Augmented Intelligence for EmTech May 2016 (Anand-final-Without Video) Presentation
1. Dr. Anand S. Rao
Partner, Innovation Lead, PwC Data & Analytics
Augmented Intelligence: The art of making
complex business decisions
05.23.16
www.pwc.com/digitalandtech
3. PwC
AI as AAAI
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Assisted Intelligence
Nature of tasks don’t change
Tasks are automated
Humans don’t learn
Machines learn
Augmented Intelligence
Nature of tasks change
Humans inform Machines
Machines inform humans
Autonomous Intelligence
Nature of tasks change
Decisions are automated
Machines learn continuously
Man-Machine Intelligence Continuum
4. PwC
Case study—Market Adoption Model for
Personal Mobility
4
01
Market entry strategies (e.g., personal mobility) are
complex business decisions with uncertain, incomplete,
and sparse data and multiple stakeholders
5. PwC
An agent-based
simulation model
captured the entire
ecosystem of players,
decisions, and
assumptions
5
Consumer Sites
Point of
Departure
(POD)
Program
Adoption
Usage
Reservation Car
Service Provider
6. PwC
The model was
calibrated to
different market
conditions of
consumer
acceptance
To account for
randomness
experienced in
dynamic
systems, each
strategy for
each city was
conducted 10
times
Over 200,000 strategic
scenarios were
simulated to explore the
‘least regret’ strategy to
enter and dominate
markets
6
Approximately 200k simulations were conducted over the course of the analysis
~6,000
Selected
simulations
Select
cities
Strategies
Market
conditions
Environ-
mental
random-
ness
Cities selected in
the previous
analysis, using a
Demographic
model and the
Demand Estimator,
were used in the
analysis
Different strategies
were tested,
varying, among
others:
Price
Aggressiveness
of Entry
Marketing
Customer Service
7. PwC
Over the course of 18
months, the combination
of human and artificial
intelligence led to a
superior understanding of
the dynamics of the
personal mobility
ecosystem modeled by an
agent-based system
7
AI: Agent-based model that captured dynamics of
driver behavior, technology advances, demand and
supply dynamics, business models, investments,
returns, advertising spend, etc.
Decision Maker: Decisions on cities to enter,
advertising spend, business model to adopt,
investments required, market share targets, learning
curve effects, etc.
Augmented Intelligence
Basic understanding of
Personal Mobility ecosystem
Good understanding of auto
buyers, drivers, and
competitive environment
Human Intelligence
No understanding of
underlying dynamics of
customer adoption,
technology changes and
regulatory impacts
Artificial Intelligence
8. PwC
Case study—Digital Advice Models
8
02
Financial Services firms are moving along the spectrum
of AAAI in developing financial advice and portfolio
management solutions
9. PwC
PwC has developed a
proprietary synthetic
population with
household level
financial statements for
330 million US
individuals using
multiple data sources
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Household
financial
statement
01
Balance sheet –
Assets & Liabilities
02
Income statement –
Income & Expenses
03
Demographics /
Family Structure
04
Behavioral
Preferences
10. PwC
Cradle-to-
Grave
Simulations
Scenario-
based
Planning
PwC’s $ecureTM is a
cognitive digital-advisor
built as an agent-based
simulation model that
projects complex financial
decisions of households
from cradle-to-grave
10
Behavioral
Economics &
Simulation
3
4
5
$ecureTM
Synthetic US
Population
/Household
Holistic
Household
View
2
1
11. PwC
Personalized cradle-to-
grave simulation of 330
million consumer agents
informs an ongoing
holistic financial planning
and execution process
between the Advisor,
Consumer, and the
$ecureTM platform
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• AI: Agent-based model that captured dynamics of
economy, market returns, individual investor needs,
behavior, health shocks, specific product characteristics,
product actions, etc.
• Consumer: Decisions on how to satisfy goals, savings
vs spending, when to retire, risk appetite, etc.
• Advisor: Asset class selection, portfolio optimization,
holistic advice, fiduciary role
Augmented Intelligence
Consumer: Low-to-medium
knowledge of investing
Advisor: Medium-to-high
level of knowledge & expertise
Human Intelligence
No understanding of
underlying dynamics of
economy, market, or
investor behavior
Artificial Intelligence
12. PwC’s Digital Services
Augmented Intelligence
Agent-based
simulation offers a
viable approach for
enterprises to capture
the underlying
structure and behavior
of decision-makers
Initially the agents
embody the human
insights, but as the
simulation unfolds the
emergent behavior
informs the humans
on the importance of
the structure/behavior
of the ecosystem
As the system
continuously reacts
to stimuli from the
external world it
learns and adapts
to changing
circumstances and
its own errors
Humans and
machines are in a
symbiotic relationship
where each is
continuously
improving based on
the interaction with
the other embodying
true augmented
intelligence
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