20160320 workshop seoul

1. Artificial Intelligence?
Machine Learning?
JinYeong Bak
jy.bak@kaist.ac.kr
School of Computing, KAIST

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. INTRODUCTION
2016-03-203

4. AlphaGo
2016-03-204

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. AlphaGo
2016-03-206

7. AlphaGo
2016-03-207

8. So…
2016-03-208

9. Contents
• Artificial Intelligence
• My research
2016-03-209

10. ARTIFICIAL INTELLIGENCE
2016-03-2010

11. Frequently Asked Questions
AlphaGo wins Lee Sedol
2016-03-2011

12. Frequently Asked Questions
AlphaGo wins Lee Sedol
• Can AlphaGo win all people?
2016-03-2011

13. Frequently Asked Questions
AlphaGo wins Lee Sedol
• Can AlphaGo win all people?
• Can AI control human being?
2016-03-2011

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. 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. 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. 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. Artificial intelligence
The intelligence exhibited by machines
2016-03-2013

19. Artificial intelligence
How to create computers and computer software that
are capable of intelligent behavior
2016-03-2014

20. Artificial intelligence - Types
• Artificial Narrow Intelligence (ANI)
• Artificial General Intelligence (AGI)
• Artificial Super Intelligence (ASI)
2016-03-2015

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. 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. 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. 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. Intelligence
• The ability to learn or understand things or to deal with new
or difficult situations
2016-03-2019

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. Human Intelligence Growth
2016-03-2020

28. Human Intelligence Growth
2016-03-2021

29. Human Intelligence Growth
2016-03-2022

30. Human Intelligence Growth
2016-03-2023

31. Human Intelligence Growth
2016-03-2024

32. AI is coming
2016-03-2025

33. Opinions on ASI Arrival
2016-03-2026

34. Opinions on ASI Arrival
2016-03-2027

35. Opinions on ASI Arrival
• Optimism
• Pessimism
2016-03-2028

36. Opinions on ASI Arrival
• Optimism
– AIs can solve any problems
– Humans can have eternal life
2016-03-2029

37. Opinions on ASI Arrival
• Pessimism
– AIs work hard to achieve the goal
2016-03-2030

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. 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. 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. 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. In the future…
2016-03-2031

43. My opinion
More like optimism
Reasons
– The goal is given by human
– Moral/Immoral is coming from human
2016-03-2032

44. My opinion
2016-03-2033

45. My opinion
2016-03-2033

46. My opinion
2016-03-2033

47. My opinion
2016-03-2033

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. OK…
2016-03-2035

50. MY RESEARCH – BACKGROUND
2016-03-2036

51. Artificial intelligence
How to create computers and computer software that
are capable of intelligent behavior
2016-03-2037

52. Machine learning
• Subfield of artificial intelligence
• Study of pattern recognition and computational
learning theory
2016-03-2038

53. Topic modeling
• Subfield of machine learning
• Discovering the abstract "topics" that occur in a
collection of documents
2016-03-2039

54. Topic modeling - Introduction
2016-03-2040

55. Topic modeling - Introduction
2016-03-2041

56. Topic modeling - Introduction
2016-03-2042

57. Topic modeling - Introduction
2016-03-2043

58. Topic modeling - Introduction
2016-03-2044

59. Topic modeling - Introduction
• What are the topics discussed in the article?
• How can we describe the topics?
2016-03-2045

60. Topic modeling - Assumption
2016-03-2046

61. Topic modeling - Assumption
2016-03-2047

62. Topic modeling - Assumption
2016-03-2048

63. Topic modeling - Assumption
2016-03-2049

64. Topic modeling
2016-03-2050
Korea
Music
Olympic
Topic proportion of each document

65. Topic modeling
2016-03-2050
Korea
Music
Olympic
Topic proportion of each document

66. Topic modeling
2016-03-2050
Korea
Music
Olympic
Topic proportion of each document

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. 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. Topic modeling
• Inputs
– Document corpus
– Parameters
2016-03-2051

70. Topic modeling
• Inputs
– Document corpus
– Parameters
• Models
– LDA
– HDP
2016-03-2051
LDA

71. Topic modeling
• Inputs
– Document corpus
– Parameters
• Models
– LDA
– HDP
• Inferences
– Gibbs sampling
– Variational Inference
2016-03-2051
LDA

72. Topic modeling
• Inputs
– Document corpus
– Parameters
• Models
– LDA
– HDP
• Inferences
– Gibbs sampling
– Variational Inference
• Outputs
– Topics
– Topic proportions
2016-03-2051
LDA

73. MY RESEARCH – ONLINE LEARNING
2016-03-2052

74. Topic modeling
• Inputs
– Document corpus
– Parameters
• Models
– LDA
– HDP
• Inferences
– Gibbs sampling
– Variational Inference
• Outputs
– Topics
– Topic proportions
2016-03-2053

75. Topic modeling
• Inputs
– Document corpus
– Parameters
• Models
– LDA
– HDP
• Inferences
– Gibbs sampling
– Variational Inference
• Outputs
– Topics
– Topic proportions
2016-03-2053
LDA

76. Topic modeling
• Inputs
– Document corpus
– Parameters
• Models
– LDA
– HDP
• Inferences
– Gibbs sampling
– Variational Inference
• Outputs
– Topics
– Topic proportions
2016-03-2053
LDA

77. Documents size
2016-03-2054

78. New documents
2016-03-2055

79. Previous approach problem
2016-03-2056

80. Previous approach problem
2016-03-2056
LDA

81. Previous approach problem
2016-03-2056
LDA

82. Previous approach problem
2016-03-2056

83. Previous approach problem
2016-03-2056

84. Previous approach problem
2016-03-2056
LDA

85. Previous approach problem
2016-03-2056
LDA

86. Previous approach problem
2016-03-2056
LDA

87. Previous approach problem
2016-03-2056
LDA

88. Previous approach problem
2016-03-2056
LDA

89. My suggestion
2016-03-2057

90. My suggestion
2016-03-2057
LDA

91. My suggestion
2016-03-2057
LDA

92. My suggestion
2016-03-2057

93. My suggestion
2016-03-2057

94. My suggestion
2016-03-2057
LDA

95. My suggestion
2016-03-2057
LDA

96. My suggestion
2016-03-2058

97. My suggestion
2016-03-2058

98. Results
2016-03-2059

99. MY RESEARCH – COMPUTATIONAL
SOCIAL SCIENCE
2016-03-2060

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. My research
• Self-disclosure in Twitter conversation
• Leadership in the AJD
2016-03-2062

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. 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. Leadership Styles [Lewin, et al. 1939]
2016-03-2064

105. Leadership Styles [Lewin, et al. 1939]
• Autocratic
– Get little input from group members
– Control over all decisions
2016-03-2065

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. 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. 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. 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. 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. Research Questions
1. Do kings show different kinds of leadership styles?
2016-03-2067

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. Dataset
• What kinds of data are needed?
2016-03-2068

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. 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. 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. The Joseon Dynasty
• Ancient kingdom in Korean peninsula
2016-03-2070
Civilization V - Civilization and Scenario Pack: Korea

118. The Joseon Dynasty
• Ancient kingdom in Korean peninsula
2016-03-2070
Civilization V - Civilization and Scenario Pack: Korea

119. The Joseon Dynasty
• Ancient kingdom in Korean peninsula
2016-03-2070
Civilization V - Civilization and Scenario Pack: Korea
Sejong
the Great

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. The Joseon Dynasty
• Monarchial system
– King governs the nation
– King decides on official issues
– King discusses it with government officials
2016-03-2072

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. 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. 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. 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. The Annals of the Joseon Dynasty
• Contents
2016-03-2073

127. The Annals of the Joseon Dynasty
• Contents
– Human resources
• Employment & Dismissal
• Person information
2016-03-2073

128. The Annals of the Joseon Dynasty
• Contents
– Human resources
• Employment & Dismissal
• Person information
– Government issues
• Military
• Tax & Population
2016-03-2073

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. 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. 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. 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. 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. 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. The Annals of the Joseon Dynasty
2016-03-2075

136. The Annals of the Joseon Dynasty
2016-03-2075

137. The Annals of the Joseon Dynasty
2016-03-2075

138. The Annals of the Joseon Dynasty
2016-03-2075

139. The Annals of the Joseon Dynasty
2016-03-2076

140. The Annals of the Joseon Dynasty
2016-03-2076
Time

141. The Annals of the Joseon Dynasty
2016-03-2076
Title
Time

142. The Annals of the Joseon Dynasty
2016-03-2076
Title
Time
Body

143. The Annals of the Joseon Dynasty
2016-03-2076
Title
Meta
information
Time
Body

144. The Annals of the Joseon Dynasty
2016-03-2077
Combining two local districts

145. The Annals of the Joseon Dynasty
2016-03-2077
Facts
Combining two local districts

146. The Annals of the Joseon Dynasty
2016-03-2077
Facts
Combining two local districts

147. The Annals of the Joseon Dynasty
2016-03-2077
Facts
Official A
Combining two local districts

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. 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. 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. 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. 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. 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. 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. Ruling styles
• Arbitrary Decision (AD)
• Discussion and Order (DO)
• Discussion and Follow (DF)
2016-03-2079

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. 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. 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. Ruling styles
2016-03-2080
• Arbitrary Decision (AD) example
King
Facts

160. Ruling styles
2016-03-2080
• Arbitrary Decision (AD) example
King
Facts
“Remove all fences
at the gates”

161. Ruling styles
2016-03-2081
• Discussion and Order (DO) example
Agency A
Official B
Official C
King
King
King

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. 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. 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. Research Question 1
1. Do kings show different kinds of leadership styles?
2016-03-2083

166. Results – Among kings
2016-03-2084
• Each king shows different ruling style
– Multinomial test between king’s ruling style distribution ( < 0.001)

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. Research Question 2
2. What factors are related with kings’ leadership?
– Context/Topics?
– Members?
– Time?
2016-03-2085

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. 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. 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. Investigate the effects o
Results - Topics
2016-03-2088
Sejong the Great
Yeonsangun
Injo

173. Investigate the effects o
Results - Topics
2016-03-2088
Sejong the Great
Yeonsangun
Injo

174. Investigate the effects o
Results - Topics
2016-03-2088
Sejong the Great
Yeonsangun
Injo

175. Investigate the effects o )
• Results
Different from overall
( )
Results - Topics
2016-03-2088
Sejong the Great
Yeonsangun
Injo

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. • 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. Results - Members
• Investigate the effects of the participants in a discussion
– Compute the mutual information among ruling styles
2016-03-2090

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. 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. Results – Time
• Investigate the changes over time
– Look at the temporal difference of a king
2016-03-2091
Yeonsangun Injo

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. Conclusion
• AIs are getting strong
– The singularity is near
– Optimistic? Pessimistic?
2016-03-2092

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. 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. 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. 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. 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
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189. 2016-03-2096
Thank you!
Any questions or comments?
JinYeong Bak
jy.bak@kaist.ac.kr
U&I Lab, KAIST