Waikato Business News | November 1, 2023

18 WAIKATO BUSINESS NEWS
NOVEMBER 2023
How is Artificial Intelligence impacting you?
ADVERTORIAL
Artificial Intelligence (AI) is
emerging as the defining
technology of our age, with
many industries already
utilising AI in some form whether you
know it or not.
Examples of AI include:
• ‘Personal assistants’ such as Alexa
and Siri and customer chatbots
• Machine learning customer
analytics to predict and
recommend actions to prevent
customer turnover
• Retailers being able to predict
customer orders in advance
• Customised robo-advice for
consumer investments
• Intelligent process automation
(robotic process automation
combined with AI)
• Optimising the scheduling and
rescheduling of healthcare
appointments, including prediction
of non-attendance
• Tesla Autopilot driver assistance
system.
The next big thing
Almost every aspect of our daily lives
has been digitised. Internet and mobile
technologies have transformed the way
that we live and work. A new wave of
technology is now coming through, and
it centres on data. 72% of US business
leaders believe AI will be the business
advantage of the future. AI will utilise
data to assist us with the many tasks
that we currently do ourselves today
and will be able to do things that we’ve
never even conceived of before.
AI at work
Commercially applied AI has expanded
in recent years, driven by a combination
of computing power, the availability of
huge datasets and advances in machine
learning techniques. AI enables
machines to respond on their own to
signals from the world at large, signals
that programmers do not directly
control and therefore can’t anticipate.
The fastest growing category of AI
is machine learning, the ability of
software to improve its own activity,
based on interaction with the world at
large.
The spectrum of AI can be divided into
three areas:
• Assisted Intelligence; widely
available today, improves what
people and businesses are already
doing
• Augmented Intelligence; emerging
today, enables people to do things
they couldn’t otherwise do
• Autonomous Intelligence;
being developed for the future,
establishes machines that act on
their own
PwC’s Global Artificial Intelligence
Study
Highlights from our Global AI Study
include:
• AI has a potential contribution of
$15.7 trillion to the global economy
by 2030 Up to 10.4% boost in GDP
for local developed Asia economies
(including Australia and New
Zealand) from AI by 2030
• Labour productivity improvements
- driving initial GDP gains as firms
seek to “augment” the productivity
of their labour force with AI
technologies and to automate
some tasks and roles
• 45% of total economic gains by
2030 will come from product
enhancements. AI will drive greater
product variety, with increased
3%
personalisation, attractiveness and
affordability over time.
AI is set to be the key source
of of transformation, jobs at potential disruption risk of automation and
competitive by early 2020s advantage in today’s fast
Strategy
Data & AI Ethics
Consider the moral
implications of uses of
data and AI and codify
them into your
organization’s values.
Policy & Regulation
Anticipate and
understand key public
policy and regulatory
trends to align
compliance processes.
changing economy.
Impact on jobs
We analysed over 200,000 jobs in 29
countries to explore the economic
benefits and potential challenges posed
by automation.
AI will both generate the demand
for many jobs, but there are also
concerns that it could displace many
existing jobs. Job displacement will
increase over time as AI technologies
mature and are rolled out across the
economy. Autonomous vehicles and
other machines will replace many
manual tasks and increased automation
will impact those in clerical and other
administrative jobs.
While AI may displace certain jobs,
it is forecast to create more jobs than it
displaces. Some business sectors will
be impacted more than others, with
increases expected in health and social
work, education and professional,
scientific and technical services.
AI will also increase productivity
and make jobs more enjoyable by
automating the more mundane tasks
within a job role, enabling people to
focus more on creative and teamwork
aspects of their job.
Four steps to making the most out of AI:
1. Work out what AI means for your
business
The starting point for strategic
evaluation is a scan of the
technological developments and
competitive pressures within
your sector, how quickly they
will arrive and considering how
you will respond. You can also
identify operational pain points or
opportunities that AI could address
both with what is available now
and more importantly, where the
technology is heading in the future.
2. Prioritise your response
In determining your strategic
evaluation, consider these key
questions: What is your appetite
and readiness for change? Do you
want to be an early adopter, fast
follower or follower? Your answers
will assist in determining how the
different AI options can help you
deliver your business goals.
3. Make sure you have the right
talent and culture, as well as
technology
Investment in AI is expensive
now, but it is anticipated that the
of jobs costs at potential will decline risk over of automation the next ten
by mid-2030s years as the software becomes
more commoditisied. While the
enabling technology is likely to be
increasingly commoditisied, the
supply of data and how it’s used are
set to become the primary assets.
4. Build in appropriate governance
and control
Trust and transparency are
critical. For example, in relation
to autonomous vehicles, AI
requires people to trust their
lives to a machine - a huge leap
of faith for both passengers and
public policymakers. Anything
that goes wrong (malfunction or
crash) is headline news. And this
reputational risk applies to all
forms of AI, not just autonomous
vehicles. Customer engagement
bots have been known to acquire
biases through training or
manipulation.
Key AI risks
• Biased, offensive or misleading
content - AI is only as good as the
data it was trained on.
• Novel privacy breaches - AI’s ability
to connect data from within the
vast datasets could compromise
your privacy controls.
• Unsafe models built on theft - with
so much data underlying some AI,
you may not know its source or if
you have permission to use it.
• Inadvertently sharing your
intellectual property - without care,
you could find your proprietary
data and insights from the
information you enter into a
generative AI model becoming part
of the database and widely shared.
• Hallucinations threaten
performance - Generative AI is
good at coming up with convincing
answers, but sometimes its
answers are flat-out wrong, yet
presented authoritatively.
• Cyber Threats - AI can assist
malicious actors to impersonate
someone’s writing style, manner
of speech and facial expressions.
This could then be used to spread
misinformation or to attempt to
convince you to share sensitive
data or lead to financial loss.
Responsible AI - some mitigations for
the risks
• Equip users for responsible use
Control ds
Responsible Practices Core Practices
Governance
Enable oversight of
systems across the
three lines of defense.
Compliance
Comply with regulation,
organizational policies,
and industry standards.
Risk Management
Expand transitional risk
detection and mitigation
practices to address
risks and harms unique
to AI.
30%
Interpretability &
Explainability
Enable transparent
model decision making.
Sustainability
Minimize negative
environmental impact
and empower people.
Robustness
Enable high performing
and reliable systems.
Bias & Fairness
Define and measure
fairness and test
systems against.
Security
Enhance the
cybersecurity of systems.
Privacy
Develop systems that
preserve data privacy.
Safety
Design and test systems
to prevent physical harm.
44%
and oversight - teach employees
of workers who use with AI low the basics education of how at risk it
of automation works, when by mid-2030s
and how to use it, and
Problem
Formulation
Identify the concrete
problem you are
solving for and whether
it warrants an AI/ML
solution
Standards
Follow industry
standards and best
practices.
when and how to verify or modify
outputs
• Set risk based priorities - based
upon your use of AI, assess the
risks and give greatest attention to
the greatest risks
• Revamp cyber, data and privacy
protections - update your policies
and processes to help mitigate the
risks from malicious actors
• Watch the regulatory landscape -
policymakers around the world are
issuing more and more guidance
on AI development and usage
• Monitor third parties - know which
of your vendors provide content or
services that use AI (including the
software and applications you use -
e.g. Microsoft Copilot for Office)
• Oversight - consider emerging
software tools to identify AIgenerated
content, verify its
output, assess it for bias or privacy
violations and add citations as
needed
Right from the start
It’s better to implement confidence by
design and ethics by design from the
start, rather than racing to close gaps
after systems are up and running. PwC
has a responsible AI framework that
can help manage these risks and others
too. It delivers confidence by design
through the entire AI lifecycle, with
frameworks, templates and code-based
assets and it is relevant at all levels of
your organisation.
Validation
Evaluate model
performance and
continue to iterate on
design and
development to
improve metrics.
Monitoring
Implement continuous
monitoring to identify
drifts and risks.
• For more information visit www.
pwc.co.nz/services/risk-services/
what-is-responsible-ai.html
Local Contact:
Aaron Steele, Director,
Risk Assurance, PwC