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Augmented Intelligence as a
response to the crisis of
Artificial Intelligence.
Prof. Alexander Ryzhov,
Presidential Academy of National Economy and Public Administration,
Lomonosov Moscow State University
Russia
13th IAC Annual Conference,
Astana, Kazakhstan,
June 27-29, 2018
Artificial Intelligence: art or tech?
• Homunculus
• Turing test
• Chess
• Go
NLP
Investments 2016 (Bln)
Computer Vision
Virtual AssistantRobots
Unmanned
vehicles
Machine learning
No criteria = from "nothing" to "everything"
could be named AI
• Turing test was successfully passed 08 of June 2014:
TURING TEST SUCCESS MARKS MILESTONE IN COMPUTING HISTORY
(HTTP://WWW.READING.AC.UK/NEWS-AND-
EVENTS/RELEASES/PR583836.ASPX)
• What is AI now? ”Automation of human’s … ” - calculator?
Merriam-Webster
• 1: a branch of computer science dealing with the simulation of intelligent behavior in
computers
• 2: the capability of a machine to imitate intelligent human behavior
Encyclopedia Britannica
• artificial intelligence (AI), the ability of a digital computer or computer-controlled
robot to perform tasks commonly associated with intelligent beings.
• Result of the uncertainty + marketing hype is crisis
AI: wrong expectations
• AI heading back to the trough. The expectations over artificial intelligence (AI) are becoming too
inflated. AI will indeed change everything, but not any time soon.
(https://www.networkworld.com/article/3206313/internet-of-things/ai-heading-back-to-the-
trough.html)
• Inflated Expectations: Artificial Intelligence Still Depends on Humans
(https://techonomy.com/2016/07/27222/)
• What AI mostly needs is expectation management (https://towardsdatascience.com/what-ai-
mostly-needs-is-expectation-management-625c90ea147f)
• Here's Why AI Can't Solve Everything (https://www.sciencealert.com/ai-machine-learning-solve-
all-humanity-problems-unrealistic)
• The Seven Deadly Sins of AI Predictions. Mistaken extrapolations, limited imagination, and other
common mistakes that distract us from thinking more productively about the future. We are
surrounded by hysteria about the future of artificial intelligence and robotics—hysteria about
how powerful they will become, how quickly, and what they will do to jobs.
(https://www.technologyreview.com/s/609048/the-seven-deadly-sins-of-ai-predictions/)
• …
• I can’t repeat here words from 99% of businessmen I hear when I just start talking about AI :)
AI: wrong expectations and results
• Facebook is shutting down M, its personal assistant service that
combined humans and AI
‘We learned a lot,’ company says
(https://www.theverge.com/2018/1/8/16856654/facebook-m-shutdown-
bots-ai)
• Cambridge Analytica and Scl Elections Commence Insolvency Proceedings
and Release Results of Independent Investigation into Recent Allegations
(https://ca-commercial.com/news/cambridge-analytica-and-scl-elections-
commence-insolvency-proceedings-and-release-results-3) (2 May 2018)
• IBM's Watson Health wing left looking poorly after 'massive' layoffs Up to
70% of staff shown the door this week, insiders claim
(https://www.theregister.co.uk/AMP/2018/05/25/ibms_watson_layoffs/)
Back to the starting point
• William Ross Ashby: ”Intellectual power, like physical power, can be amplified. Let
no one say that it cannot be done, for the gene-patterns do it every time they
form a brain that grows up to be something better than the gene-pattern could
have specified in detail. What is new is that we can now do it synthetically,
consciously, deliberately”
(Ashby, W.R., (1956). An Introduction to Cybernetics. London, UK: Chapman and
Hall, 1956 (p. 271). Retrieved from
http://pespmc1.vub.ac.be/books/IntroCyb.pdf)
• Joseph Carl Robnett Licklider : ”Man-computer symbiosis is an expected
development in cooperative interaction between men and electronic computers.
It will involve very close coupling between the human and the electronic members
of the partnership… Preliminary analyses indicate that the symbiotic partnership
will perform intellectual operations much more effectively than man alone can
perform them ”
(Licklider, J.C.R., (1960). Man-Computer Symbiosis. IRE Transactions on Human
Factors in Electronics, vol. HFE-1, 4-11 (p. 4) Retrieved from
http://groups.csail.mit.edu/medg/people/psz/Licklider.html)
Somebody has learned the lesson
• McKinsey. Automation of knowledge work - ”These capabilities not only extend
computing into new realms …, but also create new relationships between
knowledge workers and machines. It is increasingly possible to interact with a
machine the way one would with a coworker ”
(McKinsey Global Institute (May 2013). Disruptive technologies: Advances that will
transform life, business, and the global economy. (p.41) Retrieved from
http://www.mckinsey.com/insights/business_technology/disruptive_technologies)
• IBM. ”At IBM, we are guided by the term “augmented intelligence” rather than
“artificial intelligence”. It is the critical difference between systems that enhance
and scale human expertise rather than those that attempt to replicate all of
human intelligence. We focus on building practical AI applications that assist
people with well-defined tasks, and in the process, expose a range of generalized
AI services on a platform to support a wide range of new applications”
IBM, (2018). Cognitive computing. Preparing for the Future of Artificial
Intelligence. Retrieved from http://research.ibm.com/cognitive-
computing/ostp/rfi-response.shtml
Case study: muscular power amplifiers
evolution
• Spade  Excavator
• Horse  Rocket
• Lever  Crane
• …
For different tasks we
have different amplifiers
We have cases for an amplifiers of some
Intelligence features
• Memory
• Computing
Capabilities
Case study: a dream to fly
Ancient Greece Beginning of XX century Now
But people are flying (Wingsuit)
The lesson is ...
• Very expensive
• Very risky
• No practical sense
• Cheaply
• Safely
• Pragmatically
AI as s dream
Artificial Intelligence
Augmented Intelligence
What do we want?
• ”To fly like a birds”? It is an ”art”. Go to Hollywood.
• ”To fly on an aircraft”? It is the ”business + technology”. Welcome to IAC.
Albert Einstein has been widely quoted as saying, "The intuitive mind is a sacred gift and the rational mind is a faithful
servant. We have created a society that honors the servant and has forgotten the gift.”
Intuition Is The Highest Form Of Intelligence - https://www.forbes.com/sites/brucekasanoff/2017/02/21/intuition-is-
the-highest-form-of-intelligence/#18977d8e3860
Augmented Intelligence is not ”modish term”
• It is an old term (Ashby, W.R., (1956), Licklider, J.C.R., (1960), etc.)
• It means pragmatic aspect of intelligence systems
• It means a new problem definition: the synergy of human and
computer components.
Main problems of Augmented Intelligence
• Problem 1 (Perception modelling):
How we describe objects from the real world? Can we describe the
objects by the most reliable and the most effective for further
computing way?
• Problem 2 (Perception-base computing):
How we can manipulate with perception-based information (for
example, search or generalize)? Can we optimize these calculations?
1 2
Problem 1 (Perception modelling): discussion
Real world Model
Problem 1 (Perception modelling): discussion
Real world ModelMeasurement
Problem 1 (Perception modelling): discussion
Real world ModelMeasurement
Problem 1 (Perception modelling):
formalization
Problem 1. Is it possible, taking into account certain features of
the man’s perception of objects of the real world and their
description, to formulate a rule for selection of the optimum set of
values of characteristics on the basis of which these objects may
be described? Two optimality criteria are possible:
Criterion 1. We regard as optimum those sets of values through whose
use man experiences the minimum uncertainty in describing objects.
Criterion 2. If the object is described by a certain number of experts, then
we regard as optimum those sets of values which provide the minimum
degree of divergence of the descriptions.
Problem 1 (Perception modelling): solution
It is shown [Ryjov, 1985] that we can formulate a method of
selecting the optimum set of values of qualitative indications
(collection of granules).
Moreover, it is shown [Ryjov, 1991] that such a method is
robust, i.e. the natural small errors that may occur in
constructing the membership functions do not have a
significant influence on the selection of the optimum set of
values. The sets which are optimal according to criteria 1 and
2 coincide.
Following this method, we may describe objects with
minimum possible uncertainty, i.e. guarantee optimum
operation of the augmented intelligence systems from this
point of view. http://intsys.msu.ru/staff/ryzhov/FuzzySetsTheoryApplications.htm
Problem 2 (Perception-base computing):
formalization
Augmented intelligence assumes, at least, the storage
of information material (or references to it) and their
linguistic evaluations in the system database. In this
connection the following problem arises.
Problem 2. Is it possible to define the indices of quality of
information retrieval in fuzzy (linguistic) databases and to
formulate a rule for the selection of such a set of linguistic
values, use of which would provide the maximum indices
of quality of information retrieval?
Problem 2 (Perception-base computing):
solution
It is shown [Ryjov, 1992] that it is possible to introduce
indices of the quality of information retrieval in fuzzy
(linguistic) databases and to formalize them.
It is shown [Ryjov, 1992] that it is possible to formulate a
method of selecting the optimum set of values of qualitative
indications (collection of granules) which provides the
maximum quality indices of information retrieval.
Moreover, it is shown [Ryjov, 1993] that such a method is
robust, i.e. the natural small errors in the construction of the
membership functions do not have a significant effect on
the selection of the optimum set of values.
It allows to approve that the offered methods can be used in
practical tasks and to guarantee optimum work of
augmented intelligence systems.
http://www.intsys.msu.ru/staff/ryzhov/FuzzyRetrieval2010.htm
Problem 2 (Perception-base computing):
generalization
https://www.springer.com/gp/book/9783319082530
Augmented Intelligence frameworks
Evaluation and monitoring
of complex processes
Personalization of digital world
Evaluation and monitoring of complex
processes: examples
• System for monitoring and evaluation
of state’s nuclear activities
(department of safeguards, IAEA)
• System for evaluation and monitoring
of a socio-political process (RF
government structure)
• System for evaluation and monitoring
of risks of cardiovascular disease
(center of preventive medicine of
Ministry of Health of Russia)
• System for evaluation and monitoring
of microelectronic devices' design
(Cadence Design Systems)
Personalization of digital world: examples
• Social networks
• Smart learning for education
• Personalized healthcare
• News
1
2
3
Related tasks Automation of modelling
based on
• Data Mining/ Big Data
• Machine learning
Aggregation and
generalization
Personalization for
• Social Networks
• Smart Learning
• News
• Information retrieval
Task-driven information
granulation for
• Pattern recognition
• Decision Making
• Rule Induction
New applications
• Healthcare 4.0
• Smart learning for education
• Security
• E-government
• Smart City/Smart Region/
Smart Country
1
2
3
Related results Automation of modelling
based on
• Data Mining/ Big Data
• Machine learning
Aggregation and
generalization
Personalization for
• Social Networks
• Smart Learning
• News
• Information retrieval
Task-driven information
granulation for
• Pattern recognition
• Decision Making
• Rule Induction
New applications
• Healthcare 4.0
• Smart learning for education
• Security
• E-government
• Smart City/Smart Region/
Smart Country
Resume
• Augmented Intelligence is a practical (pragmatic) Artificial Intelligence
• The basic fundamental problems of Augmented Intelligence are solved
• Frameworks/ scenarios of Augmented Intelligence use are introduced
• Applications of Augmented Intelligence for various types of organizations
(international, federal, corporate levels) and various types of the problems
(non-proliferation of nuclear weapons and materials, security, healthcare,
microelectronics) are successfully developed and tested
• Vision and understanding for new applications (natural and technological
disasters management, smart city/ smart regions/ smart countries, smart
learning for education, smart healthcare, personalization and optimization for
social networks/ information retrieval/ other interactions of humans with
digital world, etc.) are proposed and discussed
Thank you!
Professor Alexander P. Ryjov
+7.916.323.4499
alexander.ryjov@gmail.com
Skype/ Facebook: alexander.ryjov
LinkedIn: ru.linkedin.com/pub/alexander-ryjov/1/957/859
http://www.intsys.msu.ru/en/staff/ryzhov

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Augmented intelligence as a response to the crisis of artificial intelligence

  • 1. Augmented Intelligence as a response to the crisis of Artificial Intelligence. Prof. Alexander Ryzhov, Presidential Academy of National Economy and Public Administration, Lomonosov Moscow State University Russia 13th IAC Annual Conference, Astana, Kazakhstan, June 27-29, 2018
  • 2. Artificial Intelligence: art or tech? • Homunculus • Turing test • Chess • Go NLP Investments 2016 (Bln) Computer Vision Virtual AssistantRobots Unmanned vehicles Machine learning
  • 3. No criteria = from "nothing" to "everything" could be named AI • Turing test was successfully passed 08 of June 2014: TURING TEST SUCCESS MARKS MILESTONE IN COMPUTING HISTORY (HTTP://WWW.READING.AC.UK/NEWS-AND- EVENTS/RELEASES/PR583836.ASPX) • What is AI now? ”Automation of human’s … ” - calculator? Merriam-Webster • 1: a branch of computer science dealing with the simulation of intelligent behavior in computers • 2: the capability of a machine to imitate intelligent human behavior Encyclopedia Britannica • artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. • Result of the uncertainty + marketing hype is crisis
  • 4. AI: wrong expectations • AI heading back to the trough. The expectations over artificial intelligence (AI) are becoming too inflated. AI will indeed change everything, but not any time soon. (https://www.networkworld.com/article/3206313/internet-of-things/ai-heading-back-to-the- trough.html) • Inflated Expectations: Artificial Intelligence Still Depends on Humans (https://techonomy.com/2016/07/27222/) • What AI mostly needs is expectation management (https://towardsdatascience.com/what-ai- mostly-needs-is-expectation-management-625c90ea147f) • Here's Why AI Can't Solve Everything (https://www.sciencealert.com/ai-machine-learning-solve- all-humanity-problems-unrealistic) • The Seven Deadly Sins of AI Predictions. Mistaken extrapolations, limited imagination, and other common mistakes that distract us from thinking more productively about the future. We are surrounded by hysteria about the future of artificial intelligence and robotics—hysteria about how powerful they will become, how quickly, and what they will do to jobs. (https://www.technologyreview.com/s/609048/the-seven-deadly-sins-of-ai-predictions/) • … • I can’t repeat here words from 99% of businessmen I hear when I just start talking about AI :)
  • 5. AI: wrong expectations and results • Facebook is shutting down M, its personal assistant service that combined humans and AI ‘We learned a lot,’ company says (https://www.theverge.com/2018/1/8/16856654/facebook-m-shutdown- bots-ai) • Cambridge Analytica and Scl Elections Commence Insolvency Proceedings and Release Results of Independent Investigation into Recent Allegations (https://ca-commercial.com/news/cambridge-analytica-and-scl-elections- commence-insolvency-proceedings-and-release-results-3) (2 May 2018) • IBM's Watson Health wing left looking poorly after 'massive' layoffs Up to 70% of staff shown the door this week, insiders claim (https://www.theregister.co.uk/AMP/2018/05/25/ibms_watson_layoffs/)
  • 6. Back to the starting point • William Ross Ashby: ”Intellectual power, like physical power, can be amplified. Let no one say that it cannot be done, for the gene-patterns do it every time they form a brain that grows up to be something better than the gene-pattern could have specified in detail. What is new is that we can now do it synthetically, consciously, deliberately” (Ashby, W.R., (1956). An Introduction to Cybernetics. London, UK: Chapman and Hall, 1956 (p. 271). Retrieved from http://pespmc1.vub.ac.be/books/IntroCyb.pdf) • Joseph Carl Robnett Licklider : ”Man-computer symbiosis is an expected development in cooperative interaction between men and electronic computers. It will involve very close coupling between the human and the electronic members of the partnership… Preliminary analyses indicate that the symbiotic partnership will perform intellectual operations much more effectively than man alone can perform them ” (Licklider, J.C.R., (1960). Man-Computer Symbiosis. IRE Transactions on Human Factors in Electronics, vol. HFE-1, 4-11 (p. 4) Retrieved from http://groups.csail.mit.edu/medg/people/psz/Licklider.html)
  • 7. Somebody has learned the lesson • McKinsey. Automation of knowledge work - ”These capabilities not only extend computing into new realms …, but also create new relationships between knowledge workers and machines. It is increasingly possible to interact with a machine the way one would with a coworker ” (McKinsey Global Institute (May 2013). Disruptive technologies: Advances that will transform life, business, and the global economy. (p.41) Retrieved from http://www.mckinsey.com/insights/business_technology/disruptive_technologies) • IBM. ”At IBM, we are guided by the term “augmented intelligence” rather than “artificial intelligence”. It is the critical difference between systems that enhance and scale human expertise rather than those that attempt to replicate all of human intelligence. We focus on building practical AI applications that assist people with well-defined tasks, and in the process, expose a range of generalized AI services on a platform to support a wide range of new applications” IBM, (2018). Cognitive computing. Preparing for the Future of Artificial Intelligence. Retrieved from http://research.ibm.com/cognitive- computing/ostp/rfi-response.shtml
  • 8. Case study: muscular power amplifiers evolution • Spade  Excavator • Horse  Rocket • Lever  Crane • … For different tasks we have different amplifiers
  • 9. We have cases for an amplifiers of some Intelligence features • Memory • Computing Capabilities
  • 10. Case study: a dream to fly Ancient Greece Beginning of XX century Now
  • 11. But people are flying (Wingsuit)
  • 12. The lesson is ... • Very expensive • Very risky • No practical sense • Cheaply • Safely • Pragmatically AI as s dream Artificial Intelligence Augmented Intelligence
  • 13. What do we want? • ”To fly like a birds”? It is an ”art”. Go to Hollywood. • ”To fly on an aircraft”? It is the ”business + technology”. Welcome to IAC. Albert Einstein has been widely quoted as saying, "The intuitive mind is a sacred gift and the rational mind is a faithful servant. We have created a society that honors the servant and has forgotten the gift.” Intuition Is The Highest Form Of Intelligence - https://www.forbes.com/sites/brucekasanoff/2017/02/21/intuition-is- the-highest-form-of-intelligence/#18977d8e3860
  • 14. Augmented Intelligence is not ”modish term” • It is an old term (Ashby, W.R., (1956), Licklider, J.C.R., (1960), etc.) • It means pragmatic aspect of intelligence systems • It means a new problem definition: the synergy of human and computer components.
  • 15. Main problems of Augmented Intelligence • Problem 1 (Perception modelling): How we describe objects from the real world? Can we describe the objects by the most reliable and the most effective for further computing way? • Problem 2 (Perception-base computing): How we can manipulate with perception-based information (for example, search or generalize)? Can we optimize these calculations? 1 2
  • 16. Problem 1 (Perception modelling): discussion Real world Model
  • 17. Problem 1 (Perception modelling): discussion Real world ModelMeasurement
  • 18. Problem 1 (Perception modelling): discussion Real world ModelMeasurement
  • 19. Problem 1 (Perception modelling): formalization Problem 1. Is it possible, taking into account certain features of the man’s perception of objects of the real world and their description, to formulate a rule for selection of the optimum set of values of characteristics on the basis of which these objects may be described? Two optimality criteria are possible: Criterion 1. We regard as optimum those sets of values through whose use man experiences the minimum uncertainty in describing objects. Criterion 2. If the object is described by a certain number of experts, then we regard as optimum those sets of values which provide the minimum degree of divergence of the descriptions.
  • 20. Problem 1 (Perception modelling): solution It is shown [Ryjov, 1985] that we can formulate a method of selecting the optimum set of values of qualitative indications (collection of granules). Moreover, it is shown [Ryjov, 1991] that such a method is robust, i.e. the natural small errors that may occur in constructing the membership functions do not have a significant influence on the selection of the optimum set of values. The sets which are optimal according to criteria 1 and 2 coincide. Following this method, we may describe objects with minimum possible uncertainty, i.e. guarantee optimum operation of the augmented intelligence systems from this point of view. http://intsys.msu.ru/staff/ryzhov/FuzzySetsTheoryApplications.htm
  • 21. Problem 2 (Perception-base computing): formalization Augmented intelligence assumes, at least, the storage of information material (or references to it) and their linguistic evaluations in the system database. In this connection the following problem arises. Problem 2. Is it possible to define the indices of quality of information retrieval in fuzzy (linguistic) databases and to formulate a rule for the selection of such a set of linguistic values, use of which would provide the maximum indices of quality of information retrieval?
  • 22. Problem 2 (Perception-base computing): solution It is shown [Ryjov, 1992] that it is possible to introduce indices of the quality of information retrieval in fuzzy (linguistic) databases and to formalize them. It is shown [Ryjov, 1992] that it is possible to formulate a method of selecting the optimum set of values of qualitative indications (collection of granules) which provides the maximum quality indices of information retrieval. Moreover, it is shown [Ryjov, 1993] that such a method is robust, i.e. the natural small errors in the construction of the membership functions do not have a significant effect on the selection of the optimum set of values. It allows to approve that the offered methods can be used in practical tasks and to guarantee optimum work of augmented intelligence systems. http://www.intsys.msu.ru/staff/ryzhov/FuzzyRetrieval2010.htm
  • 23. Problem 2 (Perception-base computing): generalization https://www.springer.com/gp/book/9783319082530
  • 24. Augmented Intelligence frameworks Evaluation and monitoring of complex processes Personalization of digital world
  • 25. Evaluation and monitoring of complex processes: examples • System for monitoring and evaluation of state’s nuclear activities (department of safeguards, IAEA) • System for evaluation and monitoring of a socio-political process (RF government structure) • System for evaluation and monitoring of risks of cardiovascular disease (center of preventive medicine of Ministry of Health of Russia) • System for evaluation and monitoring of microelectronic devices' design (Cadence Design Systems)
  • 26. Personalization of digital world: examples • Social networks • Smart learning for education • Personalized healthcare • News
  • 27. 1 2 3 Related tasks Automation of modelling based on • Data Mining/ Big Data • Machine learning Aggregation and generalization Personalization for • Social Networks • Smart Learning • News • Information retrieval Task-driven information granulation for • Pattern recognition • Decision Making • Rule Induction New applications • Healthcare 4.0 • Smart learning for education • Security • E-government • Smart City/Smart Region/ Smart Country
  • 28. 1 2 3 Related results Automation of modelling based on • Data Mining/ Big Data • Machine learning Aggregation and generalization Personalization for • Social Networks • Smart Learning • News • Information retrieval Task-driven information granulation for • Pattern recognition • Decision Making • Rule Induction New applications • Healthcare 4.0 • Smart learning for education • Security • E-government • Smart City/Smart Region/ Smart Country
  • 29. Resume • Augmented Intelligence is a practical (pragmatic) Artificial Intelligence • The basic fundamental problems of Augmented Intelligence are solved • Frameworks/ scenarios of Augmented Intelligence use are introduced • Applications of Augmented Intelligence for various types of organizations (international, federal, corporate levels) and various types of the problems (non-proliferation of nuclear weapons and materials, security, healthcare, microelectronics) are successfully developed and tested • Vision and understanding for new applications (natural and technological disasters management, smart city/ smart regions/ smart countries, smart learning for education, smart healthcare, personalization and optimization for social networks/ information retrieval/ other interactions of humans with digital world, etc.) are proposed and discussed
  • 30. Thank you! Professor Alexander P. Ryjov +7.916.323.4499 alexander.ryjov@gmail.com Skype/ Facebook: alexander.ryjov LinkedIn: ru.linkedin.com/pub/alexander-ryjov/1/957/859 http://www.intsys.msu.ru/en/staff/ryzhov