The Nevada Department of Employment has revealed that it will use Artificial Intelligence to help speed up its unemployment appeals process by analyzing appeal hearing transcripts and issuing a recommendation decision.
The department said it has been “buried” in a backlog of claims since the start of the pandemic and is desperately looking for ways to get back on track.
It has also confirmed that it will not be training a new generative AI model for the system, but will instead use Google's Vertex AI studio, which will reportedly reduce the review process from hours to just five minutes, despite new research suggesting that AI models in general are Worse than humans in 'every way' when summarizing documents and often create additional work for workers.
Clearing the backlog
Experts have warned against this approach, not only because large language models do not understand text or reason logically and within context the way humans do, but also because it may not save the department much time.
“If someone reviews something thoroughly and appropriately, they're not actually saving a lot of time,” said Morgan Shah, Director of Community Engagement for Nevada Legal Services. “At what point are you creating an environment where people are encouraged to cut corners?”
The model's lack of accuracy is a concern for attorneys at Nevada Legal Services, who cite AI “hallucinations,” an industry term used to describe when an AI model produces factually incorrect or misleading answers, as a concern.
Any AI decision will also be double-checked and reviewed by a human arbitrator before being issued, but if the human arbitrator makes a decision based on the AI's hallucination, a court may not be able to overturn the decision.
The famous IBM quote comes to mind: “A computer can never be held responsible, therefore it should never make a management decision.” Research has shown that many of us are We are still very cautious about AIespecially in high-risk products (such as medical diagnostics and automated vehicles). The success of this experiment could have an impact on a wide range of government departments in the future.
Through Gizmodo
