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C r i t i c a l T h i n k i n g
For Engineers
& Managers
P e t e r C o c h r a n e
cochrane.org.uk
ca-global.biz
Beyond the linear and simple
May 2017
o u r f o r m a l e d u c at i o n
Is all about the known the well understood
“What we can model and characterise
forms the bedrock of our most
basic understandings founded
on the strongest of scientific
principals - tried & tested
results over millennia”
It is the best formula our species
has derived - and responsible for
all human progress - all other
routes lead to belief systems -
witchcraft and general ignorance
“Whilst it is quite acceptable for the mathematicians,
physicists (et al) to declare that a problem cannot be solved -
we ENGINEERS enjoy no such luxury - we always have to get
an answer”
a u n i v e r s e o f t h e u n k n o w n
How much does our formal education prepare us for this ?
“As a young student coming into
industry I thought I knew and
understood a lot and I was well
prepared to tackle anything”
“I quickly realised that this was
not the case and my real education
was just about to start - and I am
still a student”
Where we are educated
What we understand well
Where we can solve problems
A mostly linear & well behaved space
What we know we know
What we know we don’t know
What we don’t know we don’t know
What we don’t know
What we know
Unknown ??? =
N o n l i n e a r u n i v e r s e
We have no generally applicable solutions
Our mathematics is limited to ‘Order 5’ at best
Our visualisation only extends to ~ 4 dimensions
Our simultaneous variable tracking is generally <7
Our linear problem sets are mostly bounded and trivial
Our non- linear problem sets mostly unbounded & complex
Our simultaneous variable tracking capability is generally <7
Sheer computing power and modelling dominate
Point solutions abound and we have to avoid misuse
The non-linear domain demands new approaches/thinking
t h e e n g i n e e r i n g t o o l b o x
Finding workable solutions can be really challenging
- Does a solution already exist?
- Has anyone else tackled the problem before?
- Do scientific/engineering papers report similar problem sets
- Apply basic analysis exploiting results of paper/people search
- Apply advanced analysis/modelling on the basis of the previous step
If none of the above works, then:
- Ask - what might a reasonable solution set be?
- Apply iteration starting from a best estimate/guess
- Conduct detailed experiments to gather data points
- Iterate toward a workable solution
d e c i s i o n T I M E
Fail fast and adapt even faster
In the face of incomplete data and/
or information - and facing a big
d e c i s i o n d e a d l i n e - m a k e a
decision and adapt rapidly to the
outcome…ie best guess followed by
iterations..
“ E v o l u t i o n f a v o u r s t h e m o s t
adaptable and not the strongest or
the smartest”
s i m p l e s y s t e m s
Generally within the grasp of a single mind
α
Output ≈ Input (Energy)
Directly related/predictable
Can be conceived, designed and (sometimes)
built by a single person
C O M P L i c at e d s y s t e m s
Generally beyond the grasp of a single mind
Output ≈ Input (Energy)
Directly related/predictable
Might be conceived by a single person, but
(nearly always) designed and built by a team
C O M P L E X s y s t e m s
Generally demands far more than human minds
Output ≈ Input (Energy or State)
Not directly related/predictable
Individual components may be simple, linear, well
behaved, conceived, designed and (sometimes)
built by a single person, BUT the sum of the parts
can and exhibit unexpected and unpredictable
behaviours
Medical conditions
Teleco Networks
Weather systems
Financial systems
Mobile networks
Political systems
Mobile networks
Power grids
Internet
Conflict
Warfare
IoT
BMOD
Strokes
Missiles
Rockets
Flooding
Tsunamis
Landslides
Earthquakes
Crime waves
F1 racing cars
Fighter aircraft
++++++
No top down design
Impossible to specify
Impossible to design
Difficult to model
Easy/Hard to realise
Easy/Hard to control
Easy/Hard to operate
Unpredictable
Evolves + Adaps
Always Changing
Unstable/Stable
Emergent behaviours
Beyond human grasp and abilities
Established wisdoms do not apply
Mathematics no longer works
No general laws
C O M P L E X i t y
Governs the universe and all life
Only ever Evolves/Grows/Builds
from small to big
simple to complex
And NEVER the converse
s p r e a d M o d e
Biological & man made commonality
Virus
Meme
Desease
Malware
AXIOM...still not understood by many...
Taking an interest in every system known to mankind pays dividends in
providing us with insights and challenging concepts and occasionally ,
really useful results...
..and we no longer design, deploy and operate our systems in
isolation...we live in a world of natural and unnatural
systems... evolved and designed...
...and the way they connect coexist and interact is important
especially when life dependency and mission critical issues
are at stake !
Only we design & optimise - evolution rests at good enough
“We often appear use vastly complex solutions to
achieve incredibly simple outcomes…whilst Mother
Nature mostly seems to do the converse”
B I G D i f f e r e n c e s
“Mother Nature cannot do what we do,
but then she is still confounding us”
Only goes for ‘good enough’ and optimises nothing
She conceals her underlying complexity at
every level of her constructs and activity...
M o t h e r N a t u r e
Her systems are resilient or they rapidly die
out..
The over optimisation of
companies and organisations
in a fast evolving field
leads to their certain demise
Defining ‘good enough’ is not always trivial
and is generally the biggest challenge !
~80% of the need satisfied by ~20% of
the effort….and then often destroyed/
devalued by specification creep….
P e r f e c t i o n
The enemy of good enough
Just because we can add something extra
does not mean we should….we have to
think in terms of the value to be realised…
Analogue dominant
Digital spreading fast
Hybrid Analogue//Digital ubiquitous
What we know advancing rapidly
Our understanding mathematically limited
Made by mankind we all die without them
Made by machine we all die without them
Our species survival depends upon good systems
Our planets survival depends upon good systems
Machine intelligence overtaking us in many areas
Symbiosis necessary man machine partnerships
Challenges formidable but interesting
G e n e r a l i t i e s
The technology/engineering status quo
Stored information growth
1986
I can’t draw a
dot small
enough!!
.
1996
0.001ZB
2006
0.13ZB
2016
13ZB
Impossible to read everything professional for >50 years
ZetaByte = 1021 ExaB = 1018 PetaB = 1015 TeraB = 1012
Prognosis: IoT small data distributed
storage may exceed the
internet
>20M texts available
<3M selected for analysis
Argument abstracted pro - con
No human resource can
do this !
THE BOX
In, out, or new ?
You can think
inside the box
OR You can create
an entirely
new box !
You can think
outside the box
DIVERSITY
Mostly essential
Capable people of differing
ethnics groups; social, education
industry experiences; with a wide
range of discipline differences
and diverse modes of thinking
Proven AI engines, modelling and
visualisation tools are useful
augmentations to help/overcome
the limitations of human thinking
It is never too late to stop
everything, abandon a given path
and start again
Search out and identify all those
who may be able to help you and
form a (real/virtual) team
STATUS QUO
Breaking new ground
“If it your problem were simple,
someone would have solved it a
long time ago”
“Be prepared to consider and
employ the radical, the new,
and even the crazy”
PENUMBRA/Thoughts
Your chance to ask questions and discuss
cochrane.org.uk
ca-global.biz
For more presentations, papers and videos
on this topic GOTO: www.cochrane.org.uk
May 2017

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Critical Thinking for Engineers and Managers

  • 1. C r i t i c a l T h i n k i n g For Engineers & Managers P e t e r C o c h r a n e cochrane.org.uk ca-global.biz Beyond the linear and simple May 2017
  • 2. o u r f o r m a l e d u c at i o n Is all about the known the well understood “What we can model and characterise forms the bedrock of our most basic understandings founded on the strongest of scientific principals - tried & tested results over millennia” It is the best formula our species has derived - and responsible for all human progress - all other routes lead to belief systems - witchcraft and general ignorance “Whilst it is quite acceptable for the mathematicians, physicists (et al) to declare that a problem cannot be solved - we ENGINEERS enjoy no such luxury - we always have to get an answer”
  • 3. a u n i v e r s e o f t h e u n k n o w n How much does our formal education prepare us for this ? “As a young student coming into industry I thought I knew and understood a lot and I was well prepared to tackle anything” “I quickly realised that this was not the case and my real education was just about to start - and I am still a student” Where we are educated What we understand well Where we can solve problems A mostly linear & well behaved space What we know we know What we know we don’t know What we don’t know we don’t know What we don’t know What we know Unknown ??? =
  • 4. N o n l i n e a r u n i v e r s e We have no generally applicable solutions Our mathematics is limited to ‘Order 5’ at best Our visualisation only extends to ~ 4 dimensions Our simultaneous variable tracking is generally <7 Our linear problem sets are mostly bounded and trivial Our non- linear problem sets mostly unbounded & complex Our simultaneous variable tracking capability is generally <7 Sheer computing power and modelling dominate Point solutions abound and we have to avoid misuse The non-linear domain demands new approaches/thinking
  • 5. t h e e n g i n e e r i n g t o o l b o x Finding workable solutions can be really challenging - Does a solution already exist? - Has anyone else tackled the problem before? - Do scientific/engineering papers report similar problem sets - Apply basic analysis exploiting results of paper/people search - Apply advanced analysis/modelling on the basis of the previous step If none of the above works, then: - Ask - what might a reasonable solution set be? - Apply iteration starting from a best estimate/guess - Conduct detailed experiments to gather data points - Iterate toward a workable solution
  • 6. d e c i s i o n T I M E Fail fast and adapt even faster In the face of incomplete data and/ or information - and facing a big d e c i s i o n d e a d l i n e - m a k e a decision and adapt rapidly to the outcome…ie best guess followed by iterations.. “ E v o l u t i o n f a v o u r s t h e m o s t adaptable and not the strongest or the smartest”
  • 7. s i m p l e s y s t e m s Generally within the grasp of a single mind α Output ≈ Input (Energy) Directly related/predictable Can be conceived, designed and (sometimes) built by a single person
  • 8. C O M P L i c at e d s y s t e m s Generally beyond the grasp of a single mind Output ≈ Input (Energy) Directly related/predictable Might be conceived by a single person, but (nearly always) designed and built by a team
  • 9. C O M P L E X s y s t e m s Generally demands far more than human minds Output ≈ Input (Energy or State) Not directly related/predictable Individual components may be simple, linear, well behaved, conceived, designed and (sometimes) built by a single person, BUT the sum of the parts can and exhibit unexpected and unpredictable behaviours Medical conditions Teleco Networks Weather systems Financial systems Mobile networks Political systems Mobile networks Power grids Internet Conflict Warfare IoT BMOD Strokes Missiles Rockets Flooding Tsunamis Landslides Earthquakes Crime waves F1 racing cars Fighter aircraft ++++++
  • 10. No top down design Impossible to specify Impossible to design Difficult to model Easy/Hard to realise Easy/Hard to control Easy/Hard to operate Unpredictable Evolves + Adaps Always Changing Unstable/Stable Emergent behaviours Beyond human grasp and abilities Established wisdoms do not apply Mathematics no longer works No general laws C O M P L E X i t y Governs the universe and all life Only ever Evolves/Grows/Builds from small to big simple to complex And NEVER the converse
  • 11. s p r e a d M o d e Biological & man made commonality Virus Meme Desease Malware
  • 12. AXIOM...still not understood by many... Taking an interest in every system known to mankind pays dividends in providing us with insights and challenging concepts and occasionally , really useful results... ..and we no longer design, deploy and operate our systems in isolation...we live in a world of natural and unnatural systems... evolved and designed... ...and the way they connect coexist and interact is important especially when life dependency and mission critical issues are at stake !
  • 13. Only we design & optimise - evolution rests at good enough “We often appear use vastly complex solutions to achieve incredibly simple outcomes…whilst Mother Nature mostly seems to do the converse” B I G D i f f e r e n c e s “Mother Nature cannot do what we do, but then she is still confounding us”
  • 14. Only goes for ‘good enough’ and optimises nothing She conceals her underlying complexity at every level of her constructs and activity... M o t h e r N a t u r e Her systems are resilient or they rapidly die out.. The over optimisation of companies and organisations in a fast evolving field leads to their certain demise
  • 15. Defining ‘good enough’ is not always trivial and is generally the biggest challenge ! ~80% of the need satisfied by ~20% of the effort….and then often destroyed/ devalued by specification creep…. P e r f e c t i o n The enemy of good enough Just because we can add something extra does not mean we should….we have to think in terms of the value to be realised…
  • 16. Analogue dominant Digital spreading fast Hybrid Analogue//Digital ubiquitous What we know advancing rapidly Our understanding mathematically limited Made by mankind we all die without them Made by machine we all die without them Our species survival depends upon good systems Our planets survival depends upon good systems Machine intelligence overtaking us in many areas Symbiosis necessary man machine partnerships Challenges formidable but interesting G e n e r a l i t i e s The technology/engineering status quo
  • 17. Stored information growth 1986 I can’t draw a dot small enough!! . 1996 0.001ZB 2006 0.13ZB 2016 13ZB Impossible to read everything professional for >50 years ZetaByte = 1021 ExaB = 1018 PetaB = 1015 TeraB = 1012 Prognosis: IoT small data distributed storage may exceed the internet
  • 18. >20M texts available <3M selected for analysis Argument abstracted pro - con No human resource can do this !
  • 19. THE BOX In, out, or new ? You can think inside the box OR You can create an entirely new box ! You can think outside the box
  • 20. DIVERSITY Mostly essential Capable people of differing ethnics groups; social, education industry experiences; with a wide range of discipline differences and diverse modes of thinking Proven AI engines, modelling and visualisation tools are useful augmentations to help/overcome the limitations of human thinking It is never too late to stop everything, abandon a given path and start again Search out and identify all those who may be able to help you and form a (real/virtual) team
  • 21. STATUS QUO Breaking new ground “If it your problem were simple, someone would have solved it a long time ago” “Be prepared to consider and employ the radical, the new, and even the crazy”
  • 22. PENUMBRA/Thoughts Your chance to ask questions and discuss cochrane.org.uk ca-global.biz For more presentations, papers and videos on this topic GOTO: www.cochrane.org.uk May 2017