"For instance, it's possible AI could develop hidden biases. If AI is used for predictive policing algorithms, generating an analysis for when and where crime are most likely to occur, it's possible for results to be skewed by historical crime data from over-policed neighborhoods and marginalized communities."
I really don't understand that concern... So you have either a STT-LLM-TTS or fully native speech model that is instructed to answer calls. When does it generate an analysis? Are you giving the agent some tools to generate the analysis ? Maybe don't.
Also, in general I feel like training some classifier would be slightly better from a humanitary point of view, but I agree that in general reducing the work load of overworked public workers should be a priority of AI application.
I think the fear is that the people in charge may be too gung-ho about AI and go do something like this, rather than saying that LLMs will spontaneously develop some kind of data analytics power.
I really don't understand that concern... So you have either a STT-LLM-TTS or fully native speech model that is instructed to answer calls. When does it generate an analysis? Are you giving the agent some tools to generate the analysis ? Maybe don't.
Also, in general I feel like training some classifier would be slightly better from a humanitary point of view, but I agree that in general reducing the work load of overworked public workers should be a priority of AI application.