2026-27 Center for Spatial Business Speaker: Putting AI in its place

PUTTING AI IN ITS PLACE: GEOSPATIAL APPLICATIONS, ECONOMIC TRADEOFFS,
AND RESPONSIBLE CHOICES
WEDNESDAY
OCTOBER 7, 2026
Dinner at 5:30 p.m.
Talk 6:00 - 7:00 p.m.
University of Redlands, Casa Loma Room
1230 E Brockton Ave, Redlands, CA 92374
RSVP by October 2

ABOUT THE TALK
Artificial intelligence is changing how organizations analyze
information, automate tasks, and make decisions. Yet many of the
most important AI questions are not technical questions at all.
They are questions about incentives, tradeoffs, externalities, risk,
and governance.
This presentation examines AI through the combined perspectives of
geospatial analytics and behavioral economics. We explore how AI
creates value, where hidden costs emerge, how benefits and burdens
are distributed across people and places, and why the strongest
guardrails are required where consequences of error are greatest.
Along the way, we will tackle a deceptively simple question:
Does this problem truly require AI, or could a simpler solution
achieve the same outcome?
Attendees will leave with a practical framework for making
more informed, responsible, and economically sound decisions
about AI adoption.
with Dr. Wendy Keyes, Esri

ABOUT THE TALK
Artificial intelligence is changing how organizations analyze
information, automate tasks, and make decisions. Yet many of the
most important AI questions are not technical questions at all.
They are questions about incentives, tradeoffs, externalities, risk,
and governance.
This presentation examines AI through the combined perspectives of
geospatial analytics and behavioral economics. We explore how AI
creates value, where hidden costs emerge, how benefits and burdens
are distributed across people and places, and why the strongest
guardrails are required where consequences of error are greatest.
Along the way, we will tackle a deceptively simple question:
Does this problem truly require AI, or could a simpler solution
achieve the same outcome?
Attendees will leave with a practical framework for making
more informed, responsible, and economically sound decisions
about AI adoption.