AISP Toolkit Feb25 2025 - Flipbook - Page 57
Algorithms
Arti昀椀cial
Intelligence (AI)
Machine Learning
(ML)
Deep Learning
(DL)
A technology that
combines different
types of algorithms
to perform tasks
that typically require
human intelligence
(e.g., recognizing
patterns, learning
from data, and making
decisions)
A complex
combination of
algorithms that can
learn from data and
improve performance
on tasks over time
with minimal human
intervention
A type of ML that
uses a multi-layered
network of algorithms
to identify complex
patterns within
large datasets and
make decisions or
predictions without
speci昀椀c instructions
Example: A tool that
displays spikes in
protest activities to
identify potential
moments of
mobilization or new
movements
Example: A tool that
analyzes canvassing
conversations to
understand voter
concerns and
motivations
Example: Image
recognition programs
to detect or classify
abnormalities in
medical imaging
Example: Predictive
analytics to forecast
outcomes in child
welfare cases
ALGORITHMS
Automated instructions
ARTIFICIAL INTELLIGENCE
Programs with the agility to
mimic human behavior
MACHINE LEARNING
Algorithms with the ability to learn
without being explicitly programmed
CENTERING RACIAL EQUITY THROUGHOUT THE DATA LIFE CYCLE
A set of step-bystep instructions or
rules that enables
automated problem
solving or task
completion
DEEP LEARNING
Subset of machine learning
in which arti昀椀cial neural
networks adapt and learn
from vast amounts of data
Graphic used with permission under CC BY-ND 4.0. Vrana, J. & Singh, R. (2020). The NDE 4.0: Key
Challenges, Use Cases, and Adaption.
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