TY - GEN
T1 - Incorporating Citizen-Generated Data into Large Language Models
AU - Vadapalli, Jagadeesh
AU - Gupta, Srishti
AU - Karki, Bishwa
AU - Tsai, Chun Hua
N1 - Publisher Copyright:
© 2024 Copyright held by the owner/author(s).
PY - 2024/6/11
Y1 - 2024/6/11
N2 - This study investigates the use of citizen-generated data to optimize a large language model (LLM) chatbot that gives nutrition advice. By actively participating in the data collection and annotation process from FDA-approved websites, citizens provided insightful information that was essential for improving the model and addressing biases. The study highlights the difficulties in gathering and annotating data, especially in situations where nuances matter, such as pregnancy nutrition. The results show that the use of citizen-generated data improves the efficacy and efficiency of data collection procedures, providing a practical viewpoint and encouraging community involvement. In addition to guaranteeing data quality, the iterative process raises stakeholders’ awareness of and proficiency with data. Thus, citizen-generated data becomes an essential tool for creating information systems that are more reliable and inclusive.
AB - This study investigates the use of citizen-generated data to optimize a large language model (LLM) chatbot that gives nutrition advice. By actively participating in the data collection and annotation process from FDA-approved websites, citizens provided insightful information that was essential for improving the model and addressing biases. The study highlights the difficulties in gathering and annotating data, especially in situations where nuances matter, such as pregnancy nutrition. The results show that the use of citizen-generated data improves the efficacy and efficiency of data collection procedures, providing a practical viewpoint and encouraging community involvement. In addition to guaranteeing data quality, the iterative process raises stakeholders’ awareness of and proficiency with data. Thus, citizen-generated data becomes an essential tool for creating information systems that are more reliable and inclusive.
UR - http://www.scopus.com/inward/record.url?scp=85195271051&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85195271051&partnerID=8YFLogxK
U2 - 10.1145/3657054.3659119
DO - 10.1145/3657054.3659119
M3 - Conference contribution
AN - SCOPUS:85195271051
T3 - ACM International Conference Proceeding Series
SP - 1023
EP - 1025
BT - Proceedings of the 25th Annual International Conference on Digital Government Research, DGO 2024
A2 - Liao, Hsin-Chung
A2 - Cid, David Duenas
A2 - Macadar, Marie Anne
A2 - Bernardini, Flavia
PB - Association for Computing Machinery
T2 - 25th Annual International Conference on Digital Government Research, DGO 2024
Y2 - 11 June 2024 through 14 June 2024
ER -