EPAComp: An Architectural Model for EPA Composition
Luís Henrique Neves Villaça, Sean Wolfgand Matsui Siqueira, et al.
SBSI 2023
Large Language Models (LLMs) have introduced a paradigm shift in interaction with AI technology, enabling knowledge workers to complete tasks by specifying their desired outcome in natural language. LLMs have the potential to increase productivity and reduce tedious tasks in an unprecedented way. A systematic study of LLM adoption for work can provide insight into how LLMs can best support these workers. To explore knowledge workers' current and desired usage of LLMs, we ran a survey (n=216). Workers described tasks they already used LLMs for, like generating code or improving text, but imagined a future with LLMs integrated into their workflows and data. We ran a second survey (n=107) a year later that validated our initial findings and provides insight into up-to-date LLM use by knowledge workers. We discuss implications for adoption and design of generative AI technologies for knowledge work.
Luís Henrique Neves Villaça, Sean Wolfgand Matsui Siqueira, et al.
SBSI 2023
Michael Muller, Anna Kantosalo, et al.
CHI 2024
Ge Gao, Xi Yang, et al.
AAAI 2024
Vittorio Castelli, Lawrence Bergman
IUI 2007