AISP Toolkit Feb25 2025 - Flipbook - Page 24
Centering Racial Equity
Throughout the Data Life Cycle
entering racial equity throughout data integration is not a single, discrete step, but rather an
ongoing process at each stage of the data life cycle—planning, data collection, data access,
data analysis, use of algorithms and arti昀椀cial intelligence, and reporting and dissemination.
Each stage presents new opportunities to bring a racial equity frame to data integration, as well as
new challenges and considerations. Depending on your role, you may have more experience (and
leverage) in some stages than others. We encourage you to focus on the pieces most relevant to your
work and to consider allies and partners who have the potential to shift practice where you do not.
CENTERING RACIAL EQUITY THROUGHOUT THE DATA LIFE CYCLE
C
REPORTING &
DISSEMINATION
USE OF ALGORITHMS &
ARTIFICIAL INTELLIGENCE
DATA ANALYSIS
PLANNING
DATA COLLECTION
DATA ACCESS
The following sections provide an overview of racial equity considerations throughout the data life
cycle, examples of positive and problematic practices, and brief examples of Work in Action. The
Work in Action highlight current examples of how organizations from across the AISP Network and
beyond are centering equity at each stage of the data life cycle.
Racial Equity in Planning
Planning is the 昀椀rst stage of the data life cycle and includes all the work to prepare for future
stages. While this includes project planning and scoping, it also includes preparations even
further upstream, such as assessing organizational readiness (see What’s Next?); identifying
partners; articulating a purpose for data integration; identifying relevant legal authority
20
