC literacy for specific functional tools. Our qualitative analyses provide additional nuance for these findings, and we articulate a number of barriers to access, understanding, and usage of AI-MC tools, which we suggest hinder AI-MC accessibility for user groups traditionally disadvantaged by one-size-fits-all technological tools. We end with a call for broadly addressing accessibility concerns within the digital technology industry.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 51 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
