So, you think you have an AI strategy? Think again.
I NTRODUCTION
Popular press, media and even companies
tend to portray the future of AI from one of
two dominant world views. From a utopian
point of view, where AI brings humanity new
ways of achieving exponential benefits to
economies of scale, productivity and safety,
so the implied strategy is “build it and they
will come.” From a dystopian point of view,
though, AI will make irreversible immoral
decisions for mission critical situations, so
the implied strategy is “stop it before it takes
over the world.” The fragmented thinking
regarding plausible systemic risks and
benefits for companies, consumers and
everybody involved has resulted in AI
becoming
a
controversial
topic.
Furthermore, the rapid evolution of AI and
its convergence with other technology
platform ecosystems such as 5G, Blockchain,
AR/VR, IOT, Fog and Cloud are driving and
shaping new ways for people to live. This
next evolution is often referred to as
Ambient intelligence or the 4th Industrial
Revolution and has resulted in many open
questions, such as:
are conditioned on factors, such as
impact to environment and society?
In what ways might an AI strategy be
adapted to be resilient or to thrive
under these conditions?
In this short overview, we argue
organizations will increase the expected
value of their investments in AI technologies,
products and services by adapting their
technology strategy to include the social
impact of AI. More specifically, we assert an
AI strategy should not just be about
technology, but it should also be about
integrating open strategy and design
thinking processes and practices. These
activities should proactively include citizens’
perspectives and participation to gain direct
insights and feedback on the plausible
systemic risks and benefits of AI
technologies before, and not after, they are
deployed into their respective community.
Secondly, we argue organizations should
adopt new analytical methods and
techniques deliberately designed to
characterize the social impact of AI. These
approaches should characterize the impact
of AI to factors such as environment, energy
and society (ethics, economics, gender,
culture, language). Regardless of whether an
organization is making mobile apps or
autonomous vehicles (AV), we assert they
stand to gain more from their AI strategy by
expanding it to include the social impact of
AI.
What is the social impact of AI,
really?
How might we characterize the
plausible systemic risks and benefits
of AI before, not after, it is deployed
into a community?
To
what
extent
does
an
organization’s
AI
strategy
comprehend plausible futures
where the adoption of AI
technologies, products and services
First, we provide a brief background on our
motivations, the opportunity space, and a
sampling of existing initiatives exploring
social impact of AI. Next, we walk through an
example of “Social Impact Factor Analysis”
- 51 -
June 2019