  Recent years have seen growing adoption of AI-based decision-support systems
(ADS) in homeless services, yet we know little about stakeholder desires and
concerns surrounding their use. In this work, we aim to understand impacted
stakeholders' perspectives on a deployed ADS that prioritizes scarce housing
resources. We employed AI lifecycle comicboarding, an adapted version of the
comicboarding method, to elicit stakeholder feedback and design ideas across
various components of an AI system's design. We elicited feedback from county
workers who operate the ADS daily, service providers whose work is directly
impacted by the ADS, and unhoused individuals in the region. Our participants
shared concerns and design suggestions around the AI system's overall
objective, specific model design choices, dataset selection, and use in
deployment. Our findings demonstrate that stakeholders, even without AI
knowledge, can provide specific and critical feedback on an AI system's design
and deployment, if empowered to do so.
