Explores AI adoption in the public sector across the United States
This national survey invites public employees to report their use and perception of AI at the work place. It is designed to provide valuable input into the academic and public policy discussions about the use, limitations and security of AI in the public service of the United States. The survey asks about current use patterns, self-assessed productivity changes, limitations, investment, training, and security aspects of the technology. Survey methods, questions, and content are carefully designed following best research practices and are selected solely by the survey team.
The survey is conducted by experienced researchers at Stanford University. The survey team consists of a group of experts on technology and public policy.
Disruptive technologies like artificial intelligence have the potential to transform the workplace. AI may provide access to a personalized assistant, transform backend processes, and automates repetitive tasks. With increasing capabilities, including text, voice, and vision, AI may complement the work of a larger and larger share of the workforce--both in the private and public sector. However, the use of AI does not come without risks. Potential biases, as well as security loopholes of the new technology may not justify the productivity gains for applications in sensitive areas. Furthermore, the emerging technology still has limitations that constrains its use. This survey assesses use patterns, self-assessed productivity changes, limitations and security aspects of the technology.
This survey is conducted among public sector employees across the United States. Approximately, 20% of the workforce work for the public sector in the United States. Thus, incremental changes in productivity enabled through new technology have large economic impacts. Moreover, state and local governments manage large administrative datasets which often contains sensitive information. Thus, the use of AI has to balance productivity increases with potential risks originating from inherent biases or security loopholes of the nascent technology.
Contact us:
aiadoptionsurvey@stanford.edu