Writer-Defined AI Personas for On-Demand Feedback Generation
September 19, 2023 Β· Declared Dead Β· π International Conference on Human Factors in Computing Systems
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Authors
Karim Benharrak, Tim Zindulka, Florian Lehmann, Hendrik Heuer, Daniel Buschek
arXiv ID
2309.10433
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CL
Citations
62
Venue
International Conference on Human Factors in Computing Systems
Last Checked
3 months ago
Abstract
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.
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