Who is The Champion For AI Ethics?
April 15, 2022
A new IBM Institute for Business Value (IBV) study revealed a radical shift in
the roles responsible for leading and upholding AI ethics at an organization.
When asked which function is primarily accountable for AI ethics, 80% of
respondents pointed to a non-technical executive, such as a CEO, as the primary
"champion" for AI ethics, a sharp uptick from 15% in 2018.
is primary responsible for AI ethics?
study* also indicates that despite a strong
imperative for advancing trustworthy AI,
including better performance compared to
peers in sustainability, social
responsibility, and diversity and inclusion,
there remains a gap between leaders'
intention and meaningful actions. The
Business executives are now seen as the
driving force in AI ethics
(28%) – but also Board members (10%),
General Counsels (10%), Privacy Officers
(8%), and Risk & Compliance Officers
(6%) are viewed as being most
accountable for AI ethics by those
66% of respondents cite the CEO or other
C-level executive as having a strong
influence on their organization's ethics
strategy, more than half cite board
directives (58%) and the shareholder
Building trustworthy AI is perceived as a
strategic differentiator and organizations
are beginning to implement AI ethics
than three-quarters of business leaders
surveyed this year agree AI ethics is
important to their organizations, up
from about 50% in 2018.
- At the
same time, 75% of respondents believe
ethics is a source of competitive
differentiation, and more than 67% of
respondents that view AI and AI ethics
as important indicate their
organizations outperform their peers in
sustainability, social responsibility,
and diversity and inclusion.
companies have started making strides.
In fact, more than half of respondents
say their organizations have taken steps
to embed AI ethics into their existing
approach to business ethics.
than 45% of respondents say their
organizations have created AI-specific
ethics mechanisms, such as an AI project
risk assessment framework and
Ensuring ethical principles are embedded in
AI solutions is an urgent need for
organizations, but progress is still too
surveyed CEOs (79%) are now prepared to
embed AI ethics into their AI practices
– up from 20% in 2018 -- and more than
half of responding organizations have
publicly endorsed common principles of
less than a quarter of responding
organizations have operationalized AI
ethics, and fewer than 20% of
respondents strongly agreed that their
organization's practices and actions
match (or exceed) their stated
principles and values.
- 68% of
surveyed organizations acknowledge that
having a diverse and inclusive workplace
is important to mitigating bias in AI,
but findings indicate that AI teams are
still substantially less diverse than
their organizations' workforces: 5.5
times less inclusive of women, 4 times
less inclusive of LGBT+ individuals and
1.7 times less racially inclusive.
companies today use AI algorithms across
their business, they potentially face
increasing internal and external demands to
design these algorithms to be fair, secured
and trustworthy; yet, there has been little
progress across the industry in embedding AI
ethics into their practices," said Jesus
Mantas, Global Managing Partner, IBM
Consulting. "Our IBV study findings
demonstrate that building trustworthy AI is
a business imperative and a societal
expectation, not just a compliance issue. As
such, companies can implement a governance
model and embed ethical principles across
the full AI life cycle."
The time for
companies to act is now. The study data
suggests that those organizations who
implement a broad AI ethics strategy
interwoven throughout business units may
have a competitive advantage moving forward.
The study provides recommended actions for
business leaders including:
a cross-functional, collaborative
approach - ethical AI requires a
holistic approach, and a holistic set of
skills across all stakeholders involved
in the AI ethics process. C-Suite
executives, designers, behavioral
scientists, data scientists, and AI
engineers each have a distinct role to
play in the trustworthy AI journey.
Establish both organizational and AI
lifecycle governance to operationalize
the discipline of AI ethics - take a
holistic approach to incentivizing,
managing and governing AI solutions
across the full AI lifecycle, from
establishing the right culture to
nurture AI responsibly, to practices and
policies to products.
beyond your organization for partnership
– expand your approach by
identifying and engaging key AI-focused
technology partners, academics,
startups, and other ecosystem partners
to establish "ethical interoperability."