By  Elizabeth Laird – Public agencies have significant incentives to adopt artificial intelligence (AI) in their delivery of services and benefits, particularly amid recent advancements in generative AI. In fact, public agencies have already been using AI for years in use cases ranging from chatbots that help constituents navigate agency websites to fraud detection in benefit applications. Agencies’ resource constraints, as well as their desire to innovate, increase efficiency, and improve the quality of their services, all make AI and the potential benefits it often offers — automation of repetitive tasks, analysis of large swaths of data, and more — an attractive area to invest in.

However, using AI to solve any problem or for any other agency use case should not be a foregone conclusion. There are limitations both to AI’s capabilities generally and to it being a logical fit for a given situation. Thus, agencies should engage in an explicit decision-making process before developing or procuring AI systems to determine whether AI is a viable option to solve a given problem and a stronger solution than non-AI alternatives. The agency should then repeatedly reevaluate its decision-making throughout the AI development lifecycle if it decides initially to proceed with an AI system. Vetting the use of AI is critical because inappropriate use of AI in government service and benefit delivery can undermine individuals’ rights and safety and waste resources.

Despite the emergence of new frameworks, guidance, and recommendations to support the overall responsible use of AI by public agencies, there is a dearth of guidance on how to decide whether AI should be used in the first place, including how to compare it to other solutions and how to document and communicate that decision-making process to the public. This brief seeks to address this gap by proposing a four-step framework that public administrators can use to help them determine whether to proceed with an AI system for a particular use case:  Read On: