Artificial Intelligence can increase human productivity many-fold and transform society for the better. This concept deck imagines the future of work in an age of cognitive computing.

1. The
Robots
Are
Coming,
Let’s
Reimagine
the
Humans

5. The
end
of
work?

6. Automa<on
means
less
work…
…
but
not
less
jobs
50%
increase
in
total
number
of
employed
people
Wage
rise
2.23%
faster
than
infla<on

7. Automa<on
=
higher
produc<vity…
…flaMening
out
around
the
end
of
‘00s

8. Source:
Wells
Fargo
The
big
slowdown:
Not
enough
automa<on?

9. Source:
Boston
Consul<ng
Group
Manufacturing
costs
are
on
the
rise…

10. The
Solow
Paradox
You
can
see
the
computer
age
everywhere
but
in
the
produc<vity
sta<s<cs.

11. We
need
more
automa<on!

12. The
4th
Industrial
Revolu<on:
Automa<ng
the
intellect

13. Ar<ficial
Intelligence:
key
disrup<on
areas
Natural
language
conversa<ons
Machine
Learning

14. The
automa<on
of
cogni<on
Source:
The
Future
of
Employment,
by
C.
Frey
and
M.
Osborne
47%
of
jobs
will
be
lost
to
cogni<ve
machines
in
the
next
10
years?

15. Jobs
versus
ac<vi<es
Source:
McKinsey
Interim
report
on
automa<on
of
jobs,
Nov.
2015
45%
of
job
ac<vi<es
can
be
automated
+AI
=
58%
of
job
ac<vi<es
can
be
automated
60%
of
jobs
can
have
30%
of
their
ac<vi<es
automated
Hello
Jane,
you
look
great
today!
How
can
I
help
you?

17. A
new
cyberne<c
rela<onship
Second-­‐order
cyberne<cs
in
the
era
of
machine
intelligence
Humans
and
machines
working
together:
machines
managing
complexity,
humans
providing
crea<vity
From
knowing
what
you
do
not
know
and
searching
for
it
…to
…
…not
knowing
what
you
do
not
know
and
having
“someone”
to
help
you
discover
it

18. Possible
impacts
of
4th
Industrial
Revolu<on
• Government
role
enhanced
through
Universal
Income
• Collabora<ve
Economy
creates
universal
currency
• Full-­‐<me
employees
become
Free
Agents
(“CEO
of
Me”)
• Corpora<ons
evolve
into
Value
People
Networks
• Zero
Latency
Enterprise
evolves
into
the
Responsive
Organisa<on

19. The
collabora<ve
economy
Collabora<ve
virtual
communi<es
crea<ng
value
through
exchange
and
sharing
of
products
and
services

20. Cyber-­‐physical
Systems
&
Industry
4.0
From
hierarchies
to
networks
CPS-­‐based
automa/on
Field
level
Control
(PLC)
Level
Process
Control
Level
Plant
management
Level
ERP
Level
Automa/on
hierarchy

21. Zero
Latency
Enterprise
Company
Organisa<on
Enterprise
Systems
Enterprise
Applica<ons
Enterprise
App
Integra<on
Data
Store
In
a
real
(me,
zero
latency
enterprise,
informa(on
is
delivered
to
the
right
place
at
the
right
(me
for
maximum
business
value.*
*Defini<on
of
ZLE
by
Gartner

22. The
Responsive
Organisa<on
An
agile,
client-­‐facing,
innova(ve
organiza(on
that
con(nuously
learns
and
op(mizes
talent
and
technologies
in
order
to
deliver
superior
products
and
services.
Machine
Intelligence
Applica<ons
People
Networks
Business
Systems
Learning
&
Conversa<ons
Business
Applica<ons
Business
App
Integra<on
Virtual
Data
Store

23. People
Networks:
reinven<ng
business
organisa<on
• Self-­‐organised
ad
hoc
teams
• Build-­‐in
discovery
from
design
to
customer
service
• Scaling
Agile
• Cross-­‐market
&
Cross-­‐exper<se
• Collabora<on
plaqorms
• AI
enabled
UI/UX
• Predic<ve
analy<cs

24. Getng
there:
“lead
the
work”
model
Leaders
transforming
work
in
their
organisa<on
Source:
“Lead
the
Work”
by
R.
Jesuthasan,
J.
Bourdeau,
D.
Creelman
Assignment
Organisa<on
Rewards
• Self-­‐contained
• Unlinked
• Exclusive
• Stable
• Deconstructed
Tasks
• Dispersed
• Project-­‐bound
• Constructed
Jobs
• Anchored
• Employment-­‐Bound
• Long-­‐Term
• Collec<ve
and
consistent
• Tradi<onal
• Permeable
• Interlinked
• Collabora<ve
• Flexible
• Short-­‐term
• Individualised
and
Differen<ated
• Imagina<ve
AI
enabled

25. Getng
there:
Scaling
Agile
organisa<on
Apply
agile
prac<ce
across
the
organisa<on
hMp://crowdmics.com/
hMp://crowdmics.com/
INNOVATE
DELIVER
VALIDATE
UNDERSTAND

26. Getng
there:
digital
engagement
Apply
Next
Genera<on
Integrated
Digital
Engagement
Model
(IDEM)
for
the
digital
transforma<on
of
work
Behavioural
Modelling
Human-­‐
machine
conversa<ons
AI
Interface
Data
Worker
experience
Human-­‐machine
collabora<on

27. Getng
there:
machine
intelligence
for
EX
Build
the
machine
intelligence
layer
of
the
responsive
organisa<on

28. Thank
you
George
Zarkadakis,
PhD,
CEng
@zarkadakis