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Artificial Intelligence?
Machine Learning?
JinYeong Bak
jy.bak@kaist.ac.kr
School of Computing, KAIST
About Me
• JinYeong Bak (jy.bak@kaist.ac.kr)
• Ph.D. student at KAIST, U&I Lab
– MS degree at KAIST
– BS degree at SKKU
• ...
INTRODUCTION
2016-03-203
AlphaGo
2016-03-204
AlphaGo
• Computer program
– Developed by Google DeepMind
– Play the board game Go
• Algorithm: a combination of
– Artific...
AlphaGo
2016-03-206
AlphaGo
2016-03-207
So…
2016-03-208
Contents
• Artificial Intelligence
• My research
2016-03-209
ARTIFICIAL INTELLIGENCE
2016-03-2010
Frequently Asked Questions
AlphaGo wins Lee Sedol
2016-03-2011
Frequently Asked Questions
AlphaGo wins Lee Sedol
• Can AlphaGo win all people?
2016-03-2011
Frequently Asked Questions
AlphaGo wins Lee Sedol
• Can AlphaGo win all people?
• Can AI control human being?
2016-03-2011
Frequently Asked Questions
AlphaGo wins Lee Sedol
• Can AlphaGo win all people?
• Can AI control human being?
• Can AI mak...
Frequently Asked Questions
AlphaGo wins Lee Sedol
• Can AlphaGo win all people?
• Can AI control human being?
• Can AI mak...
Frequently Asked Questions
AlphaGo wins Lee Sedol
• Can AlphaGo win all people?
• Can AI control human being?
• Can AI mak...
AlphaGo
• Computer program
– Developed by Google DeepMind
– Play the board game Go
• Algorithm: a combination of
– Artific...
Artificial intelligence
The intelligence exhibited by machines
2016-03-2013
Artificial intelligence
How to create computers and computer software that
are capable of intelligent behavior
2016-03-2014
Artificial intelligence - Types
• Artificial Narrow Intelligence (ANI)
• Artificial General Intelligence (AGI)
• Artificia...
Artificial intelligence
• Artificial Narrow Intelligence (ANI)
– Weak AI
– Specializes in one area
– Ex) AlphaGo, Siri, Sp...
Artificial intelligence
• Artificial Narrow Intelligence (ANI)
• Artificial General Intelligence (AGI)
– Strong AI (Human ...
Artificial intelligence
• Artificial Narrow Intelligence (ANI)
• Artificial General Intelligence (AGI)
• Artificial Super ...
Artificial intelligence
• Artificial Narrow Intelligence (ANI)
• Artificial General Intelligence (AGI)
• Artificial Super ...
Intelligence
• The ability to learn or understand things or to deal with new
or difficult situations
2016-03-2019
Intelligence
• The ability to learn or understand things or to deal with new or difficult
situations
• Capacity for
– Logi...
Human Intelligence Growth
2016-03-2020
Human Intelligence Growth
2016-03-2021
Human Intelligence Growth
2016-03-2022
Human Intelligence Growth
2016-03-2023
Human Intelligence Growth
2016-03-2024
AI is coming
2016-03-2025
Opinions on ASI Arrival
2016-03-2026
Opinions on ASI Arrival
2016-03-2027
Opinions on ASI Arrival
• Optimism
• Pessimism
2016-03-2028
Opinions on ASI Arrival
• Optimism
– AIs can solve any problems
– Humans can have eternal life
2016-03-2029
Opinions on ASI Arrival
• Pessimism
– AIs work hard to achieve the goal
2016-03-2030
Opinions on ASI Arrival
• Pessimism
– AIs work hard to achieve the goal
– AIs are amoral
• Not moral
• Not immoral
• Not i...
Opinions on ASI Arrival
• Pessimism
– AIs work hard to achieve the goal
– AIs are amoral
• Not moral
• Not immoral
• Not i...
Opinions on ASI Arrival
• Pessimism
– AIs work hard to achieve the goal
– AIs are amoral
• Not moral
• Not immoral
• Not i...
Opinions on ASI Arrival
• Pessimism
– AIs work hard to achieve the goal
– AIs are amoral
• Not moral
• Not immoral
• Not i...
In the future…
2016-03-2031
My opinion
More like optimism
Reasons
– The goal is given by human
– Moral/Immoral is coming from human
2016-03-2032
My opinion
2016-03-2033
My opinion
2016-03-2033
My opinion
2016-03-2033
My opinion
2016-03-2033
My opinion
More like optimism
Reasons
– The goal is given by human
– Moral/Immoral is coming from human
– I am machine lea...
OK…
2016-03-2035
MY RESEARCH – BACKGROUND
2016-03-2036
Artificial intelligence
How to create computers and computer software that
are capable of intelligent behavior
2016-03-2037
Machine learning
• Subfield of artificial intelligence
• Study of pattern recognition and computational
learning theory
20...
Topic modeling
• Subfield of machine learning
• Discovering the abstract "topics" that occur in a
collection of documents
...
Topic modeling - Introduction
2016-03-2040
Topic modeling - Introduction
2016-03-2041
Topic modeling - Introduction
2016-03-2042
Topic modeling - Introduction
2016-03-2043
Topic modeling - Introduction
2016-03-2044
Topic modeling - Introduction
• What are the topics discussed in the article?
• How can we describe the topics?
2016-03-20...
Topic modeling - Assumption
2016-03-2046
Topic modeling - Assumption
2016-03-2047
Topic modeling - Assumption
2016-03-2048
Topic modeling - Assumption
2016-03-2049
Topic modeling
2016-03-2050
Korea
Music
Olympic
Topic proportion of each document
Topic modeling
2016-03-2050
Korea
Music
Olympic
Topic proportion of each document
Topic modeling
2016-03-2050
Korea
Music
Olympic
Topic proportion of each document
Topic modeling
2016-03-2050
korea south korean kim lee
music album song single live
olympic summer medal gold
winter
Word ...
Topic modeling
2016-03-2050
korea south korean kim lee
music album song single live
olympic summer medal gold
winter
Word ...
Topic modeling
• Inputs
– Document corpus
– Parameters
2016-03-2051
Topic modeling
• Inputs
– Document corpus
– Parameters
• Models
– LDA
– HDP
2016-03-2051
LDA
Topic modeling
• Inputs
– Document corpus
– Parameters
• Models
– LDA
– HDP
• Inferences
– Gibbs sampling
– Variational In...
Topic modeling
• Inputs
– Document corpus
– Parameters
• Models
– LDA
– HDP
• Inferences
– Gibbs sampling
– Variational In...
MY RESEARCH – ONLINE LEARNING
2016-03-2052
Topic modeling
• Inputs
– Document corpus
– Parameters
• Models
– LDA
– HDP
• Inferences
– Gibbs sampling
– Variational In...
Topic modeling
• Inputs
– Document corpus
– Parameters
• Models
– LDA
– HDP
• Inferences
– Gibbs sampling
– Variational In...
Topic modeling
• Inputs
– Document corpus
– Parameters
• Models
– LDA
– HDP
• Inferences
– Gibbs sampling
– Variational In...
Documents size
2016-03-2054
New documents
2016-03-2055
Previous approach problem
2016-03-2056
Previous approach problem
2016-03-2056
LDA
Previous approach problem
2016-03-2056
LDA
Previous approach problem
2016-03-2056
Previous approach problem
2016-03-2056
Previous approach problem
2016-03-2056
LDA
Previous approach problem
2016-03-2056
LDA
Previous approach problem
2016-03-2056
LDA
Previous approach problem
2016-03-2056
LDA
Previous approach problem
2016-03-2056
LDA
My suggestion
2016-03-2057
My suggestion
2016-03-2057
LDA
My suggestion
2016-03-2057
LDA
My suggestion
2016-03-2057
My suggestion
2016-03-2057
My suggestion
2016-03-2057
LDA
My suggestion
2016-03-2057
LDA
My suggestion
2016-03-2058
My suggestion
2016-03-2058
Results
2016-03-2059
MY RESEARCH – COMPUTATIONAL
SOCIAL SCIENCE
2016-03-2060
Computational Social Science
• Computational approaches to the social sciences
• Computers are used to model, simulate, an...
My research
• Self-disclosure in Twitter conversation
• Leadership in the AJD
2016-03-2062
Leadership
• A process of social influence in which a person can
enlist the aid and support of others in the
accomplishmen...
Leadership
• A process of social influence in which a person can
enlist the aid and support of others in the
accomplishmen...
Leadership Styles [Lewin, et al. 1939]
2016-03-2064
Leadership Styles [Lewin, et al. 1939]
• Autocratic
– Get little input from group members
– Control over all decisions
201...
Leadership Styles [Lewin, et al. 1939]
• Autocratic
– Get little input from group members
– Control over all decisions
• L...
Leadership Styles [Lewin, et al. 1939]
• Autocratic
– Get little input from group members
– Control over all decisions
• L...
Leadership Styles
• Target people
– School children [Lewin, et al. 1939]
– Work employee [Hoel. 2010]
– USA president [Bli...
Leadership Styles
• Target people
– School children [Lewin, et al. 1939]
– Work employee [Hoel. 2010]
– USA president [Bli...
Leadership Styles
• Target people
– School children [Lewin, et al. 1939]
– Work employee [Hoel. 2010]
– USA president [Bli...
Research Questions
1. Do kings show different kinds of leadership styles?
2016-03-2067
Research Questions
1. Do kings show different kinds of leadership styles?
2. What factors are related with kings’ leadersh...
Dataset
• What kinds of data are needed?
2016-03-2068
Dataset
• What kinds of data are needed?
• Requirements: records of king’s official duty activities
– Discussions with gov...
Dataset
• What kinds of data are needed?
• Requirements: records of king’s official duty activities
– Discussions with gov...
The Annals of the Joseon Dynasty
• Series of books which describe about historical facts
in Joseon dynasty
• 1,893 books, ...
The Joseon Dynasty
• Ancient kingdom in Korean peninsula
2016-03-2070
Civilization V - Civilization and Scenario Pack: Kor...
The Joseon Dynasty
• Ancient kingdom in Korean peninsula
2016-03-2070
Civilization V - Civilization and Scenario Pack: Kor...
The Joseon Dynasty
• Ancient kingdom in Korean peninsula
2016-03-2070
Civilization V - Civilization and Scenario Pack: Kor...
The Joseon Dynasty
• Ancient kingdom in Korean peninsula
– From 1392 to 1897
– 27 kings
– Capital city: Seoul
– Religion: ...
The Joseon Dynasty
• Monarchial system
– King governs the nation
– King decides on official issues
– King discusses it wit...
The Joseon Dynasty
• Monarchial system
– King governs the nation
– King decides on official issues
– King discusses it wit...
The Joseon Dynasty
• Monarchial system
– King governs the nation
– King decides on official issues
– King discusses it wit...
The Joseon Dynasty
• Monarchial system
– King governs the nation
– King decides on official issues
– King discusses it wit...
The Joseon Dynasty
• Monarchial system
– King governs the nation
– King decides on official issues
– King discusses it wit...
The Annals of the Joseon Dynasty
• Contents
2016-03-2073
The Annals of the Joseon Dynasty
• Contents
– Human resources
• Employment & Dismissal
• Person information
2016-03-2073
The Annals of the Joseon Dynasty
• Contents
– Human resources
• Employment & Dismissal
• Person information
– Government i...
The Annals of the Joseon Dynasty
• Contents
– Human resources
• Employment & Dismissal
• Person information
– Government i...
The Annals of the Joseon Dynasty
• Contents
– Human resources
• Employment & Dismissal
• Person information
– Government i...
The Annals of the Joseon Dynasty
• Contents
– Human resources
• Employment & Dismissal
• Person information
– Government i...
The Annals of the Joseon Dynasty
• National Institute of Korean History (http://www.history.go.kr)
– Translated it to mode...
The Annals of the Joseon Dynasty
• National Institute of Korean History (http://www.history.go.kr)
– Translated it to mode...
The Annals of the Joseon Dynasty
• National Institute of Korean History (http://www.history.go.kr)
– Translated it to mode...
The Annals of the Joseon Dynasty
2016-03-2075
The Annals of the Joseon Dynasty
2016-03-2075
The Annals of the Joseon Dynasty
2016-03-2075
The Annals of the Joseon Dynasty
2016-03-2075
The Annals of the Joseon Dynasty
2016-03-2076
The Annals of the Joseon Dynasty
2016-03-2076
Time
The Annals of the Joseon Dynasty
2016-03-2076
Title
Time
The Annals of the Joseon Dynasty
2016-03-2076
Title
Time
Body
The Annals of the Joseon Dynasty
2016-03-2076
Title
Meta
information
Time
Body
The Annals of the Joseon Dynasty
2016-03-2077
Combining two local districts
The Annals of the Joseon Dynasty
2016-03-2077
Facts
Combining two local districts
The Annals of the Joseon Dynasty
2016-03-2077
Facts
Combining two local districts
The Annals of the Joseon Dynasty
2016-03-2077
Facts
Official A
Combining two local districts
The Annals of the Joseon Dynasty
2016-03-2077
Facts
Official A
“It’s reasonable to combine
two local districts.”
Combining...
The Annals of the Joseon Dynasty
2016-03-2077
Facts
Official A
King
“It’s reasonable to combine
two local districts.”
Comb...
The Annals of the Joseon Dynasty
2016-03-2077
Facts
Official A
King
“It’s reasonable to combine
two local districts.”
Comb...
The Annals of the Joseon Dynasty
2016-03-2077
Facts
Official A
King
Official B
Official C
“It’s reasonable to combine
two ...
The Annals of the Joseon Dynasty
2016-03-2077
Facts
Official A
King
Official B
Official C
The king follows
Official C’s su...
Methodology
• Identify relevant articles
– To avoid non-governmental affairs (e.g. observations)
– Look at the kings words...
Methodology
• Identify relevant articles
– To avoid non-governmental affairs (e.g. observations)
– Look at the kings words...
Ruling styles
• Arbitrary Decision (AD)
• Discussion and Order (DO)
• Discussion and Follow (DF)
2016-03-2079
Ruling styles
• Arbitrary Decision (AD)
– Like autocratic style
– No discussion with officials
– Orders directly
• Discuss...
Ruling styles
• Arbitrary Decision (AD)
– Like autocratic style
– No discussion with officials
– Orders directly
• Discuss...
Ruling styles
• Arbitrary Decision (AD)
– Like autocratic style
– No discussion with officials
– Orders directly
• Discuss...
Ruling styles
2016-03-2080
• Arbitrary Decision (AD) example
King
Facts
Ruling styles
2016-03-2080
• Arbitrary Decision (AD) example
King
Facts
“Remove all fences
at the gates”
Ruling styles
2016-03-2081
• Discussion and Order (DO) example
Agency A
Official B
Official C
King
King
King
Ruling styles
2016-03-2081
• Discussion and Order (DO) example
Agency A
Official B
Official C
King
King
King
“Please inter...
Ruling styles
2016-03-2081
• Discussion and Order (DO) example
Agency A
Official B
Official C
King
King
King
“I don’t want...
Ruling styles
2016-03-2082
• Discussion and Follow (DF) example
Facts
Official A
King
Official B
Official C
The king follo...
Research Question 1
1. Do kings show different kinds of leadership styles?
2016-03-2083
Results – Among kings
2016-03-2084
• Each king shows different ruling style
– Multinomial test between king’s ruling style...
Results – Among kings
2016-03-2084
• Each king shows different ruling style
– Multinomial test between king’s ruling style...
Research Question 2
2. What factors are related with kings’ leadership?
– Context/Topics?
– Members?
– Time?
2016-03-2085
Methodology
• Discover topics in each article
– LDA [Blei et al. 2003] with 300 topics
– LDA outputs a topic proportion fo...
Methodology
• Discover topics in each article
– LDA [Blei et al. 2003] with 300 topics
– LDA outputs a topic proportion fo...
Results - Topics
Retirement Agriculture Remission Grants
신하 곡물 죄 한 필
은퇴 마을 법 한 구획
지위 한 구획 전하 하사
사람 창고 관여 안장
유능 사람 용서 한 지역
...
Investigate the effects o
Results - Topics
2016-03-2088
Sejong the Great
Yeonsangun
Injo
Investigate the effects o
Results - Topics
2016-03-2088
Sejong the Great
Yeonsangun
Injo
Investigate the effects o
Results - Topics
2016-03-2088
Sejong the Great
Yeonsangun
Injo
Investigate the effects o )
• Results
Different from overall
( )
Results - Topics
2016-03-2088
Sejong the Great
Yeonsangun...
• Remission of sins topic
– Kings act DO than overall
– Injo tends to DF
Results - Topics
2016-03-2089
Sejong the Great
Ye...
• Remission of sins topic
– Kings act DO than overall
– Injo tends to DF
• Granting rewards topic
– Sejong the Great acts ...
Results - Members
• Investigate the effects of the participants in a discussion
– Compute the mutual information among rul...
Results - Members
• Investigate the effects of the participants in a discussion
– Compute the mutual information among rul...
Results - Members
• Investigate the effects of the participants in a discussion
– Compute the mutual information among rul...
Results – Time
• Investigate the changes over time
– Look at the temporal difference of a king
2016-03-2091
Yeonsangun Injo
Results – Time
• Investigate the changes over time
– Look at the temporal difference of a king
• Results
– Yeonsangun beco...
Conclusion
• AIs are getting strong
– The singularity is near
– Optimistic? Pessimistic?
2016-03-2092
Conclusion
• AIs are getting strong
– The singularity is near
– Optimistic? Pessimistic?
• I am machine learning researche...
Conclusion
• AIs are getting strong
– The singularity is near
– Optimistic? Pessimistic?
• I am machine learning researche...
Reference
• Chemers, M. (2014). An integrative theory of leadership. Psychology Press.
• Mills, D. Q. (2005). Leadership: ...
Reference
• http://waitbutwhy.com/2015/01/artificial-
intelligence-revolution-1.html
• http://waitbutwhy.com/2015/01/artif...
Image sources
• http://www.popsci.com/microsoft-makes-ai-easier
• http://kevinbinz.com/tag/machine-learning/
• http://onhe...
2016-03-2096
Thank you!
Any questions or comments?
JinYeong Bak
jy.bak@kaist.ac.kr
U&I Lab, KAIST
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20160320 workshop seoul

  1. 1. Artificial Intelligence? Machine Learning? JinYeong Bak jy.bak@kaist.ac.kr School of Computing, KAIST
  2. 2. About Me • JinYeong Bak (jy.bak@kaist.ac.kr) • Ph.D. student at KAIST, U&I Lab – MS degree at KAIST – BS degree at SKKU • Research interests – Machine Learning – Computational Social Science • Research interns – Microsoft Research Asia, 2013 – United Nations Pulse Lab Jakarta, 2016 2016-03-202
  3. 3. INTRODUCTION 2016-03-203
  4. 4. AlphaGo 2016-03-204
  5. 5. AlphaGo • Computer program – Developed by Google DeepMind – Play the board game Go • Algorithm: a combination of – Artificial neural networks – Machine learning (reinforcement learning) – Monte Carlo tree search 2016-03-205
  6. 6. AlphaGo 2016-03-206
  7. 7. AlphaGo 2016-03-207
  8. 8. So… 2016-03-208
  9. 9. Contents • Artificial Intelligence • My research 2016-03-209
  10. 10. ARTIFICIAL INTELLIGENCE 2016-03-2010
  11. 11. Frequently Asked Questions AlphaGo wins Lee Sedol 2016-03-2011
  12. 12. Frequently Asked Questions AlphaGo wins Lee Sedol • Can AlphaGo win all people? 2016-03-2011
  13. 13. Frequently Asked Questions AlphaGo wins Lee Sedol • Can AlphaGo win all people? • Can AI control human being? 2016-03-2011
  14. 14. Frequently Asked Questions AlphaGo wins Lee Sedol • Can AlphaGo win all people? • Can AI control human being? • Can AI make the Terminator? 2016-03-2011
  15. 15. Frequently Asked Questions AlphaGo wins Lee Sedol • Can AlphaGo win all people? • Can AI control human being? • Can AI make the Terminator? • Do we all die? 2016-03-2011
  16. 16. Frequently Asked Questions AlphaGo wins Lee Sedol • Can AlphaGo win all people? • Can AI control human being? • Can AI make the Terminator? • Do we all die? 2016-03-2011
  17. 17. AlphaGo • Computer program – Developed by Google DeepMind – Play the board game Go • Algorithm: a combination of – Artificial neural networks – Machine learning (reinforcement learning) – Monte Carlo tree search 2016-03-2012
  18. 18. Artificial intelligence The intelligence exhibited by machines 2016-03-2013
  19. 19. Artificial intelligence How to create computers and computer software that are capable of intelligent behavior 2016-03-2014
  20. 20. Artificial intelligence - Types • Artificial Narrow Intelligence (ANI) • Artificial General Intelligence (AGI) • Artificial Super Intelligence (ASI) 2016-03-2015
  21. 21. Artificial intelligence • Artificial Narrow Intelligence (ANI) – Weak AI – Specializes in one area – Ex) AlphaGo, Siri, Spam mail filter, Translator, etc… • Artificial General Intelligence (AGI) • Artificial Super Intelligence (ASI) 2016-03-2016
  22. 22. Artificial intelligence • Artificial Narrow Intelligence (ANI) • Artificial General Intelligence (AGI) – Strong AI (Human level AI) – Be as smart as a human across the board – “a very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly, and learn from experience.” • Artificial Super Intelligence (ASI) 2016-03-2017
  23. 23. Artificial intelligence • Artificial Narrow Intelligence (ANI) • Artificial General Intelligence (AGI) • Artificial Super Intelligence (ASI) – Be smarter than the best human brains in every field 2016-03-2018
  24. 24. Artificial intelligence • Artificial Narrow Intelligence (ANI) • Artificial General Intelligence (AGI) • Artificial Super Intelligence (ASI) – Be smarter than the best human brains in every field 2016-03-2018
  25. 25. Intelligence • The ability to learn or understand things or to deal with new or difficult situations 2016-03-2019
  26. 26. Intelligence • The ability to learn or understand things or to deal with new or difficult situations • Capacity for – Logic – Abstract thought – Understanding – Self-awareness – Communication – Learning – Emotional knowledge – Memory – Planning – Creativity – Problem solving 2016-03-2019
  27. 27. Human Intelligence Growth 2016-03-2020
  28. 28. Human Intelligence Growth 2016-03-2021
  29. 29. Human Intelligence Growth 2016-03-2022
  30. 30. Human Intelligence Growth 2016-03-2023
  31. 31. Human Intelligence Growth 2016-03-2024
  32. 32. AI is coming 2016-03-2025
  33. 33. Opinions on ASI Arrival 2016-03-2026
  34. 34. Opinions on ASI Arrival 2016-03-2027
  35. 35. Opinions on ASI Arrival • Optimism • Pessimism 2016-03-2028
  36. 36. Opinions on ASI Arrival • Optimism – AIs can solve any problems – Humans can have eternal life 2016-03-2029
  37. 37. Opinions on ASI Arrival • Pessimism – AIs work hard to achieve the goal 2016-03-2030
  38. 38. Opinions on ASI Arrival • Pessimism – AIs work hard to achieve the goal – AIs are amoral • Not moral • Not immoral • Not involving questions of right or wrong 2016-03-2030
  39. 39. Opinions on ASI Arrival • Pessimism – AIs work hard to achieve the goal – AIs are amoral • Not moral • Not immoral • Not involving questions of right or wrong 2016-03-2030
  40. 40. Opinions on ASI Arrival • Pessimism – AIs work hard to achieve the goal – AIs are amoral • Not moral • Not immoral • Not involving questions of right or wrong 2016-03-2030
  41. 41. Opinions on ASI Arrival • Pessimism – AIs work hard to achieve the goal – AIs are amoral • Not moral • Not immoral • Not involving questions of right or wrong – Can Humans control ASI? • ASI is smarter than humans 2016-03-2030
  42. 42. In the future… 2016-03-2031
  43. 43. My opinion More like optimism Reasons – The goal is given by human – Moral/Immoral is coming from human 2016-03-2032
  44. 44. My opinion 2016-03-2033
  45. 45. My opinion 2016-03-2033
  46. 46. My opinion 2016-03-2033
  47. 47. My opinion 2016-03-2033
  48. 48. My opinion More like optimism Reasons – The goal is given by human – Moral/Immoral is coming from human – I am machine learning researcher 2016-03-2034
  49. 49. OK… 2016-03-2035
  50. 50. MY RESEARCH – BACKGROUND 2016-03-2036
  51. 51. Artificial intelligence How to create computers and computer software that are capable of intelligent behavior 2016-03-2037
  52. 52. Machine learning • Subfield of artificial intelligence • Study of pattern recognition and computational learning theory 2016-03-2038
  53. 53. Topic modeling • Subfield of machine learning • Discovering the abstract "topics" that occur in a collection of documents 2016-03-2039
  54. 54. Topic modeling - Introduction 2016-03-2040
  55. 55. Topic modeling - Introduction 2016-03-2041
  56. 56. Topic modeling - Introduction 2016-03-2042
  57. 57. Topic modeling - Introduction 2016-03-2043
  58. 58. Topic modeling - Introduction 2016-03-2044
  59. 59. Topic modeling - Introduction • What are the topics discussed in the article? • How can we describe the topics? 2016-03-2045
  60. 60. Topic modeling - Assumption 2016-03-2046
  61. 61. Topic modeling - Assumption 2016-03-2047
  62. 62. Topic modeling - Assumption 2016-03-2048
  63. 63. Topic modeling - Assumption 2016-03-2049
  64. 64. Topic modeling 2016-03-2050 Korea Music Olympic Topic proportion of each document
  65. 65. Topic modeling 2016-03-2050 Korea Music Olympic Topic proportion of each document
  66. 66. Topic modeling 2016-03-2050 Korea Music Olympic Topic proportion of each document
  67. 67. Topic modeling 2016-03-2050 korea south korean kim lee music album song single live olympic summer medal gold winter Word distribution of each topic Korea Music Olympic Topic proportion of each document
  68. 68. Topic modeling 2016-03-2050 korea south korean kim lee music album song single live olympic summer medal gold winter Word distribution of each topic LDA Korea Music Olympic Topic proportion of each document
  69. 69. Topic modeling • Inputs – Document corpus – Parameters 2016-03-2051
  70. 70. Topic modeling • Inputs – Document corpus – Parameters • Models – LDA – HDP 2016-03-2051 LDA
  71. 71. Topic modeling • Inputs – Document corpus – Parameters • Models – LDA – HDP • Inferences – Gibbs sampling – Variational Inference 2016-03-2051 LDA
  72. 72. Topic modeling • Inputs – Document corpus – Parameters • Models – LDA – HDP • Inferences – Gibbs sampling – Variational Inference • Outputs – Topics – Topic proportions 2016-03-2051 LDA
  73. 73. MY RESEARCH – ONLINE LEARNING 2016-03-2052
  74. 74. Topic modeling • Inputs – Document corpus – Parameters • Models – LDA – HDP • Inferences – Gibbs sampling – Variational Inference • Outputs – Topics – Topic proportions 2016-03-2053
  75. 75. Topic modeling • Inputs – Document corpus – Parameters • Models – LDA – HDP • Inferences – Gibbs sampling – Variational Inference • Outputs – Topics – Topic proportions 2016-03-2053 LDA
  76. 76. Topic modeling • Inputs – Document corpus – Parameters • Models – LDA – HDP • Inferences – Gibbs sampling – Variational Inference • Outputs – Topics – Topic proportions 2016-03-2053 LDA
  77. 77. Documents size 2016-03-2054
  78. 78. New documents 2016-03-2055
  79. 79. Previous approach problem 2016-03-2056
  80. 80. Previous approach problem 2016-03-2056 LDA
  81. 81. Previous approach problem 2016-03-2056 LDA
  82. 82. Previous approach problem 2016-03-2056
  83. 83. Previous approach problem 2016-03-2056
  84. 84. Previous approach problem 2016-03-2056 LDA
  85. 85. Previous approach problem 2016-03-2056 LDA
  86. 86. Previous approach problem 2016-03-2056 LDA
  87. 87. Previous approach problem 2016-03-2056 LDA
  88. 88. Previous approach problem 2016-03-2056 LDA
  89. 89. My suggestion 2016-03-2057
  90. 90. My suggestion 2016-03-2057 LDA
  91. 91. My suggestion 2016-03-2057 LDA
  92. 92. My suggestion 2016-03-2057
  93. 93. My suggestion 2016-03-2057
  94. 94. My suggestion 2016-03-2057 LDA
  95. 95. My suggestion 2016-03-2057 LDA
  96. 96. My suggestion 2016-03-2058
  97. 97. My suggestion 2016-03-2058
  98. 98. Results 2016-03-2059
  99. 99. MY RESEARCH – COMPUTATIONAL SOCIAL SCIENCE 2016-03-2060
  100. 100. Computational Social Science • Computational approaches to the social sciences • Computers are used to model, simulate, and analyze social phenomena • Fields – Computational economics – Computational sociology – Computational psychology 2016-03-2061
  101. 101. My research • Self-disclosure in Twitter conversation • Leadership in the AJD 2016-03-2062
  102. 102. Leadership • A process of social influence in which a person can enlist the aid and support of others in the accomplishment of a common task [Chemers. 2014] 2016-03-2063
  103. 103. Leadership • A process of social influence in which a person can enlist the aid and support of others in the accomplishment of a common task [Chemers. 2014] • The ability to – Influence other people – Get them to do something significant • Energizing people toward a goal [Mills. 2005] 2016-03-2063
  104. 104. Leadership Styles [Lewin, et al. 1939] 2016-03-2064
  105. 105. Leadership Styles [Lewin, et al. 1939] • Autocratic – Get little input from group members – Control over all decisions 2016-03-2065
  106. 106. Leadership Styles [Lewin, et al. 1939] • Autocratic – Get little input from group members – Control over all decisions • Laissez-Faire – Give little guidance to group members – Leave them to decision-making 2016-03-2065
  107. 107. Leadership Styles [Lewin, et al. 1939] • Autocratic – Get little input from group members – Control over all decisions • Laissez-Faire – Give little guidance to group members – Leave them to decision-making • Democratic – Encourage group members to participate – Retain the final say in the decision-making 2016-03-2065
  108. 108. Leadership Styles • Target people – School children [Lewin, et al. 1939] – Work employee [Hoel. 2010] – USA president [Bligh, et al. 2004] & Prime minister [Kaarbo. 1997] 2016-03-2066
  109. 109. Leadership Styles • Target people – School children [Lewin, et al. 1939] – Work employee [Hoel. 2010] – USA president [Bligh, et al. 2004] & Prime minister [Kaarbo. 1997] • Relationships [Van. 2006] – Age – Health – Context 2016-03-2066
  110. 110. Leadership Styles • Target people – School children [Lewin, et al. 1939] – Work employee [Hoel. 2010] – USA president [Bligh, et al. 2004] & Prime minister [Kaarbo. 1997] • Relationships [Van. 2006] – Age – Health – Context • How about the kings in the old times? 2016-03-2066
  111. 111. Research Questions 1. Do kings show different kinds of leadership styles? 2016-03-2067
  112. 112. Research Questions 1. Do kings show different kinds of leadership styles? 2. What factors are related with kings’ leadership? – Context/Topics? – Members? – Time? 2016-03-2067
  113. 113. Dataset • What kinds of data are needed? 2016-03-2068
  114. 114. Dataset • What kinds of data are needed? • Requirements: records of king’s official duty activities – Discussions with government officials – King’s decisions – Long and large dataset 2016-03-2068
  115. 115. Dataset • What kinds of data are needed? • Requirements: records of king’s official duty activities – Discussions with government officials – King’s decisions – Long and large dataset • My answer: The Annals of the Joseon Dynasty 2016-03-2068
  116. 116. The Annals of the Joseon Dynasty • Series of books which describe about historical facts in Joseon dynasty • 1,893 books, 380,271 articles • 472 years (1392 – 1863) 2016-03-2069
  117. 117. The Joseon Dynasty • Ancient kingdom in Korean peninsula 2016-03-2070 Civilization V - Civilization and Scenario Pack: Korea
  118. 118. The Joseon Dynasty • Ancient kingdom in Korean peninsula 2016-03-2070 Civilization V - Civilization and Scenario Pack: Korea
  119. 119. The Joseon Dynasty • Ancient kingdom in Korean peninsula 2016-03-2070 Civilization V - Civilization and Scenario Pack: Korea Sejong the Great
  120. 120. The Joseon Dynasty • Ancient kingdom in Korean peninsula – From 1392 to 1897 – 27 kings – Capital city: Seoul – Religion: Neo-Confucianism 2016-03-2071
  121. 121. The Joseon Dynasty • Monarchial system – King governs the nation – King decides on official issues – King discusses it with government officials 2016-03-2072
  122. 122. The Joseon Dynasty • Monarchial system – King governs the nation – King decides on official issues – King discusses it with government officials 2016-03-2072 A screenshot of a historical drama - Yi san
  123. 123. The Joseon Dynasty • Monarchial system – King governs the nation – King decides on official issues – King discusses it with government officials 2016-03-2072 King A screenshot of a historical drama - Yi san
  124. 124. The Joseon Dynasty • Monarchial system – King governs the nation – King decides on official issues – King discusses it with government officials 2016-03-2072 King Government officials A screenshot of a historical drama - Yi san
  125. 125. The Joseon Dynasty • Monarchial system – King governs the nation – King decides on official issues – King discusses it with government officials 2016-03-2072 King Government officials historiographers A screenshot of a historical drama - Yi san
  126. 126. The Annals of the Joseon Dynasty • Contents 2016-03-2073
  127. 127. The Annals of the Joseon Dynasty • Contents – Human resources • Employment & Dismissal • Person information 2016-03-2073
  128. 128. The Annals of the Joseon Dynasty • Contents – Human resources • Employment & Dismissal • Person information – Government issues • Military • Tax & Population 2016-03-2073
  129. 129. The Annals of the Joseon Dynasty • Contents – Human resources • Employment & Dismissal • Person information – Government issues • Military • Tax & Population – Diplomatic relations • China • Japan 2016-03-2073
  130. 130. The Annals of the Joseon Dynasty • Contents – Human resources • Employment & Dismissal • Person information – Government issues • Military • Tax & Population – Diplomatic relations • China • Japan – Judgements • Punishment • Remission 2016-03-2073
  131. 131. The Annals of the Joseon Dynasty • Contents – Human resources • Employment & Dismissal • Person information – Government issues • Military • Tax & Population – Diplomatic relations • China • Japan – Judgements • Punishment • Remission – Observations • Astronomical phenomena • Weather 2016-03-2073
  132. 132. The Annals of the Joseon Dynasty • National Institute of Korean History (http://www.history.go.kr) – Translated it to modern Korean 2016-03-2074
  133. 133. The Annals of the Joseon Dynasty • National Institute of Korean History (http://www.history.go.kr) – Translated it to modern Korean – Tagged meta information • Title • Category (political, economic, social and cultural) • Entity (person, location, nation) 2016-03-2074
  134. 134. The Annals of the Joseon Dynasty • National Institute of Korean History (http://www.history.go.kr) – Translated it to modern Korean – Tagged meta information • Title • Category (political, economic, social and cultural) • Entity (person, location, nation) – Published on the web • http://sillok.history.go.kr 2016-03-2074
  135. 135. The Annals of the Joseon Dynasty 2016-03-2075
  136. 136. The Annals of the Joseon Dynasty 2016-03-2075
  137. 137. The Annals of the Joseon Dynasty 2016-03-2075
  138. 138. The Annals of the Joseon Dynasty 2016-03-2075
  139. 139. The Annals of the Joseon Dynasty 2016-03-2076
  140. 140. The Annals of the Joseon Dynasty 2016-03-2076 Time
  141. 141. The Annals of the Joseon Dynasty 2016-03-2076 Title Time
  142. 142. The Annals of the Joseon Dynasty 2016-03-2076 Title Time Body
  143. 143. The Annals of the Joseon Dynasty 2016-03-2076 Title Meta information Time Body
  144. 144. The Annals of the Joseon Dynasty 2016-03-2077 Combining two local districts
  145. 145. The Annals of the Joseon Dynasty 2016-03-2077 Facts Combining two local districts
  146. 146. The Annals of the Joseon Dynasty 2016-03-2077 Facts Combining two local districts
  147. 147. The Annals of the Joseon Dynasty 2016-03-2077 Facts Official A Combining two local districts
  148. 148. The Annals of the Joseon Dynasty 2016-03-2077 Facts Official A “It’s reasonable to combine two local districts.” Combining two local districts
  149. 149. The Annals of the Joseon Dynasty 2016-03-2077 Facts Official A King “It’s reasonable to combine two local districts.” Combining two local districts
  150. 150. The Annals of the Joseon Dynasty 2016-03-2077 Facts Official A King “It’s reasonable to combine two local districts.” Combining two local districts “How should we handle this?”
  151. 151. The Annals of the Joseon Dynasty 2016-03-2077 Facts Official A King Official B Official C “It’s reasonable to combine two local districts.” Combining two local districts “How should we handle this?”
  152. 152. The Annals of the Joseon Dynasty 2016-03-2077 Facts Official A King Official B Official C The king follows Official C’s suggestion. “It’s reasonable to combine two local districts.” Combining two local districts “How should we handle this?”
  153. 153. Methodology • Identify relevant articles – To avoid non-governmental affairs (e.g. observations) – Look at the kings words and decisions – 126K, 36% over all articles 2016-03-2078
  154. 154. Methodology • Identify relevant articles – To avoid non-governmental affairs (e.g. observations) – Look at the kings words and decisions – 126K, 36% over all articles • Identify king’s final decisions in the article – Build sixty candidate verbs • Order: 명하다, 命 • Approve: 윤허하다, 允 • Disapprove: 불허하다, 不允 • Reject: 따르지 않았다, 不從 • Follow: 따르다, 從之 – Look at the verbs in king’s last sentence and title 2016-03-2078
  155. 155. Ruling styles • Arbitrary Decision (AD) • Discussion and Order (DO) • Discussion and Follow (DF) 2016-03-2079
  156. 156. Ruling styles • Arbitrary Decision (AD) – Like autocratic style – No discussion with officials – Orders directly • Discussion and Order (DO) • Discussion and Follow (DF) 2016-03-2079
  157. 157. Ruling styles • Arbitrary Decision (AD) – Like autocratic style – No discussion with officials – Orders directly • Discussion and Order (DO) – Like democratic style – Discussion with officials – Orders, approves, or rejects at the end • Discussion and Follow (DF) 2016-03-2079
  158. 158. Ruling styles • Arbitrary Decision (AD) – Like autocratic style – No discussion with officials – Orders directly • Discussion and Order (DO) – Like democratic style – Discussion with officials – Orders, approves, or rejects at the end • Discussion and Follow (DF) – Like laissez-faire style – Discussion with officials – Follows officials suggestion 2016-03-2079
  159. 159. Ruling styles 2016-03-2080 • Arbitrary Decision (AD) example King Facts
  160. 160. Ruling styles 2016-03-2080 • Arbitrary Decision (AD) example King Facts “Remove all fences at the gates”
  161. 161. Ruling styles 2016-03-2081 • Discussion and Order (DO) example Agency A Official B Official C King King King
  162. 162. Ruling styles 2016-03-2081 • Discussion and Order (DO) example Agency A Official B Official C King King King “Please interrogate a suspect”
  163. 163. Ruling styles 2016-03-2081 • Discussion and Order (DO) example Agency A Official B Official C King King King “I don’t want to do that. Don’t ask me about that again” “Please interrogate a suspect”
  164. 164. Ruling styles 2016-03-2082 • Discussion and Follow (DF) example Facts Official A King Official B Official C The king follows Official C’s suggestion.
  165. 165. Research Question 1 1. Do kings show different kinds of leadership styles? 2016-03-2083
  166. 166. Results – Among kings 2016-03-2084 • Each king shows different ruling style – Multinomial test between king’s ruling style distribution ( < 0.001)
  167. 167. Results – Among kings 2016-03-2084 • Each king shows different ruling style – Multinomial test between king’s ruling style distribution ( < 0.001) • Tyrants (Yeonsangun, Gwanghaegun) show high value of AD
  168. 168. Research Question 2 2. What factors are related with kings’ leadership? – Context/Topics? – Members? – Time? 2016-03-2085
  169. 169. Methodology • Discover topics in each article – LDA [Blei et al. 2003] with 300 topics – LDA outputs a topic proportion for each article – LDA outputs a multinomial word distribution for each topic 2016-03-2086
  170. 170. Methodology • Discover topics in each article – LDA [Blei et al. 2003] with 300 topics – LDA outputs a topic proportion for each article – LDA outputs a multinomial word distribution for each topic • Identify who said what – To analyze the participants in the discussion – Look at subjects and person tags in front of the sentence of each quote – 20K people/agencies 2016-03-2086
  171. 171. Results - Topics Retirement Agriculture Remission Grants 신하 곡물 죄 한 필 은퇴 마을 법 한 구획 지위 한 구획 전하 하사 사람 창고 관여 안장 유능 사람 용서 한 지역 일 쌀 찬성 한 구역 의무 저장 반란 호필 직 흉년 사람 외피 2016-03-2087
  172. 172. Investigate the effects o Results - Topics 2016-03-2088 Sejong the Great Yeonsangun Injo
  173. 173. Investigate the effects o Results - Topics 2016-03-2088 Sejong the Great Yeonsangun Injo
  174. 174. Investigate the effects o Results - Topics 2016-03-2088 Sejong the Great Yeonsangun Injo
  175. 175. Investigate the effects o ) • Results Different from overall ( ) Results - Topics 2016-03-2088 Sejong the Great Yeonsangun Injo
  176. 176. • Remission of sins topic – Kings act DO than overall – Injo tends to DF Results - Topics 2016-03-2089 Sejong the Great Yeonsangun Injo
  177. 177. • Remission of sins topic – Kings act DO than overall – Injo tends to DF • Granting rewards topic – Sejong the Great acts DF – Yeonsangun acts arbitrarily – Injo tends to give grants to servants than overall Results - Topics 2016-03-2089 Sejong the Great Yeonsangun Injo
  178. 178. Results - Members • Investigate the effects of the participants in a discussion – Compute the mutual information among ruling styles 2016-03-2090
  179. 179. Results - Members • Investigate the effects of the participants in a discussion – Compute the mutual information among ruling styles • Results – Discussion and Order • Chief secretary • Local government officials 2016-03-2090
  180. 180. Results - Members • Investigate the effects of the participants in a discussion – Compute the mutual information among ruling styles • Results – Discussion and Order • Chief secretary • Local government officials – Discussion and Follow • Central government officials • Crown prince • Agency officials who remonstrate to the king 2016-03-2090
  181. 181. Results – Time • Investigate the changes over time – Look at the temporal difference of a king 2016-03-2091 Yeonsangun Injo
  182. 182. Results – Time • Investigate the changes over time – Look at the temporal difference of a king • Results – Yeonsangun becomes more arbitrary over time – Injo stays consistent in his ruling style 2016-03-2091 Yeonsangun Injo
  183. 183. Conclusion • AIs are getting strong – The singularity is near – Optimistic? Pessimistic? 2016-03-2092
  184. 184. Conclusion • AIs are getting strong – The singularity is near – Optimistic? Pessimistic? • I am machine learning researcher – Making algorithms and models for specific problems – Analyzing (text) dataset – Helping to make ASI 2016-03-2092
  185. 185. Conclusion • AIs are getting strong – The singularity is near – Optimistic? Pessimistic? • I am machine learning researcher – Making algorithms and models for specific problems – Analyzing (text) dataset – Helping to make ASI 2016-03-2092
  186. 186. Reference • Chemers, M. (2014). An integrative theory of leadership. Psychology Press. • Mills, D. Q. (2005). Leadership: How to lead, how to live. MindEdge Press. • Lewin, K., Lippitt, R., & White, R. K. (1939). Patterns of aggressive behavior in experimentally created “social climates”. The Journal of Social Psychology, 10(2), 269-299. • Bligh, M. C., Kohles, J. C., & Meindl, J. R. (2004). Charting the language of leadership: a methodological investigation of President Bush and the crisis of 9/11. Journal of Applied Psychology, 89(3), 562. • Hoel, H., Glasø, L., Hetland, J., Cooper, C. L., & Einarsen, S. (2010). Leadership styles as predictors of self-reported and observed workplace bullying. British Journal of Management, 21(2), 453-468. • Kaarbo, J. (1997). Prime minister leadership styles in foreign policy decision- making: A framework for research. Political Psychology, 553-581. • Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. the Journal of machine Learning research, 3, 993-1022. • Van Vugt, M. (2006). Evolutionary origins of leadership and followership. Personality and Social Psychology Review, 10(4), 354-371. 2016-03-2093
  187. 187. Reference • http://waitbutwhy.com/2015/01/artificial- intelligence-revolution-1.html • http://waitbutwhy.com/2015/01/artificial- intelligence-revolution-2.html • http://www.singularity.com 2016-03-2094
  188. 188. Image sources • http://www.popsci.com/microsoft-makes-ai-easier • http://kevinbinz.com/tag/machine-learning/ • http://onhech.blogspot.com/2013/10/laissez-faire- leadership-is-less-more.html • http://www.imbc.com/broad/tv/drama/isan/preview/16 73111_23417.html • https://en.wikipedia.org/wiki/Joseon • https://en.wikipedia.org/wiki/Korean_Peninsula • http://store.steampowered.com/app/99612 • http://sillok.history.go.kr • http://sillok.history.go.kr/viewer/viewtype1.jsp?id=kda_ 10103027_005 2016-03-2095
  189. 189. 2016-03-2096 Thank you! Any questions or comments? JinYeong Bak jy.bak@kaist.ac.kr U&I Lab, KAIST

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