So, you think you have an AI strategy? Think again.
(SIFA) by applying it to an AV use case; where
mission- and non-mission-critical workloads
occur in public and private spaces. AVs also
relate well to adjacent smart transportation
use cases such as autonomous planes, boats,
buses or trains. Applying SIFA to the AV use
case shows a relatively low cost and quick-
turn way for organizations to integrate open
strategy and design thinking processes and
practices into their technology strategy
activities.
There is a lack of standardization for how city
leaders and decision makers can perform
this evaluation. For example, the
International
Organization
for
2
Standardization (ISO) approved ISO 37120
standard on “Indicators for City Services and
Quality of Life” and ISO 37122 standard on
“Indicators for Smart Cities.” Unfortunately,
ISO 37122 has 18 factors and 32 indicators,
and only two relate to AI. One indicator
addresses “Percentage of vehicles registered
in the city that are autonomous vehicles”
and the other addresses “Percentage of
roads compliant with autonomous driving
systems.”
M OTIVATION
The United Nations estimates that the
world’s population will reach 10.2B by 2060,
and 68% of those people will reside in cities. 1
In order to cope with this emerging crisis,
city leaders and decision makers will need to
adapt their strategy for serving existing
citizens as well as future ones through the
adoption of AI technologies, products and
services. They will face at least two
challenges. First, AI products and services
are capable of sensing, collecting, storing
and predicting highly sensitive data and
information about citizens. City leaders and
decision makers will need to figure out how
to balance evaluating these technologies to
meet security requirements with satisfying
business policies aligned to social values
such as privacy and ethics.
Building on advancements over the past few
decades, the promise of AI to change the
nature of work has become more plausible,
mainly due to the computational
advancements in recent years and the ability
to collect, store and analyze more data than
was the case only a few years ago. These
mean new possibilities from manufacturing,
construction, health-care, transportation,
agriculture to smart cities.
Despite these advancements and their
promise to bring a seismic change to the way
machines and humans interact, the exact
evolution of AI remains unclear. For
example, DARPA asserts AI will evolve in
three waves. 3 In the third wave, they expect
1 https://www.un.org/development/desa/en/news/population/2018-revision-of-world-urbanization-prospects.html
2 https://www.iso.org/
3 https://www.darpa.mil/about-us/darpa-perspective-on-ai
IIC Journal of Innovation
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