Cognitive Computing for Tacit
Knowledge - Palliative or Tonic?
Cognitive Computing Enthusiasts
September 16th, 2015
HackerDojo, Mountain View, CA
About me
Cognitive Sciences: 1950 - 1978
Interdisciplinary inquiry of several university researchers/experts
A report accepted by Sloan Foundation in 1978 (picture).
Aimed at “universal science” to discover the representational
and computational capacities of the human mind and their
structural and functional realization in the human brain.
Why were “cognitive sciences” silent during the boom of
personal computers, Internet and Enterprise IT?
In 1978:
- cybernetics used concepts developed by computer science to
model brain functions elucidated in neuroscience.
- computer science and linguistics were linked through
computational linguistics
Which “Wave” are we on now?
Is cracking “human mind computation”
the solution to semiconductor technology crisis?
1978 - 2004
The cognitive revolution: a historical perspective by
George A. Miller, Department of Psychology,
Princeton University (2003)
I am here to share & learn…
Cognition
Identity?
(Adaptation) “Makes a new class of problems
computable. It addresses complex situations
that are characterized by ambiguity and
uncertainty; in other words it handles human
kinds of problems” (Wikipedia, retrieved
September 2015)
(Definition) “Set of all mental abilities and
processes related to knowledge, attention,
memory and working memory, judgment and
evaluation, reasoning and "computation",
problem solving and decision making,
comprehension and production of language,
etc…. Cognitive processes use existing
knowledge and generate new knowledge”
(Wikipedia, retrieved September 2015)
Cognitive
Computing
Humanities?
Cognitive
Computing
Systems
“Socio-technical” systems?
(Purpose) “Learn and interact naturally with
people to extend what either humans or
machine could do on their own. They help
human experts make better decisions by
penetrating the complexity of Big Data” (IBM
Research , September 2015)
Traditions of Cognitive Science
COGNITIVISM
EMERGENCE
ENACTION
"When the symbols appropriately represent some
aspect of the real world, and the information
processing leads to ... successful solution of the
problem given..."
"When the emergent properties (and resulting
structure) can be seen to correspond to a specific
cognitive capacity -- a successful solution to a required
task."
"When it becomes part of an ongoing existing world (as
the young of every species do) or shapes a new one (as
happens in evolutionary history)."
Varela, Thompson & Rosch (The Embodied Mind : Cognitive Science and Human Experience, Cambridge, MA: MIT Press, 1991.1991).
Encyclopaedia Autopoietica: a work of Randall Whitaker http://www.informatik.umu.se/~rwhit/EAIntro.html , retrieved from http://www.cybsoc.org/EA.html#enactive%20cognitive%20science on September 15th 2015
People learning through problem solving
(with or without machines)
People solving problems with machines
(higher complexity, less self-learning, more stress)
A “Personal Watson” or a
“Synthetic Neocortex”?
HOW DO I KNOW WHEN A COGNITIVE
SYSTEM IS FUNCTIONING
ADEQUATELY?
(beyond the Turing test/Jeopardy game)
2 mins window
“Flash-bulb” memory
200 bits storage
& manipulation
Hyper-diffused
storage
False memory syndrome
Memory enrichment
We have in the cranium a slightly alkaline three-pound electrochemical computer running on
glucose at about 25 watts. This computer contains some ten thousand million (that’s ten to the
ten) logical elements called neurons, operating on a basic scanning rhythm of ten cycles per
second. Then this is a high-variety dynamic system all right; but it really is finite. It follows (from
Ashby’s Law) that we can recognize patterns up to a certain limit, and not beyond (Stafford
Beer, “Science in the Service of Man” , 1973)
Conceptual differences ….
Our System 2 requires at least 1.5 minutes (90 seconds) to engage
Our System 2 has a very small size working memory:
- most of us can recall only 5 to 9 of the items shown once
Our System 2 has a “faulty” long term memory:
- can not remember each and every time we need to remember
- each time a memory is accessed, it is rebuilt and distorted
I am intrigued that Cognitive Computing field does so little to help us deal with
our weaknesses and so much to “mimic the way the human brain works”
Tacit knowledge is personal knowledge embedded in individual experience and involves
intangible factors, such as personal beliefs, perspective, and the value system.
- Know-how and other cognitive sciences aspects
- Hard to articulate with languages
Real-Time collaboration in creative work
(PhD research& dissertation – 1994 -1999)
How CC helps
me and you
create value
and preserve
identity?
Industrialization of Software Engineering,
Internet and Enterprise IT (1996 onwards)
Managing variability to develop healthy and
productive organizations (2008 onwards)
Environment of
digital computers in
all individual and
institutional aspects
Knowledge is
information that
changes something
or somebody—
either by becoming
grounds for actions,
or by making an
individual (or an
institution) capable
of different or more
effective action." Peter F. Drucker in
The New Realities
Clark, D.R. (2004). Knowledge Typology Map Retrieved from
http://www.nwlink.com/~donclark/knowledge/knowledge_typology.html on June 2014.
Cognitive computing for collaborative creative work in
telepresence (analog or digital – does it matter?)
Topic: "Group communication in a computer mediated environment: analysis, experiences and evaluations on
enterprise collaborative projects and group training"
Digital technologies context: Telecom ISDN (2*64kb/16kb, PictureTel/H323), CSCW (server centric design), OO
Programming (principles), Internet (IETF), Mbone (ALF/ILP, VBR encoding, p2p principles, open source)
Idea: “let each member of the group instantiate his/her own workspace, as he/she feels the need while engaged in
solving the task at hand”
(CS/Software Engineering R&D 1994-1997/PhD dissertation March 1999)
Cross the borders into cognitive sciences:
Proposed model: “computer mediated telepresence” as a cognitive system - to the benefit of group accomplishment - rather
than a multimodal communication system
Inspired by Roberto Maturana’s Cognition (1975) how cognition as a biological phenomenon takes place and Maturana &
Varela “autopoietic systems”
“Can the whole system - people, computers, software tools - operate effectively and successfully in a given domain,
language included?"
Test and validation for specific domain (professional training) different group
interactions to accomplish specific goals in situation of telepresence
•
•
•
Prototype & experimentation of above model for
mediated cooperative work on practical case studies:
Peer-to-peer architectures, User agents,
Application Level Framing and Integrated Layer
Processing for adaptation to variable conditions,
Internet Mbone (IP multicast source based
routing), variable bit-rate video encoding, (IETF
MMUSIC + …. SIP adoption in 3GPP)
Objective assessments (work results)
Compared with identical scenarios in physical presence
Subjective assessment (technology sufficiency/affordability/usability)
1995-1996 school year experimentation:
1 professor of Mechanical Engineering @INSA de Lyon, 40 students in 4 mediated sessions
and 30 in 3 real presence sessions (1 semester of studies in “Genie
Productique”/mechanical engineering ) + 1 professor of social sciences
3 scenarios: lecture, lab and project (teams of 5 people, isolated in media offices)
It takes a village:
NRG@
Mbone
9
Memory test
Concept test
Lecture set up – very much like today’s webinars
Project results (avg)
Usability results (avg)
Qualité
d’usage/rôle
1
2
3
4a
4b
1. l’acceptation
2. la difficulté d’exécution de la tâche
3. l’effort personnel
4.la qualité de réponse du système:
4a. pour la production
4b pour la communication/téléprésence
Landed 3 years contract 1996-1999 in TeleRegions SUN – TeleApplications
for Europeans Regions (health, education, citizen services in 6 regions, 4
countries)
Apprenant
Formateur
3,85
2,87
3,43
2,85
3,58
3,66
4,66
4
5
3
situation de cours/travaux dirigés
Qualité
d’usage/rôle
1
exécutant
chef
apprenant
Formateur
(exéc. +chef)
4,04
4,25
4,11
3,83
2
3,52
3,52
3,52
3,6
3
4,2
4,2
4,2
4,8
4a
4b
3,2
2,7
3,5
2,7
3,4
2,7
3,6
situation de projet coopératif
11
This experiment 20 years after ….
1996
2015 (still no video for everyone!)
But mobile operators
are launching Video over LTE
using …. IP Multicast, RTP/RTCP!
It took 20 years of denial.
Economists expertise required!
Biology and Human Behavior: The Neurological Origins of Individuality
Robert Sapolsky, Ph.D. Professor of Neurology and Neurosurgery Stanford University
We have:
• Online gaming for skills development (procedural
knowledge)
• Webex/Citrix/Skype/Whatsapp/WeChat/IM for group
communication (presence and telecommunications)
• Virtual Worlds and Robotics
1. How much of our creative work, the one that engages deeply our tacit knowledge, is “real-time collaborative”?
- Writing, Coding or Designing/Planning/Creating/Simulating an action or an object
- Manufacturing/Acting on physical objects
- Pondering alternatives and deciding
2. Can we work & communicate synchronously such as our communicative behavior becomes a mutual orientation
for the purpose of accomplishing a creative task rather than a painful exercise of memory and manipulation of
widgets?
Industrialization of Software Engineering, Internet services and
Enterprise IT (1996 onwards)
“…The increasing complexity of programming work associated with a new and more powerful generation of
computers had overwhelmed the technical and managerial ability of software groups. Software was late,
over budget, lacked features, worked inefficiently, and was unreliable. Something to be called “software
engineering” was proposed as the solution to the crisis. …” – as concluded by NATO Conference on Software
Engineering, held in Garmisch, Germany in 1968.
Thomas Haigh - “Crisis, What Crisis?” Reconsidering the Software Crisis of the
1960s and the Origins of Software Engineering (2010)
"Don't worry about turning your system over to the computer programmers. There won't be any in 1985,
because the machine will be doing the job itself. The job will be automated, as intelligent computers program
themselves."
(1960) Herbert Simon one of the founding fathers of several of today's important scientific domains,
including artificial intelligence, information processing, decision-making, problem-solving, attention
economics, organization theory, complex systems, and computer simulation of scientific discovery.
Difference Area
Adapted from
Hardware
Software
Human Factors
Major Life-cycle Cost Source
Development, manufacturing
Maintenance and Evolution
Training and operations labor
Ease of Changes
Generally difficult
Good within architectural framework
Very good, but people-dependent
Change Process
Manual, labor-intensive, expensive
Electronic, inexpensive
Needs retraining, can be expensive
User-tailorability/Friendliness
Generally difficult, limited options
Technically easy; mission-driven
Technically easy; mission-driven
Sub-setability/Divisibility
Inflexible lower limit
Flexible lower limit
Smaller increments easier to introduce
Underlying Science
Physics, chemistry, continuous
Discrete mathematics,
Behavioral sciences
mathematics
linguistics/programming
By test organization; much analytic
By test organization;
Testing
continuity
Directly by users
little analytic continuity
Economics of mass production embrace the human brainchild
enabled by computers: “Software”
1975 - Software Engineering of IBM OS/360 defies industrial
(large scale manufacturing) management: increasing the
team size also increases the time to complete the work
Culprit: Communication of thinking among software
engineers combined with lack of job specific tools
"adding manpower
to a late software
project makes it
later".
Fred Brooks
Domain specific Language(s)
Domain(s) specific Models(s)
Multiple perspectives
Multiple tools
~
Industrialization of Software
Stafford Beer, “The disregarded tools of modern man”, lectures, 1973
Years to
Develop
Software,
Hardware
SW
HW
Thousands of source lines of code (KSLOC)
Today: Massive software projects become possible, with
exponentially growing delivery time.
Culprit: the cone of requirements uncertainty ( inability
to imagine the end product amplified by the easiness to
change the current one)
“Mapping the value of employee collaboration” McKinsey Quarterly 2006, Number 3
Context
Technology
Factor
Hardware cost
Software cost
Attribute of
Product
Innovation
Relevant theoretical
concept
Relative advantage
Relative advantage
Impact *
+
+
Reliability
Product
Relative advantage
+/-
Availability of 3rd party apps
Portability of own apps
Product
Product
Compatibility
Compatibility
Network effects
Switching costs
+
+/0
Skills of existing IT workers
Fit to task
Product
Product
Compatibility
Compatibility
Switching costs
+/+/0
Varying perceptions of OSS platform reliability
Prerequisite to adoption, depends on platform
popularity
Increases adoption where such apps exist
Increases adoption if and only if existing skills are
compatible
Increases adoption for certain tasks
Difficulty in administra-tion
Product
Complexity
-
Perceived complexity decreases adoption
Ease of ex-perimenting
Innovation
Trialability
+
IT capital budget
Innovation
Slack
-
Reduces risk
Large budgets alllow more choice of expensive
options
IT staff time
Innovation
Slack
+
Slack required to evaluate new technologies
Explanation
Lintel runs on commodity hardware
OSS operating systems are ??free??
More innovative firms take more risks, want to be
??cutting edge??
Organization
Environment
Innovativeness of IT organization Innovation
Worker experience with new
platform
Product
Innovativeness
+
Boundary spanning
+
Industry maturity
Innovation
Industry life cycle
-
Availability of skilled IT workers
Availability of external support
services
Product
Support infrastructure
Network effects
+
Innovation
Support infrastructure
+
Platform long-term viability
Product
Sponsorship
"Angry orphan"
(switching costs)
+
Linux knowledge that workers bring to
organization prior to adoption
Infant industries not committed to old ways
Availability essential to adoption, more likely with
popular platforms
Support needed to run in critical environments and
to reassure management
Organizations avoid (re)investment in
technologies that may become unsupported
WHY FIRMS ADOPT OPEN SOURCE PLATFORMS: A GROUNDED THEORY OF INNOVATION AND STANDARDS ADOPTION
(HBS and MIT Sloan, 2003)
Procedural
knowledge stresses
executive functions
Tacit knowledge
drives learning
Crystallized Intelligence
(educational & cultural interactions)
Fluid Intelligence
(perception and reasoning)
Skills
Experience
Knowledge
•Knowledge is a fluid mix of framed experience, values, contextual information and
expert insight that provides a framework for evaluating and incorporating new
experiences and information.
•In Enterprises it often becomes embedded not only in documents or
repositories but also in organizational routines, processes, practices and
norms.
Crystallized Intelligence
(educational & cultural interactions)
Fluid Intelligence
(inductive & deductive
reasoning)
Skills
Experience
Knowledge
Tacit knowledge
John B. Carroll's three stratum model of cognitive abilities.
-fluid intelligence (Gf),
-crystallized intelligence (Gc),
Cognitive Computing DL simulates
- general memory and learning (Gy),
- broad visual perception (Gv),
Gy, Gv & Gu while inherently apt
- broad auditory perception (Gu)
at Gr, Gs &Gt
- broad retrieval ability (Gr),
- broad cognitive speediness (Gs)
- processing speed (Gt).
Cognitive Neuroscience
(from Prof. Garzzaniga)
Internal representation
of knowledge resulting
from the slow process of
learning
Quantitative
Analysis
Hypothesis
Formulation
Concepts
Modeling
Argumentation
support
Consistent/coherent
visual design
Qualitative
Analysis
Factor/Dependencies
Analysis
Systems (dynamic, agents)
Modeling & Simulation
Economics …
Enaction …
Computers are inherently logical and controlled
They can channel the creativity of the “Fast brain” through visuals
While engaging the “Slow brain” to think broad and deep
They retain this work as an external, automated, and objective mind
They can show it back in different ways, helping to iterate
Information
diffusion
Research overwhelmingly shows that human have preferences and poor objectivity
95 % time, people fail to alter their behavior through conscious effort alone
High motivation it simply takes too much mental energy and vigilance
Summary
Cognitive computing for collaborative creative work in
telepresence (analog or digital – does it matter?)
- Synchronous collaboration on creative work (conceptual
Industrialization of Software Engineering, Internet services and
Enterprise IT (1996 onwards)
- The reasoning software engineer
- The memory – consumer-entertainment product, executive functions impairments
Lucia.Gradinariu@lggsolutions.com