Writer-Defined AI Personas for On-Demand Feedback Generation

Title data

Benharrak, Karim ; Zindulka, Tim ; Lehmann, Florian ; Heuer, Hendrik ; Buschek, Daniel:
Writer-Defined AI Personas for On-Demand Feedback Generation.
2024
Event: CHI Conference on Human Factors in Computing Systems , 11-16 May 2024 , Honolulu, Hawaii, USA.
(Conference item: Conference , Paper )
DOI: https://doi.org/10.1145/3613904.3642406

Related URLs

Project information

Abstract in another language

Compelling writing is tailored to its audience. This is challenging, as writers may struggle to empathize with readers, get feedback in time, or gain access to the target group. We propose a concept that generates on-demand feedback, based on writer-defined AI personas of any target audience. We explore this concept with a prototype (using GPT-3.5) in two user studies (N=5 and N=11): Writers appreciated the concept and strategically used personas for getting different perspectives. The feedback was seen as helpful and inspired revisions of text and personas, although it was often verbose and unspecific. We discuss the impact of on-demand feedback, the limited representativity of contemporary AI systems, and further ideas for defining AI personas. This work contributes to the vision of supporting writers with AI by expanding the socio-technical perspective in AI tool design: To empower creators, we also need to keep in mind their relationship to an audience.