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Trust and Safeguards
Peter Cochrane
AI Summit, Olympia, London
29 November 2017
cochrane.org.uk
W h e r e A r e W e To d ay?
At the foothills of AI we have a mountain to climb
Intelligence
Abilities
Categories
1) Narrow
Singular Problem Solving
with human involvement
in coding and tuning
Human based algorithm
Top down, Bottom up
Machine learning
2) Learning
3) Cognitive
4) Wide
W h e r e A r e W e To d ay?
At the foothills of AI we have a mountain to climb
Intelligence
Abilities
Categories
1) Narrow
Singular Problem Solving
with human involvement
in coding and tuning
Human based algorithm
Top down, Bottom up
Machine learning
2) Learning
3) Cognitive
4) Wide
Most AI today
is here as is
so very easy
Google
alphago
IBM
Watson
W h e r e A r e W e To d ay?
At the foothills of AI we have a mountain to climb
Intelligence
Abilities
Categories
1) Narrow
Singular Problem Solving
with human involvement
in coding and tuning
Human based algorithm
Top down, Bottom up
Machine learning
Multiple Problem Classes
with interactive memory
- little or no human help
Initial algorithms from (1) + a learning
abilty - solves problems by observing,
playing and creating rule sets
2) Learning
3) Cognitive
4) Wide
A wide range of problem
sets - with cognition &
near 100% autonomy
Initial algorithms from (2) + a degree
of understanding - sees new ways of
analysis and solution formulation
Can address any problem
type/set - has high level
context/self awareness
A completely new ‘mind’ proposition
in a variety of species connected to
the wider environment - autonomous
Most AI today
is here as is
so very easy
Google
alphago
IBM
Watson
W h e r e A r e W e To d ay?
At the foothills of AI we have a mountain to climb
Intelligence
Abilities
Categories
1) Narrow
Singular Problem Solving
with human involvement
in coding and tuning
Human based algorithm
Top down, Bottom up
Machine learning
Multiple Problem Classes
with interactive memory
- little or no human help
Initial algorithms from (1) + a learning
abilty - solves problems by observing,
playing and creating rule sets
2) Learning
3) Cognitive
4) Wide
A wide range of problem
sets - with cognition &
near 100% autonomy
Initial algorithms from (2) + a degree
of understanding - sees new ways of
analysis and solution formulation
Can address any problem
type/set - has high level
context/self awareness
A completely new ‘mind’ proposition
in a variety of species connected to
the wider environment - autonomous
Machine influence
Human influence
Most AI today
is here as is
so very easy
Google
alphago
IBM
Watson
Isolated
Fixed
Machines
Networked
Fixed
Machines
Networked
Fixed/Mobile
With Sensors
Networked
Fixed/Mobile
With Full I/O
W h e r e A r e W e To d ay?
At the foothills of AI we have a mountain to climb
Intelligence
Abilities
Categories
1) Narrow
Singular Problem Solving
with human involvement
in coding and tuning
Human based algorithm
Top down, Bottom up
Machine learning
Multiple Problem Classes
with interactive memory
- little or no human help
Initial algorithms from (1) + a learning
abilty - solves problems by observing,
playing and creating rule sets
2) Learning
3) Cognitive
4) Wide
A wide range of problem
sets - with cognition &
near 100% autonomy
Initial algorithms from (2) + a degree
of understanding - sees new ways of
analysis and solution formulation
Can address any problem
type/set - has high level
context/self awareness
A completely new ‘mind’ proposition
in a variety of species connected to
the wider environment - autonomous
Machine influence
Human influence
Most AI today
is here as is
so very easy
Google
alphago
IBM
Watson
Isolated
Fixed
Machines
Networked
Fixed
Machines
Networked
Fixed/Mobile
With Sensors
Networked
Fixed/Mobile
With Full I/O
Main Frame
Main Frame
PC Laptop
Main Frame
PC Laptop
Mobile
Main Frame
PC Laptop
Mobile Robot
Sentient
Machines
Sentient
Lifeforms
Cyborgs
Languages &Techniques
The biggest fraction of the technology mixes today
TechniquesSoftware
An A.I. system:
1) Must be subject to the full gamut of laws that apply to its human operator/creator
2) Must clearly disclose that it is not human
3) Cannot retain or disclose confidential information without explicit approval from the source
Etzioni’s 2017
A Robot must:
0) Not harm humanity, or, by inaction, allow humanity to come to harm
1) Not injure a human being or, through inaction, allow a human being to come to harm

2) Obey orders given it by human beings except where such orders would conflict with the 1st Law

3) Protect its own existence as long as such protection does not conflict with the First or 2nd Law
Asimov’ 1942
LAWS To Be HEEDED ?
Ignored by governments & industry to date
An A.I. system:
1) Must be subject to the full gamut of laws that apply to its human operator/creator
2) Must clearly disclose that it is not human
3) Cannot retain or disclose confidential information without explicit approval from the source
Etzioni’s 2017
A Robot must:
0) Not harm humanity, or, by inaction, allow humanity to come to harm
1) Not injure a human being or, through inaction, allow a human being to come to harm

2) Obey orders given it by human beings except where such orders would conflict with the 1st Law

3) Protect its own existence as long as such protection does not conflict with the First or 2nd Law
Asimov’ 1942
LAWS To Be HEEDED ?
Ignored by governments & industry to date
NEVER APPLIED
N o
C h a n c e
S T O P P R ESS
Killer AI & Robots are GO!
A I A R M S
RACE IS GO
ONLY ONE
All that is needed
Mobile AI/Robotic weapon platforms
demand far less resources than any
atom bomb and/or missile program
Numerous rogue states will
quickly embrace this new
opportunity!
W
e a p o n s
C o n t r o l
S E E M S
I m p o s s i b l e
Etzioni’s 2017
AI & Robots must:
0) Not harm humanity, or, by inaction, allow humanity to come to harm
1) Not injure a human being or, through inaction, allow a human being to come to harm

2) Obey orders given it by human beings except where such orders would conflict with the 1st Law

3) Protect its own existence as long as such protection does not conflict with the First or 2nd Law
4) Be subject to the full gamut of laws that apply to its human operator/creator
5) Clearly disclose that it is/they are not human
6) Not retain or disclose confidential information without explicit approval from the source
7) Be bounded in their actions & inaction according to the safety requirements of humans and their systems
8) Not violate human social, cultural, safety and legal norms
9) ????
Asimov’ 1942
LAWS To Be combineD ?
To be ignored by future governments & industry
Etzioni’s 2017
AI & Robots must:
0) Not harm humanity, or, by inaction, allow humanity to come to harm
1) Not injure a human being or, through inaction, allow a human being to come to harm

2) Obey orders given it by human beings except where such orders would conflict with the 1st Law

3) Protect its own existence as long as such protection does not conflict with the First or 2nd Law
4) Be subject to the full gamut of laws that apply to its human operator/creator
5) Clearly disclose that it is/they are not human
6) Not retain or disclose confidential information without explicit approval from the source
7) Be bounded in their actions & inaction according to the safety requirements of humans and their systems
8) Not violate human social, cultural, safety and legal norms
9) ????
Asimov’ 1942
LAWS To Be combineD ?
To be ignored by future governments & industry
L e g a l
e
n
f
o
r
c
e
m
e
n
t
v e r y
u n l i k e l y
Meanw hile in industry ?
People protected from robots by wire cages and bars
A s s i s t a n t
AT HOME in office
People are using and working with AI
AI is increasingly all pervasive in homes, offices, appliances, vehicles, mobiles
and our trust and dependency is building fast - it is changing everything…
Fa m i l i a r i t y
Just a repeat of the past ?
Faster, more profound,
inclusive and impactful
with an acceleration of
other technologies and
big changes in the way
we work and live…..
A greater dependency
and risk of human
errors/mistakes
Job creation on huge
scale but with vast
shortages of skilled
and capable people
Breeds trust & dependency
F a m i l i a r i t y
It takes time: builds slowly
along with the ability to
work together in teams
using tools, tech and nets
to collaborate globally +++
AI will soon be doing trust and
dependency rankings of us; our
teams, tools, facilities, plant &
companies along with other AI
systems +++ It is an essential
for their real world modelling
Man Woman
Machine
A triad of trust
mechanisms at
work here
A population of ’N’ machines
could see ≤ N(N-1) different
trust mechanisms at work at
the same time
SAFEGUARDS
Operational measures
Testing
Fixed, Combinatorial, Dynamic
- Gold standard problem checks
- M a t h p ro v a b l e v e r i f i c a t i o n s
- W i t h i n n o r m a l i n p u t r a n g e
- Beyond normal input range
- A n o m a l y t e s t a n d s e a rc h
- Structured walk through
- Monte Carlo assessment
- Dynamic flood testing
- Pre-release real data
- R e g r e s s i o n t e s t i n g
- S t a t i s t i c a l a n a l y s i s
- Sensitivity analysis
- New developments
SAFEGUARDS
Operational measures
Constrainers
Fixed, Combinatorial, Dynamic
- Input sensor/data range limiters
- O u t p u t a c t u a t o r / d a t a l i m i t e r s
- A n o m a l y d e t e c t i o n / w a r n i n g s
- H i s t o r i c a l e x c e p t i o n f l a g s
- Human intervention alerts
- M 2 M r a n g e c o m p a r i s o n s
- C o m p l i a n c e m o n i t o r i n g
- Statistical I/O trending
- New developments
- Core activity flags
- FlOP counter alerts
- Energy consumption alarm
H u m a n S a f e t y
Rooms, floors, cages and barriers
We have kept machines and people well apart for
decades and only recently have we considered it
safe to mix the two in the same space…
H u m a n S a f e t y
Restricted inputs/outputs by design
This philosophy is applicable to AI and Intelligent robotics
and by default, industry, appliance and vehicle producers
et al are obeying ‘The Laws of Robotics and AI’ to date
https://www.youtube.com/watch?v=F6UxmpbSQGU&ab_channel=JustWowme
FAR FUTURE
AI + Human guardians
Being discussed, debated and
Initially researched at this time:
Policing AI into the future by Humans,
AI, Bots, Machines, Networks:
- Interrogators
- Enforcers
- Monitors
- Auditors
- Ethicists A lot of research/thinking
required as a sentient and
creative AI may be capable
of outsmarting any and all
guardianship systems
Thank You
www.cochrane.org.uk
What are these crazy humans
planning to do next ?? They are
the biggest risk and not us!!

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AI Trust and Safeguards

  • 1. Trust and Safeguards Peter Cochrane AI Summit, Olympia, London 29 November 2017 cochrane.org.uk
  • 2. W h e r e A r e W e To d ay? At the foothills of AI we have a mountain to climb Intelligence Abilities Categories 1) Narrow Singular Problem Solving with human involvement in coding and tuning Human based algorithm Top down, Bottom up Machine learning 2) Learning 3) Cognitive 4) Wide
  • 3. W h e r e A r e W e To d ay? At the foothills of AI we have a mountain to climb Intelligence Abilities Categories 1) Narrow Singular Problem Solving with human involvement in coding and tuning Human based algorithm Top down, Bottom up Machine learning 2) Learning 3) Cognitive 4) Wide Most AI today is here as is so very easy Google alphago IBM Watson
  • 4. W h e r e A r e W e To d ay? At the foothills of AI we have a mountain to climb Intelligence Abilities Categories 1) Narrow Singular Problem Solving with human involvement in coding and tuning Human based algorithm Top down, Bottom up Machine learning Multiple Problem Classes with interactive memory - little or no human help Initial algorithms from (1) + a learning abilty - solves problems by observing, playing and creating rule sets 2) Learning 3) Cognitive 4) Wide A wide range of problem sets - with cognition & near 100% autonomy Initial algorithms from (2) + a degree of understanding - sees new ways of analysis and solution formulation Can address any problem type/set - has high level context/self awareness A completely new ‘mind’ proposition in a variety of species connected to the wider environment - autonomous Most AI today is here as is so very easy Google alphago IBM Watson
  • 5. W h e r e A r e W e To d ay? At the foothills of AI we have a mountain to climb Intelligence Abilities Categories 1) Narrow Singular Problem Solving with human involvement in coding and tuning Human based algorithm Top down, Bottom up Machine learning Multiple Problem Classes with interactive memory - little or no human help Initial algorithms from (1) + a learning abilty - solves problems by observing, playing and creating rule sets 2) Learning 3) Cognitive 4) Wide A wide range of problem sets - with cognition & near 100% autonomy Initial algorithms from (2) + a degree of understanding - sees new ways of analysis and solution formulation Can address any problem type/set - has high level context/self awareness A completely new ‘mind’ proposition in a variety of species connected to the wider environment - autonomous Machine influence Human influence Most AI today is here as is so very easy Google alphago IBM Watson Isolated Fixed Machines Networked Fixed Machines Networked Fixed/Mobile With Sensors Networked Fixed/Mobile With Full I/O
  • 6. W h e r e A r e W e To d ay? At the foothills of AI we have a mountain to climb Intelligence Abilities Categories 1) Narrow Singular Problem Solving with human involvement in coding and tuning Human based algorithm Top down, Bottom up Machine learning Multiple Problem Classes with interactive memory - little or no human help Initial algorithms from (1) + a learning abilty - solves problems by observing, playing and creating rule sets 2) Learning 3) Cognitive 4) Wide A wide range of problem sets - with cognition & near 100% autonomy Initial algorithms from (2) + a degree of understanding - sees new ways of analysis and solution formulation Can address any problem type/set - has high level context/self awareness A completely new ‘mind’ proposition in a variety of species connected to the wider environment - autonomous Machine influence Human influence Most AI today is here as is so very easy Google alphago IBM Watson Isolated Fixed Machines Networked Fixed Machines Networked Fixed/Mobile With Sensors Networked Fixed/Mobile With Full I/O Main Frame Main Frame PC Laptop Main Frame PC Laptop Mobile Main Frame PC Laptop Mobile Robot Sentient Machines Sentient Lifeforms Cyborgs
  • 7. Languages &Techniques The biggest fraction of the technology mixes today TechniquesSoftware
  • 8.
  • 9.
  • 10. An A.I. system: 1) Must be subject to the full gamut of laws that apply to its human operator/creator 2) Must clearly disclose that it is not human 3) Cannot retain or disclose confidential information without explicit approval from the source Etzioni’s 2017 A Robot must: 0) Not harm humanity, or, by inaction, allow humanity to come to harm 1) Not injure a human being or, through inaction, allow a human being to come to harm
 2) Obey orders given it by human beings except where such orders would conflict with the 1st Law
 3) Protect its own existence as long as such protection does not conflict with the First or 2nd Law Asimov’ 1942 LAWS To Be HEEDED ? Ignored by governments & industry to date
  • 11. An A.I. system: 1) Must be subject to the full gamut of laws that apply to its human operator/creator 2) Must clearly disclose that it is not human 3) Cannot retain or disclose confidential information without explicit approval from the source Etzioni’s 2017 A Robot must: 0) Not harm humanity, or, by inaction, allow humanity to come to harm 1) Not injure a human being or, through inaction, allow a human being to come to harm
 2) Obey orders given it by human beings except where such orders would conflict with the 1st Law
 3) Protect its own existence as long as such protection does not conflict with the First or 2nd Law Asimov’ 1942 LAWS To Be HEEDED ? Ignored by governments & industry to date NEVER APPLIED N o C h a n c e
  • 12. S T O P P R ESS Killer AI & Robots are GO! A I A R M S RACE IS GO
  • 13. ONLY ONE All that is needed Mobile AI/Robotic weapon platforms demand far less resources than any atom bomb and/or missile program Numerous rogue states will quickly embrace this new opportunity! W e a p o n s C o n t r o l S E E M S I m p o s s i b l e
  • 14. Etzioni’s 2017 AI & Robots must: 0) Not harm humanity, or, by inaction, allow humanity to come to harm 1) Not injure a human being or, through inaction, allow a human being to come to harm
 2) Obey orders given it by human beings except where such orders would conflict with the 1st Law
 3) Protect its own existence as long as such protection does not conflict with the First or 2nd Law 4) Be subject to the full gamut of laws that apply to its human operator/creator 5) Clearly disclose that it is/they are not human 6) Not retain or disclose confidential information without explicit approval from the source 7) Be bounded in their actions & inaction according to the safety requirements of humans and their systems 8) Not violate human social, cultural, safety and legal norms 9) ???? Asimov’ 1942 LAWS To Be combineD ? To be ignored by future governments & industry
  • 15. Etzioni’s 2017 AI & Robots must: 0) Not harm humanity, or, by inaction, allow humanity to come to harm 1) Not injure a human being or, through inaction, allow a human being to come to harm
 2) Obey orders given it by human beings except where such orders would conflict with the 1st Law
 3) Protect its own existence as long as such protection does not conflict with the First or 2nd Law 4) Be subject to the full gamut of laws that apply to its human operator/creator 5) Clearly disclose that it is/they are not human 6) Not retain or disclose confidential information without explicit approval from the source 7) Be bounded in their actions & inaction according to the safety requirements of humans and their systems 8) Not violate human social, cultural, safety and legal norms 9) ???? Asimov’ 1942 LAWS To Be combineD ? To be ignored by future governments & industry L e g a l e n f o r c e m e n t v e r y u n l i k e l y
  • 16. Meanw hile in industry ? People protected from robots by wire cages and bars
  • 17.
  • 18.
  • 19. A s s i s t a n t AT HOME in office People are using and working with AI AI is increasingly all pervasive in homes, offices, appliances, vehicles, mobiles and our trust and dependency is building fast - it is changing everything…
  • 20. Fa m i l i a r i t y Just a repeat of the past ? Faster, more profound, inclusive and impactful with an acceleration of other technologies and big changes in the way we work and live….. A greater dependency and risk of human errors/mistakes Job creation on huge scale but with vast shortages of skilled and capable people
  • 21. Breeds trust & dependency F a m i l i a r i t y It takes time: builds slowly along with the ability to work together in teams using tools, tech and nets to collaborate globally +++ AI will soon be doing trust and dependency rankings of us; our teams, tools, facilities, plant & companies along with other AI systems +++ It is an essential for their real world modelling Man Woman Machine A triad of trust mechanisms at work here A population of ’N’ machines could see ≤ N(N-1) different trust mechanisms at work at the same time
  • 22. SAFEGUARDS Operational measures Testing Fixed, Combinatorial, Dynamic - Gold standard problem checks - M a t h p ro v a b l e v e r i f i c a t i o n s - W i t h i n n o r m a l i n p u t r a n g e - Beyond normal input range - A n o m a l y t e s t a n d s e a rc h - Structured walk through - Monte Carlo assessment - Dynamic flood testing - Pre-release real data - R e g r e s s i o n t e s t i n g - S t a t i s t i c a l a n a l y s i s - Sensitivity analysis - New developments
  • 23. SAFEGUARDS Operational measures Constrainers Fixed, Combinatorial, Dynamic - Input sensor/data range limiters - O u t p u t a c t u a t o r / d a t a l i m i t e r s - A n o m a l y d e t e c t i o n / w a r n i n g s - H i s t o r i c a l e x c e p t i o n f l a g s - Human intervention alerts - M 2 M r a n g e c o m p a r i s o n s - C o m p l i a n c e m o n i t o r i n g - Statistical I/O trending - New developments - Core activity flags - FlOP counter alerts - Energy consumption alarm
  • 24. H u m a n S a f e t y Rooms, floors, cages and barriers We have kept machines and people well apart for decades and only recently have we considered it safe to mix the two in the same space…
  • 25. H u m a n S a f e t y Restricted inputs/outputs by design This philosophy is applicable to AI and Intelligent robotics and by default, industry, appliance and vehicle producers et al are obeying ‘The Laws of Robotics and AI’ to date https://www.youtube.com/watch?v=F6UxmpbSQGU&ab_channel=JustWowme
  • 26. FAR FUTURE AI + Human guardians Being discussed, debated and Initially researched at this time: Policing AI into the future by Humans, AI, Bots, Machines, Networks: - Interrogators - Enforcers - Monitors - Auditors - Ethicists A lot of research/thinking required as a sentient and creative AI may be capable of outsmarting any and all guardianship systems
  • 27. Thank You www.cochrane.org.uk What are these crazy humans planning to do next ?? They are the biggest risk and not us!!