FEATURE
certain applications, data integrity may
end up eclipsing data confidentiality.
The next step in the deployment of AI
and ML is to ensure that the right talent
and data is being used. Those who
build it need to be representative of
everyone, with cross-functional teams
also being a requirement to ensure its
design is representative of all. Security,
privacy, ethics and compliance issues
will increasingly require that companies
set up cross-functional teams when they
build AI and Machine Learning systems
and products for this purpose.
AI and Machine Learning are appearing
in many of the products and systems we
interact with. You could call it a success
already with its ability to remove us from
more mundane and repetitive tasks.
However, at present, organisations need to
understand the essentials and ensure they
invest time and resources to get security
and ethics right. Organisations must
ensure that in the year ahead, they are
able to close the skills gap and must take
another look at overall data quality. u
Nearly 73% of senior
business leaders
admit that they don’t
check for security
vulnerabilities during
model building.
set of users expected to interact with
these systems. If we want to create AI
technologies that work for everyone –
they need to be representative of all
races and genders.
As Machine Learning inevitably
becomes more widespread, it will
become even more important for
companies to adopt and excel in
this technology. The rise of Machine
Learning, AI, and data-driven decisionmaking
means that data risks extend
much further beyond data breaches, and
now include deletion and alteration. For
www.intelligentciso.com | Issue 25
39