Presentation by Zheng Choo, Turner & Townsend at the 2019 COMIT Conference. More information: http://www.comit.org.uk/conference-2019

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Zheng Choo
Associate Director, Data & Analytics
From waste to wealth…

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Who am I?
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Zheng Choo
 Associate Director
 Data & Analytics
 Regional operational lead for
Technology
Remit
 Lead a professional services business
 Horizon scanning and disruption of the wider
Turner & Townsend
 Upskill and develop our clients and supply
chain
90
Technology
team
members
Diverse skills
Architect / Engineering
Construction
Asset Managers
Cost and commercial
Data science
Military security
>300
Projects
delivered
8
Global
regions

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What am I talking about?
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Artificial Intelligence…
and the commoditisation of Natural Stupidity…
in construction!

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What am I talking about?
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Artificial Intelligence…
“the theory and development of computer systems able to perform
tasks normally requiring human intelligence, such as visual
perception, speech recognition, decision-making, and translation
between languages.”

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What are we interested in?
 Tangible
 Relatable
 Commercially viable
 Applicable
 Accessible
 Valuable
 Scalable
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Basics
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AI
Machine Learning
Deep learning
Any technique enabling computers to
mimic human behaviour
Subset of AI which uses statistical
methods to enable machines to
improve with experience
Subset of ML which make neural
networks that can look for trends
and learn on their own

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1950
In 1950 Turing posed the
question “can machines
think?”,
1973 The Lighthill report and
the AI winter, progress in the
field was not as fast as had
been expected.
1997 Deep Blue beats
the reigning world
champion at chess
18thC
Development
of statistical
methods
1956 The Dartmouth Workshop
gave birth to the term ‘artificial
intelligence’ (John McCarthy)
1992 Playing
backgammon
2016 AlphaGo
beats the world
champion at Go
A brief history
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2020201020001990198019701960195018thC
MACHINE LEARNING: THE POWER AND PROMISE OF COMPUTERS THAT LEARN BY EXAMPLE

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Are we in the race…
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McKinsey

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“one of the most important things that
humanity is working on. It’s more
profound than, I don’t know, electricity or
fire,”
Sundar Pichai, CEO Google
Self
actualisation
Psychological
Physiological Fire Electricity
AI?
Habitat

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Grand challenges
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Artificial
Intelligence and
data
Aging society Clean growth Future mobility

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AI sector deal & global
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China
 Investing $7Bn in AI development by 2030, including a $2Bn
innovation park
 Targeting an AI industry of $150Bn
United States
 Primarily developing with industry academic partners
 US AI chip industry is forecast to be $35Bn by 2021
UK
 Public-private partnership targeting £200m AI investment
 UK Gov funding 1,000 PhDs with Cambridge and Oxford leading
Germany
 Already a hub for AI start-ups and developers, with a commitment
from the government to compete with China
 AI campus being completed in Tubingen

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I have questions…
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Where should we spend that money in our sector?
Is there a list of the most stupid and wasteful things we do?
Is it enough of an embarrassment for us to start acting?
Does AI have the potential to impact us, moving from
emergent to mainstream, and do we have anywhere near
enough data?

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So what happens when construction gets more data
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FederateCommunicate
Act / DO Forecast and Insight
Analyse
Create
Use Analytics
Gather Data
Physical Digital

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I have questions…
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Do we really think we are clever enough to understand all
the data by ourselves?
Are we prepared for the same social backlash and ethical
questions that others are facing (driverless cars, social
media)?
With great power… comes great responsibility…

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Leading edge digital asset lifecycle management
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Turner & Townsend AMCL

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Bleeding edge digital asset lifecycle management
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Turner & Townsend AMCL

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Tool box
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Data Preparation and
Analysis tools
Automatically extract and
integrate data from
disparate sources for
analysis
Workflow Automation
Software
Automates work stream
delivery find efficiencies in
workflows
Rule Engines
Define or identify the
business riles that
govern tasks or
processes
Software Macros
Automate rule-based
activities within a single
application
Robotic process automation
Automate repetitive activities across
multiple systems via software robots
that replicate a users workflow
Machine Learning
Trained algorithms that make
decisions as part of an automated
process flow
Intelligent process automation
platform
identify patterns and learn over time
to optimize automated workflows
Predictions
Automation of predictions in data for
workflows, data extrapolation and
process
Medical Diagnosis
Trained algorithms that can make a
diagnosis based on input medical
data
Cybersecurity
Determination of unusual cyber
activity surrounding an activity or
organisation
Risk Determination
Determination of risk determined by
input factors, previous outcomes
and specialist knowledge
Generative Design
Technology method that mimics
nature’s evolutionary approach to
design. Starting with design goals,
iterating through solutions to find
optimal outcomes
Natural Language Processing
Algorithms that process natural
speech or text input
Intelligent Business Process
Management Systems
Manage work allocation between
humans and machines across
multiple automation
technologies
Image Recognition
Automate capture of images and
document information and process
the information
Trend Analysis and Prediction
Automated trend analysis based on
existing data and knowledge of
current trends and knowledge
Gartner

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The backdrop for development
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Augment
To make or become greater in
number, amount, strength,
intelligence?
Automate
technique, method, or system of operating
or controlling a process by highly automatic
means, as by electronic devices, reducing
human intervention to a minimum.
Autosuggest
To influence one's own thoughts or
behaviour through methods other than
conscious thought
Turner & Townsend AMCL

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Need opportunity solution analysis
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Virtual Assistant
Complex information,
simple interface
Natural Language
Processing
Procurement
Efficiency and accuracy,
objective appointments
3D computer vision /
Supervised learning
Safety Monitoring
Safe workplace, enhanced
wellbeing
Image recognition / Risk
determination / Medical
diagnosis
Open data platform
Controlled, curated and
managed through AI
Workflow automation / RPA /
Risk determination / Cyber
security
Design justification and
concept generation
Design type DNA (seed)
generated with context data
Data preparation & analysis
tools / RPA / Generative Design
Auto-generative design
patterns
Optimised design patterns and
off-site manufacturing
Generative design / Intelligent
process automation
Whole life cost analysis
Generative cost modelling, built
on predictive market analytics
and legislation analysis
Data preparation &analysis tools
/ Predictions / Machine learning
Brief development
Improved certainty and objective
decisions based on big data
Data preparation & analysis tools
/ Machine learning / Risk
automation

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Need opportunity solution analysis
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Digital Twin Building
Sanitise, aggregate and communicate
information as a public service
RPA / 3D computer vision / Intelligent
process automation / Natural language
Processing / Cyber security
Asset risk analysis and mitigation
Analysis and improvement of asset
maintenance and mitigation of failure
Machine learning / Supervised learning /
Risk determination / Predictions
Intelligent assets
More efficient management, maintenance and
use of assets
Workflow automation / Image recognition /
Trend analysis and prediction / Natural
language processing
Field based operations
Automated logistics planning for assets,
parts, people and equipment
Data preparation & analysis tools / RPA /
Predictions / Rule engines
System analysis and intuitive dash
boarding
Real-time trending, moving from what
happened to what will happen
Predictions / RPA / Supervised and
unsupervised learning
Task vs Actual
Schedule generation, simulation,
optimisation and tracking
Rule engines / Generative design /
Machine learning

28. Turner & Townsend
What should you do?
1. Listen… and don’t panic!
2. Work out where the low hanging fruit is for you, and just think about where to start.
3. Dedicate some investment into your digital initiatives NOW!
4. Look to other sectors/industries and recognise we can learn from them.
5. Start talent mining and promote growth mind-set to broaden capability
6. Have a plan for AI and make someone accountable
7. Come to terms with the idea of aiming for a moving target
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