TAAI 2016 Keynote Talk: Contention and Disruption

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The 2016 Conference on Hsinchu, Taiwan, Keynote speech TAAI 2016
Technologies and Applications of Artificial Intelligence 27 November 2016
(TAAI 2016)
Contention and Disruption
H. Jaap van den Herik
Leiden Centre of Data Science Digital Technology for Law and Society
(LCDS) (elaw)
Leiden University Leiden University
TAAI 2016: National Tsing Hua University

Acknowledgements
With much pleasure I would like to thank I-Chen Wu and the Taiwanese
Association for Artificial Intelligence for the invitation and Cindy Ko for
the organisation of many details.
Research is team work over a long period of time. Therefore any list of
collaborators is large. Below I provide a selection. For their
contributions and inspiration, I would like to thank:
I-Chen Wu, Aja Huang, S.C. Hsu, Tsan-sjeng Hsu, Hiroyuki Iida, Erik van
der Werf, Victor Allis, Mark Winands, Jeroen Donkers, Levente Kocsis,
Dennis Breuker, Jahn Saito, Guillaume Chaslot, Jos Uiterwijk, Daniel
Dennett, Adriaan de Groot, Joost Kok, Jacqueline Meulman, Aske
Plaat, Michel Rademaker, Bart Custers, Cor Veenman, Cees de Laat,
members of the research school SIKS, members of LCDS, Joke
Hellemons, Eric Postma.

Contents
1. Contention (1950-1990)
2. Notions and Developments
3. Four Methodological Leaders
4. A Paradigm Shift
5. Provisional Conclusions
6. Disruption (1990-2030)
7. Innovation and Nearby Innovations
8. Four Conceptual Leaders
9. Go for Go for TAAI
10.Conclusions

Contention (1950-1990-2010)
In the academic world:
Contention means: (a) rivalry or competition
(b) a point contended for
in a scientific debate
We consider both meanings

Other Notions
- Scientific Findings
Discoveries
Revolutions
- A Paradigm Shift
- Intuitions

Intuitions
1. New Developments:
(a) Clouds
(b) Crowds: - Crowdsourcing
- The Wisdom of the Crowd
2. Refinements:
(c) WATSON
3. Opponents:
(d) Games

Prevailing Question on
Contention
Will Contention between Paradigms lead to
a Paradigm Shift?
- A refinement of definitions is necessary.
What is - contention
- a paradigm
- a paradigm shift ?
7

Two Well-known Paradigm Shifts
(1)From Ptolemaic Cosmology
to Copernican Cosmology
(2) From Newton’s physics
to Einstein’s relativistic theory
And maybe:
(3) Erik Verlinde (2016)
Emergent Gravity and the Dark Universe

Scientific Discoveries
Karl Popper (1902 - 1994):
The Logic of Scientific Discovery
Thomas Kuhn (1929 – 1996):
The Structure of Scientific Revolutions
Imre Lakatos (1922 – 1974):
The Methodology of Scientific Research Programmes
Paul Feyerabend (1924 - 1994):
Against Methods

Four Methodological Leaders
Karl
Popper
Thomas
Kuhn
Imre
Lakatos
Paul
Feyerabend

Due Credit to the Great Men
Karl Popper (1934). Logik der Forschung. English translation
(1959). The Logic of Scientific Discovery. Basic Books, New
York, N.Y.
Thomas Kuhn (1962). The Structure of Scientific Revolutions.
University of Chicago Press. Chicago, IL.
Imre Lakatos, John Worall, and Gregory Currie (1980). The
Methodology of Scientific Research Programmes.
Cambridge University Press, USA.
Imre Lakatos (1976) Proofs and Refutations: The Logic of
Mathematical Discovery. Cambridge University Press, USA.
Paul Feyerabend (1975). Against Method. New Left Books,
London, UK.
Imre Lakatos, Paul Feyerabend, and Matteo Matterlini (1999).
For and Against Methods. University of Chicago Press, USA.

Four Scientific Domains
1. Games
Rivals: Minimax and Monte Carlo Tree Search
2. (Super)computers
Rivals: Personal computing and Cloud Computing
(workstations inclusive)
3. WATSON
Rivals: Human Intellect and WATSON
4. eBay
Rivals (three): (a) Human Decision
(b) Computer Decision
(c) Crowdsourced Online Dispute Resolution

The World of Games
From Chess to Go
From Minimax to MCTS
Is this a Paradigm Shift ?

Scientific Breakthroughs on
Computers and Games
John von Neumann (1903-1957):
Theory of Games and Economic Behavior
Claude Shannon (1916-2001):
Chess Programming / Information Theory
Alan Turing (1912-1954):
Turing Machine

Three Leaders in Computer
Science
John von
Neumann
Claude Shannon Alan Turing

Five Challenging Questions
1. Can a computer play Chess and Go?
2. Can a computer play at grandmaster
level?
3. Can a computer defeat the human world
champion?
4. Can a computer solve the game?
5. Are some generic ideas applicable
elsewhere?

17
Minimax
3 4 2 7
3 2
[3]

α-β Algorithm
3 4 2 7
3
3
2
β-pruning

The Strength of α-β
3 4 2
More than thousand prunings

The Importance of α-β Algorithm
3 4 2
β-pruning
3
3

21
THE NUMBER OF DIFFERENT,
REACHABLE
POSITIONS IN CHESS IS
(CHINCHALKAR): 1046
Tromp (2016): for Go it is 10172
The Possibilities of Chess

A Calculation (around 2000)
NUMBER OF POSSIBILITIES: 1046
SAVINGS BY α-Β ALGORITHM: 1023
1000 PARALLEL PROCESSORS: 103
POSITIONS PER SECOND: 109
LEADS TO: 1023-12 = 1011 SECONDS
A CENTURY IS 109 SECONDS
SOLVING CHESS: 102 CENTURIES
SO 100 CENTURIES OR 10,000 YEARS
WE RETURN TO THIS NUMBER.

Improvements on the
Estimate
• MATJAŽ GAMS (30 August 2005)
In 2035 a machine takes 4 months to
solve chess.
• VINCENT DIEPEVEEN (27 October 2005)
In 2066 the game of chess is solved.

The Impact of Moore’s Law
GAMS AND DIEPEVEEN RELY ON
MOORE’S LAW
Every 18 months the computer
capacity is doubled.
Therefore in 30 years (30 = 20 x 1.5)
the law gives a speed up of 220 = 106

A New Calculation (2010)
NUMBER OF POSSIBILITIES: 1046
SAVINGS BY α-Β ALGORITHM: 1023
1000 PARALLEL PROCESSORS: 103
POSITIONS PER SECOND: 1014 (9+6=15; 15-1=14)
LEADS TO: 1023-17 = 106 SECONDS
A CENTURY IS 109 SECONDS
SOLVING CHESS: 10-3 CENTURIES
So roughly 37 days in 2035.
This is for Chess.

When will Go be solved?
Open Question
After 2050, if it may happen at all.
This opinion is supported by an old
sheet from 2011.

OLD SHEET (2011) FUTURE EXPECTATIONS
• MoGo-Titan defeats a top Go player in
• 2008 9 – stones handicap
• 2009 - 8 – stones handicap
• 2011 - 6 – stones handicap so far OK
• 2020 - ERICA defeats the human Go World Champion
The singularity point in Go is reached

Two Related Questions
(1)Is MCTS reflective of Kuhn’s
viewpoint?
(2)Is MCTS a result of Feyerabend’s
view?

Provisional Conclusions
on a Paradigm Shift for
Games
(1)From Chess to Go is a shift of focus
(not a paradigm shift)
(2) From Minimax to MCTS is/comes closer to a
paradigm shift
It weakly fulfils the conditions of a paradigm shift
(using a new framework, using a new technology).
[ see Newton – Einstein – Verlinde]

Disruption (1990-2016-2030)
Disruption is the successor of Contention.
Disruption means
(a) the change that occurs when new digital
technologies and business models affect
the value propositions of existing goods and
services
(b) the displacement of an existing
technology (market or industry) by
something completely new and more
efficient and more worth while.

Prevailing Question on
Disruption
Will Disruption lead to the emergence of a
New Paradigm?
- A refinement of definitions is necessary,
e.g.,
Innovation vs. Disruption
- What is the difference between
- (a) a paradigm shift, and
- (b) a new paradigm?

Announcements of Disruptive
Thoughts
Daniël Dennett (1990):
Consciousness Explained
Richard Susskind (1998):
Robot Doctors and Robot Lawyers
Nick Bostrom (2014):
Superintelligence
Jaap van den Herik (2016):
Intuition is Programmable

Four Announcers of Disruptive
Thoughts
Daniel
Dennett
Richard
Susskind
Nick
Bostrom
Jaap
van den
Herik

Nine (Nearby) Innovations
• Elon Musk: autonomous cars
• Richard Susskind: robot doctors and lawyers
• Nikolaos Aletras et al.: AI Judge
• Block Chain: bitcoins
• Internet of Things
• Drones
• Crowdsourced Online Dispute Resolution
• Uber Taxi
• AirBnb
• What is a disruptive innovation?

Ethical Decisions by
Intelligent Programs
- Autonomous cars
- Elon Musk

Robot doctors and lawyers? It’s a
change we should embrace
Richard Susskind Nov.
2015

A Da Vinci surgical robot performs a
procedure at the Charles Nicolle hospital in
Rouen. Nov. 2015

PeerJ Computer Science 2:e93 October 24, 2016
https://doi.org/10.7717/peerj-cs.93

Big Data Discovery is the combination of Big Data,
Data Science and Data Discovery
(Source Gartner)

The Fifth Breakthrough (Source
Gartner)

Intuition
Two key Questions: What is Intuition?
Is Intuition Programmable?
Definition 1 (Rorty): "Intuition is unjustified false
belief not preceded by inference; in this (the
commonest) sense 'an intuition' means 'a hunch'.
The existence of hunches is uncontroversial and
not of philosophical interest."

Two more definitions (1)
Definition by Poincaré (1913)
Definition by Euwe (Tilburg, 1964)
"The essential element of playing chess at a high level is inspiration. The skill
competence of a chess player is based on a multitude of factors, such as
directly accessible knowledge, memory, accuracy, ability for combinations, but
especially on consolidated experience. De Groot considers the latter as
indicative for the distinction between master and non-master. Yet, there are
chess masters who (in brief) know everything and see everything and still
never will succeed in reaching the highest echelons. It is said that they do not
have sufficient imagination. It is thought that these players do not have from
time to time a lucid thought, say a hunch." [Emphasis added by vdH]

Two more definitions (2)
Definition 2 (De Groot): "Intuition is
having judgements (or making decisions) in
a manner that cannot be made explicit."
Definition 3 (Michie): "Intuition is simply
a name for rule-based behaviour where the
rules are not accessible for consciousness."

The Place of Intuition
Four forms of intuition are
• Mental intuition,
• Physical intuition,
• Emotional intuition, and
• Environmental intuition.

The Model by McWhinney
Grammars of Engagement
THE FOUR MODES
SOURCE DETERMINED VOLUNTARISTIC REFERENCES & COMMENTS
FOUR
REALITIES
Unitary Sensory Social Mythic McWhinney (1984).
BUDDHIST Samjña Rupa Vedana Samskara Conze (1951).
PLATO
Reason Understanding Opinion Perception
(faith) of Shadows
Jowett’s terms from The Republic and
Gilbert Ryle (1967).
GOSPELS
Matthew Mark Luke John
(Lion) (Ox) (Man) (Eagle)
The parallels were observed and analyzed
by John Lai (1996). The metaphors are
from Revelation, 4:7.
LAKOTA INDIAN
North South West East
(Buffalo) (Mouse) (Bear) (Eagle)
Storm (1972) writing from a Plains Indian
worldview.
JUNG Thinking Sensing Feeling Intuiting Jung’s Personality Types (1920).
LESHAN Clairvoyant Sensory Transpsychic Mythic
Lawrence LeShan (1976).
Descriptions of exceptional people.
HERMANN
Left Left Right Right
Cerebral Limbic Limbic Cerebral
Ned Hermann (1989).
LATOUR
Being External Social Signification
Reality Bond and Meaning
Bruno Latour (1991).

From McWhinney
Back to Jung (1920)
Focussing on Intuition
I-Chen Wu
Letty Raaphorst
Aja Huang
Jaap van den Herik
Thinking
Intuiting
Sensing
Feeling
An Instantiation of the Four Modes

Three Friends in the Future
• Big Data
• High Performance Computing
• Deep Learning

Roadmap to Deep Learning
Artificial Intelligence 1950-1990
Machine Learning 1990-2000
Adaptivity 2000-2005
Dimension Reduction 2005-2010
Deep Learning 2010-2015
Big Data & HPC 2012-2017
New Statistics 2014-2019

Go for Go for TAAI
Back to Go
Back to Aja Huang to Google DeepMind

Google DeepMind 2016

Differences between Chess and Go
Chess Go
Game complexity 10^46 10^172
Tree evaluation strong point weak point
Search method minimax (α-β) MCTS
+enhancement +enhancement
Breakthrough Tuning parameters Big Data
Search enhancements Unsupervised
Reinforcement
Learning
HPC HPC+
Currently Komodo 3400 Elo pts AlphaGo defeats Fan Hui
Carlson 2851 Elo pts 5-0 (October 2015) and
Lee Sedol 4-1(March 2016)

Match 1: Lee Sedol vs Alpha Go

Game 4: Lee Sedol vs Alpha Go after
move 79

Lee Sedol wins Game 4 from
AlphaGo

From Erica to AlphaGo

Lee Sedol Congratulates
Hassabis

CONCLUSIONS ON GAMES
1. Computers will solve a range of games.
2. New games will emerge.
3. Humans will continuously learn from
computers.
4. The Games Research will envisage new
games and even more new computer
techniques.

CONCLUSIONS ON AI
The new emerging paradigm is:
Understanding the Intuition of a Network
that
results from a Deep Learning procedure
In summary,
Our world is moving from decisions made
by humans to decisions made by
computers.

THE FUTURE
• In 2025, an AI-program is clever, but not
very clever
• In 2035, an AI-judge makes verdicts in plain
cases
• In 2050, robots will outperform human
soccer teams
• In 2080, AI-judges are more competent in
ethical decisions than humans
• After 84 years, an AI-program will act as a
full professor in all disciplines

ADVICE
The new future is NOT the end of making
decisions (judge, manager, game player or
professor). Both humans and robots will:
- address and solve new challenges
- improve their experience
- develop fully new tracks.
This is a promising perspective.

TAAI 2016 Keynote Talk: Contention and Disruption

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