Like electricity or the steam engine, Artificial Intelligence (AI) is a true general purpose technology: It can be used to drive economic gains, but also to project hard and soft power. Its widespread adoption will irrevocably change the international order as its effects on welfare, trade and defense transcend national boundaries. In this keynote speech, Simon Mueller, Expert on AI Governance and Executive Director of the AI Initiative of The Future Society, will provide perspective on the range of issues, speak about current dynamics and discuss options to address emerging challenges.

1. Image credit: NASA

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2
• Cybersecurity
• Algorithmic bias
• Privacy & danger of totalitarian
backsliding
• Autonomy & agency
• Weaponized AI
• Unemployment
• Inequality & digital divide
• "Unknown unknowns", etc.
• Productivity growth
• Access to goods & services
• Personalized education
• Better medical outcomes
• Safer roads
• Efficient drone & AV transport
• Poverty & Global Health
• Efficient energy & resource usage
• Etc.
Benefits from Innovation Risks

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Source: Dr. Greg Corrado, Principal Scientist, Google Brain Team
Artificial Intelligence
Making machines intelligent
Deep Reinforcement Learning
Artificial neural networks
Robotics
Making machines that move
IBM DeepBlue
Autonomous cars
AlphaGo
Check
scanners Machine Learning
Making machines that learn
AI is not necessarily similar or equivalent to human intelligence.
Rules engines
Expert systems
Etc.
Many layers (deep)

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• Humans develop ML
algorithms
• Data from humans &
society
• Humans interpret
output
• Humans build into
products & use in
society
Nicolas Miailhe, The Future Society

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7. 6
6
Source: Andrey Kurenkov
The birth of AI
1956
First fully
functional chess
AI developed
1958
1956
IBM Checkers
Al first
demonstrated
1962
Samuel’s program
wins game against
person
1968
First Go AI,
beats human
amateur
1986
Multi-layer neural
net approach
widely known
1992
RL and neural
net based back-
gammon AI shown
1994
Checkers AI
draws with
world champion
1997
IBM chess AI
beats world
champion
2008
MCTS Go AI
beats 4 dan
player
2014
Google buys
deep-RL AI company
for $400Mil
Chess AI beats
person in
tournament
1967
First world
computer chess
champion
1974
Convolutional
nets first
demonstrated
1989
First research
on Go with
stochastic search
1993
ConvNet with
RL for Go, 13
kyu (amateur)
1996
French researchers
advance Go AI
with MCTS
2006
MCTS based
Go AI reaches
5-dan rank
2012
Deep
Learning+MCST Go
AI beats top human
2016
Dartmouth
Conference
Samuel’s
Checkers AI
Bernstein’s
Chess AI
Checkers
AI Wins
Mac Hack
Zobrist’s AI
Kaissa
Backprop
CNN
TD-
Gammon
Monte
Carlo Go
Chinook
NeuroGo
Deep Blue
MCTS Go
Crazy Stone
Zen19
DeepMind
Alpha Go

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Source: https://www.youtube.com/watch?v=V1eYniJ0Rnk

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Pedestrian detection task using object detection models with TensorFlow Object Detection API
Source: https://www.youtube.com/watch?v=0hWW6FVcFAo&feature=youtu.be GitHub, thatbrguy

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ThisPersonDoesNotExist.com

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Source: Bloomberg, The Economist, https://www.theverge.com/2019/3/5/18251326/ai-startups-europe-fake-40-percent-mmc-report
… and Fraud
0
400
200
800
600
20112007 20152009 2013 2017
Mentions of AI and machine learning on earnings calls of
public companies
Hype …

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Military &
Security
Offensive capabilities
Defensive capabilities
Surveillance &
Control
Interference in domestics
dynamics
Government control
Economics &
Welfare
Prosperity
Talent & immigration
Long-term sustainability
Hard
power
Soft
power

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1
Genuinely new weapons (such as
autonomous systems)
2 Cybersecurity & Cyberwarfare
3 Augmentation of existing arsenal, esp.
nuclear weapons
4 Artificial General Intelligence

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• Autonomous weapons select and engage
targets without human intervention
• Benefits
• Reduces casualties for owner
• Downsides
• Lowers the threshold to go to war in
the first place
• Could become ubiquitous, and
proliferate uncontrollably
(authoritarian regimes, terrorists,
etc.)
https://futureoflife.org/open-letter-autonomous-weapons/
1) Lethal Autonomous Weapons Systems

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• Increase in data from IoT, digital economy,
wearables and biometrics
• Shortage of cyber defense talent
• Automated AI attacks ("at scale")
• Hack of AI systems such as neural networks
(adversarial attacks)
• Social engineering attacks (once Turing test
passed, via robots 'at scale')
Source: Roman Yampolskiy, World Government Summit, February 2018

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Source: Practical Black-Box Attacks against Machine Learning, by Nicolas Papernot, Patrick McDaniel, Ian Goodfellow, Somesh Jha, Z. Berkay Celik,
Ananthram Swami
• Malicious inputs
modified to yield
erroneous model
results
• These inputs are
often concealed
from human
observers

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• Early development of AI for Nuclear Weapons included threat detection, logistics planning etc.
• "Human in the loop", as dramatic consequences that a system failure would have
• Today, AI could bolster
• ISR (intelligence, surveillance, reconnaissance)
• Enhance the protection of the command & control facilities
• Non-nuclear deterrence (air defense etc.)
• Remote sensing in hard-to-access territories
• Autonomous systems could be a delivery alternative to ICBMs (e.g. Status-6)
• PRO: AI could enhance stability & rationality (better information and decision-making) as well
as better monitoring capabilities
• CON: Could kick-off a new arms race, modernization of arsenal, automating launch policies
Source: Dr Vincent Boulanin, Dec 7, 2018, https://cpr.unu.edu/ai-global-governance-ai-and-nuclear-weapons-promise-and-perils-of-ai-for-nuclear-
stability.html

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“The Nation which becomes
the leader in AI will be the
ruler of the world.”
Vladimir Putin, September 2017

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1 Interference in other states' democratic
processes
2 Consolidation of state power 'at home'

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Source: The spread of low-credibility content by social bots, Chengcheng Shao, Giovanni Luca Ciampaglia, Onur Varol, Kaicheng Yang, Alessandro Flammini,
Filippo Menczer; https://arxiv.org/abs/1707.07592

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Source: Xuexi Qiangguo. https://www.gatestoneinstitute.org/12988/china-social-credit-system, Photo: HKFP remix
• China's "Social Credit" system assigns every
person a constantly updated score based on
observed behaviors
• App on the left let's users earn "Xi Jinping
study points" – for giving correct answers to
quizzes, and for sharing articles
• China has started to block individuals from
taking ~11m flights and ~4m high-speed rail
trips (as of April 2018)

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27
Old school totalitarianism Digital totalitarianism
First-order surveillance
(wiretapping, mail, etc.)
Higher-order surveillance (actions,
personal network, intentions)
Legal interventions "Nudging" & changing of incentive
structures
Censorship & self-censorship Re-framing of discussions, infusion of
'alternative facts'

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1 Technological displacement & inequality
2 Monopolies & concentration of power
3 AI nationalism & competition

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Source: OECD HLEG Presentation in October, 2018
0
10
20
30
China, EU led by the UK, Israel, Canada, Japan ($B)
20122011 2013 20162014 2015 2017 2018
+58%
India Japan USACanadaOther Israel EU China

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0
20
40
60
United States employment, by type of work, M
Non-routine cognitive Routine cognitive
Routine manual Non-routine manual
Source: US Population Survey; Federal Reserve Bank of St. Louis (data / analysis limited to 1983-2014)
1983 2000 20141990 2010

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BHATXGAFAMI

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0
10
20
30
40
50
20072006 2012
Global sample (%)
20132008 2009 2010 2011 2014
Star scientists1 with
a corporate affiliation
Publication2 that include
an author with a corporate affiliation
1. The top 100 scientists based on citation-weighted publications 2. Citation-weighted
Source: University of Toronto

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1. Progress will be made by applying AI, not more scientific breakthroughs
2. AI platforms are largely open, lowering the barriers to entry
3. Models improve with training data, and both having more data and deploying techno-
utilitarian policies could give China a leg up
4. Strength in numbers: # of Chinese AI engineers > # of American AI engineers
5. Softer arguments around 'cut-throat' competition of Chinese entrepreneurs & ability
to not only copy, but design truly innovative products
Source: Lee Kai-Fu: AI Superpowers

38. CERN: Large Hadron Collider (Geneva,
Switzerland)

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Act fast: Window of Opportunity is now – before AI
race is in 'full speed', and interests are 'locked in'
Upskill: Policy-makers today are lacking talent
to respond adequately
Coordinate: Arms races are coordination
problems. Need to foster transparency & dialogue
Regulate: Build consensus to ban or
restrict/regulate autonomous weapons
Research: Too many questions are still unanswered –
about security, LAWS, jobs, etc.
Protect liberal values: Citizens as the sovereign of
their countries, need to actively fight for liberal values
De-concentrate power: Monitor and regulate digital
giants, protect check-and-balances for governments
and limit surveillance & manipulation

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Simon.Mueller@TheFutureSociety.org
Sim0nMueller
TheFutureSociety.org