📝 SummarXiv

Abstract

Generic AI auto-complete for message composition often fails to capture the nuance of personal identity, requiring significant editing. While harmless in low-stakes settings, for users of Augmentative and Alternative Communication (AAC) devices, who rely on such systems for everyday communication, this editing burden is particularly acute. Intuitively, the need for edits would be lower if language models were personalized to the communication of the specific user. While technically feasible, such personalization raises socio-technical questions: what are the implications of logging one's own conversations, and how does personalization affect privacy, authorship, and control? We explore these questions through an autoethnographic study in three phases: (1) seven months of collecting all the lead author's AAC communication data, (2) fine-tuning a model on this dataset, and (3) three months of daily use of personalized AI suggestions. We reflect on these phases through continuous diary entries and interaction logs. Our findings highlight the value of personalization as well as implications on privacy, authorship, and blurring the boundaries of self-expression.