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The acceleration of disruption
David Wood, @dw2
Chair of London Futurists
Principal, Delta Wisdom
Opportunities and threats for construction
Robots threaten 15M UK jobs, says Bank of England's chief economist
“Admin, clerical and production
tasks most at threat”
50%
The Guardian@dw2
137M (56% of salaried workforce) from 5 SE Asian countries at high-risk
Cambodia,
Indonesia,
the
Philippines,
Thailand
and
Vietnam
Straits Times@dw2
Foxconn factory employees reduced from 110k to 50k, thanks to robots
Kunshan, in Jiangsu province
South China MP@dw2
“Computerisation should have little effect on the
percentage of the work force engaged in these tasks…
“Non-routine manual tasks: physical tasks that
cannot be well-described as following a set of If-
Then-Else rules, because they require optical
recognition and fine motion control that have proven
extremely difficult for computers to carry out…”
“Examples include driving a truck…
Frank Levy
MIT
Richard J. Murnane
Harvard
@dw2
Completed <5%
of the course
Sandstorm: Winner of 2004 DARPA Grand Challenge
150 miles in
the Mojave
Desert region
of the US
2005 Challenge:
Five vehicles
completed whole
course


@dw2
Truck drivers Taxi drivers
Insurance
salespeople
Lots of other professions?
…
Creative professions?
Professions with human insight?
Self-driving flying cars!
@dw2
https://anticipating2025.com/preliminary-information/previews/
“What’s interesting in Go is that
there’s been a lot of progress in the
last decade…
“The best Go programs are now at a
stage where they can give a few
stones handicap to a top Go player, a
world-class Go player, and beat him.
“This has happened quite recently -
much to the amazement to the top
Go players.
“I would guess that we are 20 years
away from having a Go program that
can play at a level equivalent to
Kasparov or Carlsen.”
David Levy 1976 Interviewed in Dec 2013
1968 (£1,250) -> 1978  -> 1983 ($1,000)  -> 1989  (Deep Thought) -> 1997  (Kasparov)
@dw2
AI, Deep Learning
=> Pattern detection
(Artificial Intuition)
2016
AlphaGo 4,
Lee Sedol 1
@dw2
The third machine age
1. Machines replaced human muscular effort
– They manipulated energy
– They produced motion
2. Then machines replaced human calculation effort
– They manipulated information (using algorithms)
– They produced numerical results
3. Machines are now replacing human creative effort
– They manipulate “learning data” to reveal cause-effect patterns
– They produce algorithms (using information)
– They progress from a seed algorithm to unexpected new insight
@dw2
“A group of young people playing Frisbee”
AI, Deep Learning
=> Computer vision
@dw2
“A person riding a motorcycle on a dirt road”
@dw2
“A yellow bus driving
down a road with green
trees and green grass in
the background”
Photo via
Andrew Ng,
Chief Scientist,
Baidu
@dw2
BN
CI
NBIC Convergence
Atoms Genes
Bits Neurons
Bio-
Tech
Nano-
Tech
Cogno-
Tech
Info-
Tech
Software
Hardware
BiologyPhysical
Performance-enhancing drugs
Nootropics
Cognotech: IA
BN
CI
Performance-enhancing headsets
“This Startup Gets You High On Dopamine, No Exercise Required”
@dw2
Augmented
Reality (AR)
via smart
glasses
@dw2
“Smart Glasses Market 2015” – report from AugmentedReality.ORG
@dw2
“Towards 1 Billion
Shipments
… within 10 years”
– Ori Inbar
Glasses phase 1 -> phase 2 -> phase 3 -> phase 4…
@dw2
Design,
Manufacturing
Computers
Positive feedback cycles
@dw2
Software tools
(debuggers,
compilers…)
Software
Positive feedback cycles
@dw2
AI tools
AI
Positive feedback cycles
@dw2
Education
Technology
Positive feedback cycles
@dw2
People
Technology
Education
Networks
Tools
Positive
feedback
cycle
Designers
Entrepreneurs
Engineers
EducatorsIntegrators
Artificial Intelligence Deep Learning
The acceleration of technology
The acceleration of disruption
1. Improve your strategic reviews
2. Improve your foresight skills and trend
management
3. Practice agile futurism
4. Practice collaborative futurism
Surviving accelerated disruption:
Four takeaways
@dw2
Implications for strategy
Strategy = choice: what you’ll do, and what you’ll not do
Strengths
Weaknesses
Opportunities
Threats
Sources of upside
Sources of downside
Internal
(company)
External
(environment)
Forthcoming
Opportunities
Forthcoming
Threats
Future
(scenarios)
Strategy = preparation: readiness for key changes
SWOT
Increasingly crucial
@dw2
Opportunities
Threats
The set of
possible
future
scenarios
Foresight… … is hard
Acceleration of
technology
Multi-convergence
of factors
Business as usual
Trend management: seeing what’s credible
1. Identifying trends: establish your catalogue of trends
– Technological trends
– Social trends
– Political trends
2. Cultivate sources of insight
– Customer insight
– Competitor insight
– Employee insight
– Research insight
– Futurist insight
3. Build and review scenarios
– Combinations of trends – both disruptive and incremental
– Consider what to put in, and what to leave out (e.g. formerly key DNA!)
=> Decide what’s desirable
Gain insight
in stages
@dw2
Inertia (Waterfall)
• Elaborate planning
• Painstaking execution
• Stick to the plan!
• Big Design Up Front
• Executives’ intuition
• Secrecy
• Execute a single scenario
• Typically disappoint market
Agile / Lean
• Experimentation
• Sprints deliver incrementally
• Be ready to pivot!
• Iterative Design
• Customer feedback
• Customer feedback
• Search for insight on scenarios
• Anticipate market delight
(early & often)
26/09/2016 30
@dw2
Drawback of non-Agile execution
What the market
would, in the end,
like to have
What the initial plan
estimated the
market would like
Time
in the (non-agile) case
when “the plan is king”
Delivery
Measure of
market
dissatisfaction
Don’t lock into
scenarios too
early
@dw2
With Agile development
(and regular customer feedback)
What the market
would, in the end,
like to have
What the initial plan
estimated the
market would like
Time
following agile
(adaptive) planning
Delivery
Measure of
market
delight
Improve your foresight
planning with regular
feedback from wider circle
@dw2
People
Technology
Education
Networks
Tools
Positive
feedback
cycle
Designers
Entrepreneurs
Engineers
Futurists!
Scenarios
EducatorsIntegrators
1. Improve your strategic reviews
– Futurist perspectives add a third column to strategy reviews
2. Improve your foresight skills and trend management
– Trend analysis, consider interactions
– Create & assess multiple scenarios
– Identify “canary signals” in advance
3. Practice agile futurism
– Review your trends and scenarios (at least) once each quarter
– Fail fast, fail smart, fail forward – pivot to new experiment
4. Practice collaborative futurism
– Benefit from the positive feedback cycle for foresight
– Prepare for “smart acquisitions” if fast changes make them necessary
Positive
feedback
cycle
Surviving accelerated disruption:
Four takeaways Intelligent sustainable
visionary urgency
@dw2
Source material for preceding slides
2 http://www.theguardian.com/business/2015/nov/12/robots-threaten-low-paid-jobs-says-bank-
of-england-chief-economist
3 http://www.straitstimes.com/business/millions-of-southeast-asian-jobs-may-be-lost-to-
automation-in-next-two-decades-ilo
4 http://www.scmp.com/news/china/economy/article/1949918/rise-robots-60000-workers-
culled-just-one-factory-chinas
5 http://www.amazon.com/The-New-Division-Labor-Computers/dp/0691119724
6 http://en.wikipedia.org/wiki/DARPA_Grand_Challenge
7 http://telematicswire.net/self-drving-cars-after-google-its-baidu-carmakers-and-technology-
companies-competing-together/
8 https://www.youtube.com/watch?v=q-Rk6rtLc-E
11,12 https://medium.com/backchannel/google-search-will-be-your-next-brain-5207c26e4523
13 http://www.slideshare.net/ExtractConf/andrew-ng-chief-scientist-at-baidu
@dw2
Source materials (continued)
17 http://futurism.com/this-startup-gets-you-high-on-dopamine-no-exercise-required/
18 https://itunes.apple.com/us/app/golfscape-gps-rangefinder/id382051762
20 “Smart Glasses Market 2015” – report from AugmentedReality.ORG
Further reading
londonfuturists.com
deltawisdom.com
Blog dw2blog.com
@dw2

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The acceleration of disruption: opportunities and threats for construction - David Wood (London Futurists) #COMIT2016

  • 1. The acceleration of disruption David Wood, @dw2 Chair of London Futurists Principal, Delta Wisdom Opportunities and threats for construction
  • 2. Robots threaten 15M UK jobs, says Bank of England's chief economist “Admin, clerical and production tasks most at threat” 50% The Guardian@dw2
  • 3. 137M (56% of salaried workforce) from 5 SE Asian countries at high-risk Cambodia, Indonesia, the Philippines, Thailand and Vietnam Straits Times@dw2
  • 4. Foxconn factory employees reduced from 110k to 50k, thanks to robots Kunshan, in Jiangsu province South China MP@dw2
  • 5. “Computerisation should have little effect on the percentage of the work force engaged in these tasks… “Non-routine manual tasks: physical tasks that cannot be well-described as following a set of If- Then-Else rules, because they require optical recognition and fine motion control that have proven extremely difficult for computers to carry out…” “Examples include driving a truck… Frank Levy MIT Richard J. Murnane Harvard @dw2
  • 6. Completed <5% of the course Sandstorm: Winner of 2004 DARPA Grand Challenge 150 miles in the Mojave Desert region of the US 2005 Challenge: Five vehicles completed whole course   @dw2
  • 7. Truck drivers Taxi drivers Insurance salespeople Lots of other professions? … Creative professions? Professions with human insight? Self-driving flying cars! @dw2
  • 8. https://anticipating2025.com/preliminary-information/previews/ “What’s interesting in Go is that there’s been a lot of progress in the last decade… “The best Go programs are now at a stage where they can give a few stones handicap to a top Go player, a world-class Go player, and beat him. “This has happened quite recently - much to the amazement to the top Go players. “I would guess that we are 20 years away from having a Go program that can play at a level equivalent to Kasparov or Carlsen.” David Levy 1976 Interviewed in Dec 2013 1968 (£1,250) -> 1978  -> 1983 ($1,000)  -> 1989  (Deep Thought) -> 1997  (Kasparov) @dw2
  • 9. AI, Deep Learning => Pattern detection (Artificial Intuition) 2016 AlphaGo 4, Lee Sedol 1 @dw2
  • 10. The third machine age 1. Machines replaced human muscular effort – They manipulated energy – They produced motion 2. Then machines replaced human calculation effort – They manipulated information (using algorithms) – They produced numerical results 3. Machines are now replacing human creative effort – They manipulate “learning data” to reveal cause-effect patterns – They produce algorithms (using information) – They progress from a seed algorithm to unexpected new insight @dw2
  • 11. “A group of young people playing Frisbee” AI, Deep Learning => Computer vision @dw2
  • 12. “A person riding a motorcycle on a dirt road” @dw2
  • 13. “A yellow bus driving down a road with green trees and green grass in the background” Photo via Andrew Ng, Chief Scientist, Baidu @dw2
  • 17. Performance-enhancing headsets “This Startup Gets You High On Dopamine, No Exercise Required” @dw2
  • 19. “Smart Glasses Market 2015” – report from AugmentedReality.ORG @dw2
  • 20. “Towards 1 Billion Shipments … within 10 years” – Ori Inbar Glasses phase 1 -> phase 2 -> phase 3 -> phase 4… @dw2
  • 26. 1. Improve your strategic reviews 2. Improve your foresight skills and trend management 3. Practice agile futurism 4. Practice collaborative futurism Surviving accelerated disruption: Four takeaways @dw2
  • 27. Implications for strategy Strategy = choice: what you’ll do, and what you’ll not do Strengths Weaknesses Opportunities Threats Sources of upside Sources of downside Internal (company) External (environment) Forthcoming Opportunities Forthcoming Threats Future (scenarios) Strategy = preparation: readiness for key changes SWOT Increasingly crucial @dw2
  • 28. Opportunities Threats The set of possible future scenarios Foresight… … is hard Acceleration of technology Multi-convergence of factors Business as usual
  • 29. Trend management: seeing what’s credible 1. Identifying trends: establish your catalogue of trends – Technological trends – Social trends – Political trends 2. Cultivate sources of insight – Customer insight – Competitor insight – Employee insight – Research insight – Futurist insight 3. Build and review scenarios – Combinations of trends – both disruptive and incremental – Consider what to put in, and what to leave out (e.g. formerly key DNA!) => Decide what’s desirable Gain insight in stages @dw2
  • 30. Inertia (Waterfall) • Elaborate planning • Painstaking execution • Stick to the plan! • Big Design Up Front • Executives’ intuition • Secrecy • Execute a single scenario • Typically disappoint market Agile / Lean • Experimentation • Sprints deliver incrementally • Be ready to pivot! • Iterative Design • Customer feedback • Customer feedback • Search for insight on scenarios • Anticipate market delight (early & often) 26/09/2016 30 @dw2
  • 31. Drawback of non-Agile execution What the market would, in the end, like to have What the initial plan estimated the market would like Time in the (non-agile) case when “the plan is king” Delivery Measure of market dissatisfaction Don’t lock into scenarios too early @dw2
  • 32. With Agile development (and regular customer feedback) What the market would, in the end, like to have What the initial plan estimated the market would like Time following agile (adaptive) planning Delivery Measure of market delight Improve your foresight planning with regular feedback from wider circle @dw2
  • 34. 1. Improve your strategic reviews – Futurist perspectives add a third column to strategy reviews 2. Improve your foresight skills and trend management – Trend analysis, consider interactions – Create & assess multiple scenarios – Identify “canary signals” in advance 3. Practice agile futurism – Review your trends and scenarios (at least) once each quarter – Fail fast, fail smart, fail forward – pivot to new experiment 4. Practice collaborative futurism – Benefit from the positive feedback cycle for foresight – Prepare for “smart acquisitions” if fast changes make them necessary Positive feedback cycle Surviving accelerated disruption: Four takeaways Intelligent sustainable visionary urgency @dw2
  • 35. Source material for preceding slides 2 http://www.theguardian.com/business/2015/nov/12/robots-threaten-low-paid-jobs-says-bank- of-england-chief-economist 3 http://www.straitstimes.com/business/millions-of-southeast-asian-jobs-may-be-lost-to- automation-in-next-two-decades-ilo 4 http://www.scmp.com/news/china/economy/article/1949918/rise-robots-60000-workers- culled-just-one-factory-chinas 5 http://www.amazon.com/The-New-Division-Labor-Computers/dp/0691119724 6 http://en.wikipedia.org/wiki/DARPA_Grand_Challenge 7 http://telematicswire.net/self-drving-cars-after-google-its-baidu-carmakers-and-technology- companies-competing-together/ 8 https://www.youtube.com/watch?v=q-Rk6rtLc-E 11,12 https://medium.com/backchannel/google-search-will-be-your-next-brain-5207c26e4523 13 http://www.slideshare.net/ExtractConf/andrew-ng-chief-scientist-at-baidu @dw2
  • 36. Source materials (continued) 17 http://futurism.com/this-startup-gets-you-high-on-dopamine-no-exercise-required/ 18 https://itunes.apple.com/us/app/golfscape-gps-rangefinder/id382051762 20 “Smart Glasses Market 2015” – report from AugmentedReality.ORG Further reading londonfuturists.com deltawisdom.com Blog dw2blog.com @dw2