Nevada will soon become the first state to use AI to help speed up the decision-making process when ruling on appeals that impact people's unemployment benefits.
The state's Department of Employment, Training, and Rehabilitation (DETR) agreed to pay Google $1,383,838 for the AI technology, a 2024 budget document shows, and it will be launched within the "next several months," Nevada officials told Gizmodo.
Nevada's first-of-its-kind AI will rely on a Google cloud service called Vertex AI Studio. Connecting to Google's servers, the state will fine-tune the AI system to only reference information from DETR's database, which officials think will ensure its decisions are "more tailored" and the system provides "more accurate results," Gizmodo reported.
Under the contract, DETR will essentially transfer data from transcripts of unemployment appeals hearings and rulings, after which Google's AI system will process that data, upload it to the cloud, and then compare the information to previous cases.
In as little as five minutes, the AI will issue a ruling that would've taken a state employee about three hours to reach without using AI, DETR's information technology administrator, Carl Stanfield, told The Nevada Independent. That's highly valuable to Nevada, which has a backlog of more than 40,000 appeals stemming from a pandemic-related spike in unemployment claims while dealing with "unforeseen staffing shortages" that DETR reported in July.
"The time saving is pretty phenomenal," Stanfield said.
As a safeguard, the AI's determination is then reviewed by a state employee to hopefully catch any mistakes, biases, or perhaps worse, hallucinations where the AI could possibly make up facts that could impact the outcome of their case.
Google's spokesperson Ashley Simms told Gizmodo that the tech giant will work with the state to "identify and address any potential bias" and to "help them comply with federal and state requirements.” According to the state's AI guidelines, the agency must prioritize ethical use of the AI system, "avoiding biases and ensuring fairness and transparency in decision-making processes."