Artificial Intelligence in Public Governance: Chatbot Applications in State Governments
Presenter Type
UNO Graduate Student (Doctoral)
Major/Field of Study
Public Administration
Advisor Information
Yu-Che Chen
Location
MBSC302 - G (Doctoral)
Presentation Type
Oral Presentation
Start Date
24-3-2023 10:30 AM
End Date
24-3-2023 11:45 AM
Abstract
Artificial intelligence (AI) systems have been applied to address various social issues in recent decades. Governments use AI to integrate different data sources and datasets, identify patterns or detect irregularities in big data, and even generate prediction and policy estimations. One emerging application is the conservational chatbots for answering citizens’ questions. The government uses chatbots to interact with citizens, understand social demands, and build trust between citizens and public organizations. However, the existing research can rarely present how the government adopts chatbots in public service delivery and explains why public institutions use chatbots in their work. Hence, this study proposes two research questions: (1) what are the implemented functions of chatbots in interacting with citizens? (2) what are the affecting factors of chatbot applications in state governments? This study integrates policy innovation theory and digital transformation theory to develop a conceptual framework and use empirical data to answer the research questions. Policy innovation theory discusses why governments adopt new policies, while digital transformation theory illustrates how technologies can change organizational cultures, structures, and interactions with other actors in public governance. The conceptual framework hypothesizes that IT capacity, state population, and broadband internet coverage can associate with chatbot adoptions. This study reviewed the chatbot applications in state governments and conducted t-tests to explore the research hypotheses. The results indicate that the 33 state governments use at least one chatbot, and there are 40 chatbots in total. Among the 33 state governments, 22 of them use a chatbot for specific purposes, including COVID-19, unemployment, and emergency management issues. The five governments adopt chatbots as the one-stop platform to answer citizens’ questions or guide them to responsible government agencies. Also, the six states adopt both types of AI-enabled chatbots. On the other hand, all chatbots provide question-answering services, while 38 chatbots can help citizens get access to documents or websites. No chatbots can route, complete, and translate documents or applications for citizens. However, this study finds that 11 chatbots can use multiple languages to serve citizens. Finally, the results demonstrate that IT capacity and state population affect chatbot applications. This study suggests that governments can include more chatbot functions to serve various social demands, keep investing in IT-related capacities, and improve chatbot performances.
Scheduling
10:45 a.m.-Noon
Artificial Intelligence in Public Governance: Chatbot Applications in State Governments
MBSC302 - G (Doctoral)
Artificial intelligence (AI) systems have been applied to address various social issues in recent decades. Governments use AI to integrate different data sources and datasets, identify patterns or detect irregularities in big data, and even generate prediction and policy estimations. One emerging application is the conservational chatbots for answering citizens’ questions. The government uses chatbots to interact with citizens, understand social demands, and build trust between citizens and public organizations. However, the existing research can rarely present how the government adopts chatbots in public service delivery and explains why public institutions use chatbots in their work. Hence, this study proposes two research questions: (1) what are the implemented functions of chatbots in interacting with citizens? (2) what are the affecting factors of chatbot applications in state governments? This study integrates policy innovation theory and digital transformation theory to develop a conceptual framework and use empirical data to answer the research questions. Policy innovation theory discusses why governments adopt new policies, while digital transformation theory illustrates how technologies can change organizational cultures, structures, and interactions with other actors in public governance. The conceptual framework hypothesizes that IT capacity, state population, and broadband internet coverage can associate with chatbot adoptions. This study reviewed the chatbot applications in state governments and conducted t-tests to explore the research hypotheses. The results indicate that the 33 state governments use at least one chatbot, and there are 40 chatbots in total. Among the 33 state governments, 22 of them use a chatbot for specific purposes, including COVID-19, unemployment, and emergency management issues. The five governments adopt chatbots as the one-stop platform to answer citizens’ questions or guide them to responsible government agencies. Also, the six states adopt both types of AI-enabled chatbots. On the other hand, all chatbots provide question-answering services, while 38 chatbots can help citizens get access to documents or websites. No chatbots can route, complete, and translate documents or applications for citizens. However, this study finds that 11 chatbots can use multiple languages to serve citizens. Finally, the results demonstrate that IT capacity and state population affect chatbot applications. This study suggests that governments can include more chatbot functions to serve various social demands, keep investing in IT-related capacities, and improve chatbot performances.