AI & DEI: With Great Opportunities Comes Great HR Responsibility

Today’s Purpose
Revolutionizing global HR leadership by leading
with AI, growing skills, building trust in the
workforce to mitigate bias, drive business
outcomes and promote DEI&A
1. Opportunity & Responsibility
2. Upskilling HR & DEI&A
3. Power of Trust

Jen Kirkwood Great Responsibility

“In every step of the AI journey, we got more and more efficient.
The difference with GenAI is that the level of efficiency is so
much higher. We’re seeing a substantial increase in efficiency,
more than in any of the other steps that we have done in the last
ten years.
Over time, this will have a huge impact.”
Hans Vestberg, CEO of Verizon
Why is the industry so focused on GenAI?

AI generated images are making headlines
They are in fact, KPIs on the Data’s Diversity – or Lack
there of.
Misuse. Misinformation
(includes Hallucinations, Harms)
Are humans or AI more bias?
Bloomberg, 2023
Jen Kirkwood Great Responsibility

What has held HR back from AI in the Past may NOT
be always a hurtle today… Money and IT Budget
With the CEO focus on strategy, spending on (gen)AI is increasing.
https://www.horsesforsources.com/big4-lunch-eaten-genai_121723/
Spending outside of the CIO Budget
Great Responsibility

CEO NOW Strategy on (gen)AI
3 out of 4 CEO’s stated they plan to or are using GenAI as a
competitive strategy. *
74% of CEOs according to the same study, were convinced
they had the right skills in house to create, build and maintain
GenAI use cases. However, only 29% of the rest of their C
suite team agreed. *
6 months later, things have changed. MIT and BCG reported
only
29% of 4 CEOs felt that were still true. (Dec. 2023)**
* Institute of Business Value, the CEO’s Competitive Guide to Generative AI
World Economic Forum Meeting, Davos, Switzerland, Executive Interviews
** MIT and Boston Consulting Group, Dec. 2023
Opportunity & Responsibility

Artificial intelligence system: a machine-based
system that, for explicit or implicit objectives,
infers, from the input it receives, how to
generate outputs such as predictions, content,
recommendations or decisions that can influence
physical or virtual environments.
Generative AI: AI models specifically intended to
produce new digital material as an output (e.g. text,
images, audio, video and software code), including
when such AI models are used in applications and
their user interfaces. These are typically constructed
as machine learning systems that have been trained
on massive amounts of data.
Responsible AI: AI that is developed and
deployed in ways that maximize benefits and
minimize the risks it poses to people, society and
the environment. It is often described by various
principles and organizations, including but not
limited to robustness, transparency, explainability,
fairness and equity.
Responsible transformation: The organizational
effort and orientation to harness the opportunities
and benefits of generative AI while mitigating the
risks to individuals, organizations and society.
Responsible transformation is strategic coordination
and change across an organization’s governance,
operations, talent and communications.
Responsible adoption: The adoption of individual
use cases and opportunities within the responsible
AI framework of an organization. It requires thorough
evaluation to ensure that value can be realized and
change management is successfully aligned with
defined goals in a responsible framework.
Diversity is More Important than Ever
Upskilling in the Age of AI
See definitions from Unlocking Value from Generative: Guidance for Responsible
Transformation, World Economic Forum, Jan. 2024

HR is more Important than Ever
New Skills + Experience + Foundational
Artificial Intelligence in Human Resources has
the potential to transform the global workplace.
According to Gartner, 80% of HR is using or
planning to use (gen)AI
AI in tools can help improve the entire candidate- employee
lifecycle. With the ability to automate and eliminate repetitive HR
tasks, this technology empowers HR professionals to focus on
strategic initiatives. IF there is good thought around decision
making.
The impact of AI on HR is a profound change that brings a new era
of responsibility.
And HR needs to lead it.
See additional cases in Unlocking Value from Generative: Guidance for Responsible
Transformation, World Economic Forum, Jan. 2024

HR & Diversity Is Sorely Needed for Responsible AI
Now to Upskill.
“Diversity objectives have finally
become the center focus of AI as
headlines show bias as the headline
an issue executives want to avoid
more than regulatory compliance”
(Gartner, 2023)
Yet when Responsible AI
needs diversity skills so
critically… Organizations are
shedding the skills
One org’s departure is another’s best hire…

The Impact …
Why is HR Responsible?
• The workforce is using these tools – Ready or
Not.
• Despite whether there are policies stating
public GPT tools cannot be used for work
purposes, employees are bringing the output to
work if these tools are not robust and provided
for them.
• The impact of using public models at work can
have significant consequences on employees,
brand, compliance, safety and customers.
• Bias exists in all models and must be mitigated
and managed early in ideation, design and in
maintenance.
• Responsible AI Strategy is an imperative for HR
to protect the workforce, organizational risk,
and brand.
Created with Canva AI

AI
Literacy
in DEIA
1. When job seekers interact with AI hiring technology, what accommodations or assistance might they ask
for? What information would help given the headlines and issues of trust, privacy?
2.Vendors have been in the news with discrimination and bias in their AI in HR tools.
How can HR ensure fair and equitable tools?
3. How can HR update reasonable accommodation policies to account for any unique aspects of AI HR
technologies
4. The organization needs DEIA and HR Resources from the START of use case creation through the AI life
cycle. Why? Bias starts at the inception of ideas and team formation. Innovation needs diverse and creative
thought.
Opportunity & Responsibility
IBM IBV CEO GenAI Study, 2023

Areas of triage for GenAI projects to be successful:
1. Talent and Skills are the center of success in order to drive
growth, revenue and AI strategy. The key enabler in
stakeholders: HR.
2. Change management and workforce adoption were critical
gaps.
3. Data. Without good data; bias & discrimination and poor
outcomes. (GenAI can help with cleaning of the data)
4. We need everyone from leadership and domains in this
effort. Legal. Compliance. HR. Operations.
5. HR is needed to assist the org and embed the DEIA skills
within these roles in learning and culture to retain diverse
teams as tech needs diversity to find the talent and in
other areas (AI Ethics, Legal etc)
Speed to market is key. Skills and good data quickly.
Hear it from the Executives themselves

Not just…
IT
Legal
Compliance
Ops
HR
DEIA
AI should augment human decision making, not
replace it. Where in your processes today do you
have automation or AI where there is zero human
oversight?
Have YOU inventoried every automation & AI in your
ecosystem?
This is a question for all…

Organizations have learned the hard reality in their
generative AI journeys – through failed experiments and
some successes.
On average only 30-40% of experiments are moving to
an enterprise scale. * (data between July- Dec 2023)
Why?
Research:
66% of executives are ambivalent or outright
dissatisfied with their organization's progress on
AI and GenAI so far 62 % citing the reasons on a
lack of talent and skills.****
What is holding Gen(AI) back from being MORE Successful Overall
(beyond HR)?
* Institute of Business Value, the CEO’s Competitive Guide to Generative AI
* *World Economic Forum Meeting, Davos, Switzerland, Executive Interviews
• * *MIT and Boston Consulting Group, Dec. 2023
• * * * * Gartner

Photo selected for lack of diversity
What is Understood What is often not
understood
Consider leveraging AI in this world of work, thoughtfully and with the
human in the loop.
Employers will always carry responsibility when it comes to vendors and
software. Consider third party auditors/ legal, data scientists, outside
experts, and others involved in considering privacy and AI requirements.
Regulations are rarely holding vendors responsible.
If our workforce is not diverse, should we use AI in
sourcing?
What should we consider?

1. Tailor communication styles to individual
preferences, promoting understanding and
inclusivity.
2. Generate summaries and transcripts of
meetings, making them accessible for those
with hearing impairments or who were absent.
3. Analyze company-wide communications or
employee feedback for unconscious bias or
potential areas of improvement.
4. Assistants as part of the Experience
5. Co-pilots, assistants help offload the tactical
6. Employees love presentation help, calendaring,
word smithing!
DEIA and Gen AI Creativity Cases on the Rise!
Recruiting & Job Descriptions Training & Development Communication & Feedback
1. Reduce bias in job descriptions by using AI
to identify and suggest gender-neutral and
inclusive language. (Please!)
2. Expand talent pools by sourcing candidates
from diverse backgrounds and expand to
include, when possible, accessibility for job
appropriate and neurodiversity (tech,
accounting is great for these!)
3. Create simulated interviews to help
candidates from diverse backgrounds gain
experience and alleviate anxieties.
1. Develop personalized learning
paths to address individual needs
and knowledge gaps.
2. Offer translation and language
learning tools to promote
understanding and
communication in multilingual
teams.
3. Design accessible training
materials (e.g., captions, audio
descriptions) for employees with
disabilities.

HR Use Cases of AI with DEIB and Responsible AI
Tech Firm
What
Organization redesigned their HR model after they
implemented an AI assistant solving employees
every tactical issues and managers top priorities. HR
is now coaching, mentoring and AMPLIFICATION of
Diversity, Equity, Inclusion & Accessibility Programs
Outcomes
Using Ethics by Design and Fairness 360, (Open
source models), HR implemented over 300k
employees now using recruiting, skills development,
performance and more. Human in the loop is key
and reviewing the data is key to understand “what is
good.” The data needed to be cleaned and reviewed,
ensuring only diverse data sets were used to avoid
the “Stable Diffusion” effect.
Airlines
What
Organization designed an assessment model of front-line
workers. They dropped the video assessment piece reading the
facial cues (GREAT!) due to bias concerns and instead mapped a
framework of skills to the skills desired in the country using a
global cross walk to the taxonomy they selected as most
appropriate. Legal was consulting along the way.
Outcomes
Responsible AI and OECD Frameworks were created by HR to
assist with explainability, trust, fairness & equity. Technical help
assisted and together Factsheets were produced so recruiters
could answer questions by candidates, employees when needed
and send to marketing and other departments (by persona). This
helped with career branding of their portal and communications
for those applying including those with accommodations whose
questions may have differed. Overall they hired quicker and a
recruiter also assigned in workflows to overview those who were
declined and dispositioned. Human in the loop!

Cases Needing Oversight
Workforce Management: Intelligent forecasting tools are leveraging AI
to predict better staffing and scheduling (leveraging multiple systems
now with GenAI)/ Be careful the training date and assumptions. Too
often the design “team” is 1-2 people in procurement creating a model
they do not think is AI that impact humans…and laws.
Procurement: Supplier bias mitigation leveraging AI in the model.
Assessment Tools: Some still use facial recognition despite
regulations and legal cases. EU Act is coming… Many US and
UK/Europe/ France/Germany state laws.
Assessments- Leveraging interviewing questions using AI that is using
limited voice mapping, maps to skills in countries using only US jobs
with no mapping to global frameworks
Accessibility Tools- Workflows, learning, and content NOT giving
required by law content that is accessible.
Always check privacy laws, regulations.

How do I start educating my team on Responsible AI
1.
2.
3. 4.
Open Tech Responsible
AI Academies, online
training but also invest in
yourself and your team to get
certifications that are
necessary or from 3rd parties
quickly.
Educate your HR
& Diversity Team
in AI & Data
Literacy
HR needs to build the skills for all use
cases, Responsible AI and DEIB as it is
embedded safety against the biggest
harms. Learning, policies and content
should be created by personas.
Assess the skills in your
organization
Persona-based In
order to build
effective guardrails,
HR must be at the
beginning of creating
ideas AND able to
leverage tech for HR
use and future scale.
Insert HR Leadership and
Expertise with DEIB and
the “Pillars” at the
creation START of use case
design (NOT END)
Take this team next
level to build the future
roadmap for HR and
DEIB
AI is advancing quickly
and results will be
expected financially
very soon. This team of
super skills can stay
ahead.
Build the HR Super SWOT
Team in AI Ethics
IBM Academy has open
education on AI Ethics,
Responsible AI for
certification
Power of Trust with HR

DEIA Is Needed More Than Ever for CEO Strategy
CEO Strategies depend on HR leadership to ensure competitive strategies
leveraging AI are successful
New business opportunity in business- productivity, revenue, and
efficiency depends on HR to be successful
HR can seize the opportunity to upskill and learn new skills in
Responsible AI as well as help the organization in other critical
areas (tech, customer, etc)
Trust- HR leadership understands workforce adoption change
management and ethics and can help drive use cases OUTSIDE of
HR to scale

Our HR DEIA Thought Leadership and AI Ethics at Work –
Workforce Literacy Starts With Leadership Data Literacy
31
CEO decision-making in
the age of AI
Foundation Models:
Opportunities, Risks &
Mitigations
Augmented work for an
automated, AI-driven
world
AI ethics in action Generating ROI with AI
Enterprise generative AI:
State of the market
World Economic Forum AI Governance Alliance
https://initiatives.weforum.org/ai-governance-alliance/home
IBM at the World Economic Forum Annual Meeting 2024
https://www.ibm.com/events/world-economic-forum
Balancing AI: “Do good” and avoid harm – January 25, 2024 Blog by Jennifer
Kirkwood
https://www.ibm.com/blog/balancing-ai-do-good-and-avoid-harm/
World Economic Forum
Generative AI Series, Jan. 2024
Briefing Paper Series (250
Global Organizations on
GenAI)
https://www.weforum.org/pu
blications/ai-governance-
alliance-briefing-paper-
series/

AI & DEI: With Great Opportunities Comes Great HR Responsibility

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