AISP Toolkit Feb25 2025 - Flipbook - Page 19
surveillance using biometric data often without disclosure, should be considered with the utmost
caution, and in some instances data sharing should not proceed.
Examples included in this toolkit are not meant to be used as binary yes/no decision-making
tools, but rather as guides for thinking about and talking through intended and unintended
consequences of civic data use with a variety of voices and perspectives.
HIGH
Mapping indicators to allocate
new investments to high-need
neighborhoods
Linking individual data
on wages & earnings
Case management
algorithms
Using “risk scores” to
target interventions
Unduplicated counts of children
across early childhood programs
Predictive analytics
in policing
Open data initiatives
that publish aggregate
data sets
Tracking social media on students
Linking biometric data
(e.g., facial recognition)
RISK
LOW
HIGH
Including more voices as part of your deliberation about the risk vs. bene昀椀t of a use case will both
strengthen your social license and also require more time and resources. This is a delicate balance
that each of us must walk with on our path towards more participatory governance.
FOUNDATIONS FOR COMMUNITY INVOLVEMENT
BENEFIT
Program evaluation with
longitudinal outcomes
We encourage:
0 Assessing organizational readiness for community involvement along a
spectrum; see What’s Next? for a framework and tools to help determine
next steps
0 Working to build social license developmentally, with participatory
governance as the goal
0 Using the four questions as a starting point to assess
use cases
0 Carefully considering risk vs. benefit for data collection,
access, and use
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