AI Trustworthiness Challenges and Opportunities Related to IIoT
data science teams while also ensuring
critical content stays safe and protected
from the outside world.
characteristics (security, privacy, reliability
and resilience).
To address the trustworthiness challenges, it
helps to partition the AI use cases that are
emerging into two categories:
AI IN I NDUSTRIAL S YSTEMS
Industrial operation is facing a shrinking
decision timeline, so when it comes to the
application of AI in industry, it is not enough
for AI to simply pass the proverbial Turing
Test. 5 This is because human-like
performance can at times be immoral and
lead to unacceptable outcomes, as
evidenced by malware, ransom-ware and
terrorism to mention a few. This means that
in IoT, a naive approach to AI is
unacceptable, especially since people place
higher expectations on automated systems 6 .
1. The use of AI to improve the
efficiency,
reliability
and
effectiveness of processes and tasks
that can be fully automated with
little risk. These are processes and
tasks that are generally mundane,
repeatable,
static
with
few
variations, or tasks that are very
specific and/or localized to specific
components in system.
2. The use of AI in processes that are
critical, consequential 8 9 and non-
mundane. When the level of risk is
high enough, humans must maintain
the
ultimate
decision-making
capacity – this is referred to as the
“human-in-the-loop” approach or
HIL.
Just as with other systems, designers of AI
must address regulations, laws and
established best practices, especially with
regards to safety, privacy and security. They
need to consider the need to be able to
explain the decisions of systems and how
they are reached, not only to avoid
inappropriate bias, but also to create
systems that can be trusted, through
evidence and audit. Such an approach is
essential to addressing safety concerns, 7 as
well as other IoT Trustworthiness
Consider these two categories are part of
designing for trustworthiness. The basic
principle
is
that
trustworthiness
characteristics (safety, security, privacy,
reliability and resilience) cannot easily be
5
The Turing Test is a test of a machines ability to exhibit intelligent behavior equivalent to or indistinguishable from that of a
human.
6
Car accidents of autonomous cars get much higher attention in society than car accidents caused by humans.
7
“Key Safety Challenges for the IIoT”, IIC White Paper, 1 December 2017,
https://www.iiconsortium.org/pdf/Key_Safety_Challenges_for_the_IIoT.pdf
8
Patient X-rays analysis, autonomous driving, etc.
9
US DoD Directive 3009.09: Establishes DoD policy and assigns responsibilities for the development and use of autonomous
functions in weapon systems, and establishes guidelines to minimize the probability and consequences of failures in such
autonomous systems - https://www.hsdl.org/?abstract&did=726163
IIC Journal of Innovation
- 80 -