How does the merit staffing consideration apply to questions about AI/tech adoption?
e.g. if I am the SNAP Director in Nevada, and I recognize that eligibility interviews are not required by statute, but I also am very concerned about the impact on improper payments should we remove it -- I might see an automated/AI "interview" as a viable way to reduce workload while maintaining an interrogation of the case file for gaps in verification or incongruence that needs to be resolved.
While non-merit staff cannot perform the Actual Interview or Certification, this would, in practice being a "removing the interview", but updating the service design so that applicants must go through it or explicitly opt-out. Opt-outs could be directed to an Actual Interview with Merit Staff. Merit Staff would still conduct the actual Certification for all applicants, using the output of the "interview" conducted by AI/automation.
My understanding is that in your example the state could not do that, because the interview itself is required by FNS guidance. (The nuance is that while the interview is not statutorily required, FNS does have the authority to require it; it seems they are simply not obligated by law to require it.)
You're also hitting at a really key thing! What's the line for automation of eligibility work that must be done by merit staff? Doing some of the more rote parts of the interview (think: reading to the client what they put on the app, and asking them if it's correct) might streamline sub-components without removing the judgment of a person in the final determination. Certainly already today some parts of the process of a determination has some automation in it (i.e. benefit amount calculation) where the human's role is to review and finalize.
(Edited to add: unfortunately I think the FNS guidance released and cited above would make all of this require permission before trying any of it.)
"ANGIE, a system that eliminates location-based work-distribution and distributes tasks by
priority and due date to HRA SNAP staff, allowing operations to run more efficiently and
remotely when necessary."
Found this in your first link above — that *does* seem valuable in terms of balancing workload more efficiently. (Unfortunately NYC's SNAP timeliness is way in the hole.)
Maybe? I don't know how I feel. This doesn't *quite* seem like a fed-specific thing (states do the work in SNAP) though it is I suppose connected to AI in government issues more broadly.
How does the merit staffing consideration apply to questions about AI/tech adoption?
e.g. if I am the SNAP Director in Nevada, and I recognize that eligibility interviews are not required by statute, but I also am very concerned about the impact on improper payments should we remove it -- I might see an automated/AI "interview" as a viable way to reduce workload while maintaining an interrogation of the case file for gaps in verification or incongruence that needs to be resolved.
While non-merit staff cannot perform the Actual Interview or Certification, this would, in practice being a "removing the interview", but updating the service design so that applicants must go through it or explicitly opt-out. Opt-outs could be directed to an Actual Interview with Merit Staff. Merit Staff would still conduct the actual Certification for all applicants, using the output of the "interview" conducted by AI/automation.
My understanding is that in your example the state could not do that, because the interview itself is required by FNS guidance. (The nuance is that while the interview is not statutorily required, FNS does have the authority to require it; it seems they are simply not obligated by law to require it.)
You're also hitting at a really key thing! What's the line for automation of eligibility work that must be done by merit staff? Doing some of the more rote parts of the interview (think: reading to the client what they put on the app, and asking them if it's correct) might streamline sub-components without removing the judgment of a person in the final determination. Certainly already today some parts of the process of a determination has some automation in it (i.e. benefit amount calculation) where the human's role is to review and finalize.
(Edited to add: unfortunately I think the FNS guidance released and cited above would make all of this require permission before trying any of it.)
In New York City, the Human Resources Administration (HRA), which administers SNAP and Cash Assistance, has started using software for applications (ACCESS HRA) and case management (ANGIE) in the last few years (https://www.nyc.gov/assets/opportunity/pdf/policybriefs/expanding-access-to-public-benefits.pdf). It seems like ANGIE might be counterproductive (https://citylimits.org/2023/09/28/city-officials-grilled-on-staffing-needs-amid-public-benefit-processing-crisis/) but in theory, systems like these could be useful interventions.
"ANGIE, a system that eliminates location-based work-distribution and distributes tasks by
priority and due date to HRA SNAP staff, allowing operations to run more efficiently and
remotely when necessary."
Found this in your first link above — that *does* seem valuable in terms of balancing workload more efficiently. (Unfortunately NYC's SNAP timeliness is way in the hole.)
Would you want this posted to relevant subreddits? Seems like r/fednews might appreciate it, along with some policy subreddits.
Maybe? I don't know how I feel. This doesn't *quite* seem like a fed-specific thing (states do the work in SNAP) though it is I suppose connected to AI in government issues more broadly.
I think the issues with hiring also apply in a federal context, but was also thinking about places like the SNAP subreddit.