Ai revolution for human capital for government v2

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The AI revolution for human capital: the government edition

Andrew
Liew Cool!Let’s
rock!
10,000++
2,000++
Name: Andrew Liew Weida
Title: Analytics + Innovation +
Technology
Role: Subject matter expert
Brief Profile:
Andrew is a experienced technologist with over 10 years of experience,
having cofounded 4 startups and being the early employee executives
of 2 startups, having work over 9 international cities.. He specialized in
Technology industry, particularly within the HR, SaaS, Analytics and
On Demand Marketplace segment. Andrew has worked extensively
across 8 countries and assisted numerous clients in advising how
technology can scale their operations, how to reduce risk in
implementing technology and the potential impact of tech to companies
top line.
• Startup experience – over 5 years of CXO work for tech startups & tech
enabled companies in areas of financial management, HR management, digital
product management
• Financial Analytics- creating data sourcing map to build data driven simulations
for MNCs in the banking, Private and Public service sectors for increasing
revenue , reducing cost and reducing risk management.
• Reward Design –working with Remuneration committee of MNCs to ensure
financial feasibility of compensation design to ensure market competitiveness
and internal harmony.
Education:
• PhD candidate [Econometrics]@ ANU
• Master (Economics) (Admission with
scholarship)@ ANU
• Master (Finance) (1/400, Valedictorian)@
Usyd
• BSc (2.5/4 years, fastest graduating student in
faculty history) @NUS
• AB leadership@ Korea University
• UIUX HBF
• Externalities
assessment
• Analytics
• Benchmarking
• Reward
management
• Tech based Cash
flow Modelling
• Fundraising
• Digital Product
Management
• Salesforce
Effectiveness
Key Competencies:
Relevant Work experience:
Cofounder
We are your friends (1 min)

https://www.todayonline.com/commentary/singapore-must-chart-bold-course-age-digital-economy#.WnucawwlC-M.facebook

4© 2017 Qicstart All Rights Reserved
Table of Contents
1. Trends
2. Doomsday scenarios that people fear
3. Does AI purely replace people?
4. Ideas to build an ecosystem for people-
powered AI
5. What is a world of people-empowered AI ?
6. Black box approach versus White box
approach in using AI for HR
7. What can you do to support the
ecosystem?

We will be super human within the next 5-10 years

AI is a general purpose technology [GPT]
[Bresnahan & Trajtenberg 1995] “GPT: Engines of Growth. J. Econometrics
● Like any GPT, AI/Automation => job displacement and job creation
● Technology deployment is limited by how fast workers can be train for it.

Headlines on Government’s involvement

Interdependency of AI adoption and Labor market mismatch
Existing skillsets Existing skillsets
Required skillsets Required skillsets
Slow tech progress Fast tech progress

Reskilling, Deskilling and AI
Need for Universal Benefits Income come in to prevent a Luddites revolution.
C1
C2

Reskilling, Deskilling and AI
The inability to manage AI deployment and manage individual reskilling transition can create social
instability.

Today’s job will be Tomorrow’s composition of gigs
1. Job will recompose every 6 months with new elements that cannot be automated.
2. Job stability => High risk , high returns.

The only risk in life is not to take risks in your work
1. Security means having more access
to opportunities and having more
capabilities to translate opportunities
into income using technology.
1. Security means passive streams of
gigs.
1. Retirement doesn’t mean stop
working but means working less
gigs.

Why Universal income will become a global norm ?
1. More time for creativity, innovation and learning
1. More mental space to be entrepreneurial
a. Enable time to take risk to gain social
mobility
b. Enable inclusiveness for everyone
2. The society will be collectively better off with big
wins.
a. Trend of mega philanthropy
b. Work is a calling and giving is a blessing
3. Work become means of dignification instead of
survival

Behavior of future generations
1. Millennials or future generation are paying for experience.
a. This means they take a gig, gain new learning experience and move on.
b. By moving to many sectors, they deepen their transferable skills.
c. Most often these skills are not capture using traditional screening methods like
Resume.
2. Millennials or future generation will work for purpose.
a. This means they are willing to volunteer to work in organizations (charity,
startups) because they think their work have greater impact.
b. Universal incomes actually increase more activities in volunteerism and
working in startups in these countries.

How can we find work for displaced?
Source: Robotic, AI and Economy by Jeffery Sachs:
https://futureoflife.org/wp-content/uploads/2017/01/Jeffrey-Sachs.pdf

How can we find work for existing workers?

4 Key Ideas for government bodies
Show metrics Human capital
statements in
ACRA
Build a API
sandbox/testbed for
HR Tech startups
“It takes an
ecosystem
to raise a
nation.”
Efficient market
clearinghouse for
labor market

Successful campaigns have visible metrics to the target audience

Existing HR campaigns lack visible metrics

Adding clarity to the market
Show metrics
Source: Training in imperfect labor markets
What is the estimated increase in payroll for workers that take up training initiatives?
What is the impact of training on the company revenue within the next 12 months ?
Which sector see the biggest impact in industry output via training?
Which training institute offer the biggest impact to the specific industry?

24© 2017 Adjective and Qicstart All Rights Reserved
Lack of transparency on quantifying human capital investments
Show metrics
Time
Resources / $
Employer
offer
Applicant
need
Candidate A human
capital potential
without training
Govt
subsidy
Candidate A human capital
potential with training
If training is not effective and
cannot be indicated by a
metric , then there will always
be labor market failure.

Gurus say add metrics to initiate impact

Companies to start sharing and discussing human capital
insights like financial capital
Human capital
statements in
ACRA
The Human Capital Asset Statement
Measuring Human Capital: an Organization most valuable asset
Human capital
headcount
deployed
2015 % of all
staff
2016 % of all
staff
Leaders 10 10% 10 10%
Professional 30 30% 40 40%
Rank and file 70 70% 60 60%
Total 100 100% 100 100%

Saving time and effort to get opportunities
Enable all ATS
[ERPs] to use “one
click populate”
Talent potential >= Job
position.
Quantify match!
Click to
watch
Show companies the
ROI of training, hiring,
paying for potential
talents
“It takes an
ecosystem
to raise a
nation.”
Efficient market
clearinghouse for
labor market

API : be connected, be the hub for spokes
Build a API
sandbox/testbed for
Tech startups to
create local insights
Human Capital Database Hub
CPF
Job bank
ACRA Training
bank
Health
bank
HR Tech Hub
Public sector
Small medium enterprises, Freelancers and Investors

Vision: Unlocking human capital using tech
Now: possible in 5-10 years Now: possible in 10-20 years
Vision

Black box versus White box
Black Box
Algorithmic model
Unknown DGP
Obtain predictive accuracy
Prediction
White Box
Econometric model
Known Mechanics
Validate hypothesis +
interpretability
Causality
Source: Breiman (2001)
Suitable for HR
applications:
reward, training,
recruiting, talent
management
Suitable for HR
applications:
benefits,
employee records

Interpretability versus Accuracy

Inductive versus Deductive

Upcoming Talks
Investing in AI and
HR Tech
Individual Edition HR Portfolio
management in
the age of AI
Government
responsibilities
on human capital
in the age of AI

Contact us
Andrew Liew
https://www.linkedin.com/in/andrewliewweida/
Subscribe: ineedhelp@andrewliewweida.com

Ai revolution for human capital for government v2

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