Google DeepMind's Susan Zhang requests documented proof of AI support bots successfully resolving customer issues without human intervention
An engineer argued support loops are intentional cost-reduction tactics.
@suchenzang Appointment booking, it did work perfectly fine when i didn't have any special request.
so... has anyone seen an ai customer support bot resolve an issue firsthand, without escalating to a human or forcing you to give up after a hall-of-mirrors-infinite-loop? if so, what task (& for which co.) did it complete the above successfully?
(preferably examples that don't involve refunds)
I did AI for customer support at stripe for a bit before I left, and I learned two things: 1) humans are incredibly, incredibly bad at support 2) support exists to reduce the burden on the core engineering team by redirecting and filtering, and the best way to support is by FIXING THE ACTUAL PROBLEMS IN THE PRODUCT and allowing self serve
so... has anyone seen an ai customer support bot resolve an issue firsthand, without escalating to a human or forcing you to give up after a hall-of-mirrors-infinite-loop? if so, what task (& for which co.) did it complete the above successfully?
@suchenzang the hall of mirrors is actually engineered, designed to reduce costs. the way you help with "AI" is actually just.. datapipelines and attribution to teams, to create incentives (negative or positive) for engineering to actually fix the core issues and see a line go down
I did AI for customer support at stripe for a bit before I left, and I learned two things: 1) humans are incredibly, incredibly bad at support 2) support exists to reduce the burden on the core engineering team by redirecting and filtering, and the best way to support is by FIXING THE ACTUAL PROBLEMS IN THE PRODUCT and allowing self serve
@suchenzang it's the **same** exact problem as resource usage. if you measure it, and give teams and engineers a hill to climb, they'll climb it
make the problem verifiable in some manner.. testable
@suchenzang the hall of mirrors is actually engineered, designed to reduce costs. the way you help with "AI" is actually just.. datapipelines and attribution to teams, to create incentives (negative or positive) for engineering to actually fix the core issues and see a line go down