BC NA December 2020

model that can produce the best or
most optimized schedule for multiple
objectives and constraints,” says
Carter. “We provide decision-makers
with a mathematically aided assessment
that predicts schedules weeks
in advance and it gives them back time
in their day.”
Wider implications for the project
involve the gaining of efficiencies
across the board, from supply chains
to maintenance. “For instance, the
work that we’re doing today could
allow for advancements in scheduling
for hospital staffing, shift
workers, cargo and mail distribution,
logistics operations, and even commercial
airline crew scheduling or
flight maintenance.”
Carter emphasizes the extent to
which ethical considerations guide
everything which is done with AI.
“Within all of our projects we are considering
the implications of ethics.
EXECUTIVE PROFILE:
Ronisha Carter
33
Title: Artificial Intelligence R&D
Location: United States
Industry: Academia and Defense
Capt. Carter is the USAF-MIT Artificial Intelligence Accelerator’s
lead for AI-Assisted Optimization of Training Schedules project.
Carter has a B.S. in Computer Science from Hawaii Pacific
University and an M.S. in Computer Engineering from Florida
International University. Carter worked as a Cyber Operations
Officer before being selected to the Education with Industry
program where she was assigned to VMWare to use ML/AI to
create content driven intelligence platforms. Her technical
papers on ML/AI during this time helped land her a
follow-on assignment to MIT to serve as part of the initial
core of embedded Airmen for the AI Accelerator.
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