Real-world Stories and Long-term Risks and Opportunities. Tom Dietterich, Ph.D. Technical and Business Perspectives on the Current and Future Impact of Machine Learning - MLVLC October 20, 2015

1. Artificial Intelligence:
Progress and Challenges
Tom Dietterich

2. Tool AI
High-Stakes
Autonomy
Near-Term
Risks
?
Technological
Unemployment

3. What is AI?
Smart Software
 vision, speech, touch
 choosing actions to achieve goals
 learning
 understanding and predicting
behavior
Credit: Andrej Karpathy, Li Fei-Fei

4. Exciting Progress: Perception
2013 2014 2015
23% Word Error
8%
Google Speech Recognition
Credit: Fernando Pereira & Matthew
Firestone, Google
Google Translate from Images
Credit: www.bbc.com
“a black and white cat is
sitting on a chair."
Credit: Jeff Donahue, Trevor Darrell

5. Exciting Progress: Perception
Deep

6. Exciting Progress: Reasoning (SAT)
Credit: Vijay
Ganesh

7. Exciting Progress: Reasoning (Poker)
Moore’s
Law
Heads-Up Limit
Texas Hold’em
Rhode
Island
Hold’em
Credit: Michael
Bowling

8. Exciting Progress: Chess & Go
Monte Carlo Tree Search
Credit: Martin Mueller

9. Exciting Progress: Collaborative Systems
Red: Best AI solution
Yellow: “Foldit Void Crushers
Group” solution
Blue: X-Ray Crystal Structure
solution
Sept 20, 2011

10. What’s Next?
Tool AI
• Google, Bing
• IBM’s Watson
• Siri, Cortana, Google Now
• Google Translate
• Skype Real-Time Translation
Autonomous AI
• AI Hedge Funds
• High Speed Trading
• Self-Driving Cars
• Automated Surgical Assistants
• Smart Power Grid
• Autonomous Weapons

11. Tool AI

12. Tool AI: What’s Next?
Deeper understanding of video:
• What type of play?
• Who carried the ball?
• Was the pass complete?
• Which players made mistakes?
• Which players achieved their
goals?
Credit: Alan Fern

13. Tool AI: What’s Next?
Deeper understanding of text:
• Is Yoadimnadji dead? Yes
• Is he in Paris? Yes
• Is he married? Yes
• Where is his wife? In Paris
• Where will she be in the future? In
Chad
“Pascal Yoadimnadji has been
evacuated to France on
Wednesday after falling ill and
slipping into a coma in Chad.
His wife, who accompanied
him to Paris, will repatriate his
body to Chad.”

14. Tool AI: What’s Next?
Linking Big Data to Medicine:
• Web search logs can detect adverse
drug interaction events better than
FDA’s existing Adverse Drug
Interaction Reporting Service
White, Harpaz, Shah, DuMouchel, Horvitz, 2014

15. Tool AI: What’s Next?
Improved Personal Assistants that
combine
• Knowledge of recipes (lasagna
ingredients)
• Wine pairing recommendations
(cabernet or pinot noir)
• Brother’s home address
• Routes to brother’s home address
• Stores along that route that have
cheap cabernet or pinot in stock
to produce a plan
Source: Wired August 12, 2014

16. High-Stakes
Autonomy
Near-Term
Risks

17. Autonomous AI Systems: What’s Next?
• AI Hedge Funds
• High Speed Trading
• Self-Driving Cars
• Automated Surgical Assistants
• Smart Power Grid
• Autonomous Weapons

18. The Motivations The Dangers
High-Stakes Autonomy
 Advances in AI enable exciting
applications
 There is a great potential to save
lives
 There is a need to act at lightning
speed
 Bugs
 Cyber Attacks
 Mixed Autonomy
 Misunderstanding User
Commands

19. Software Quality
 Many AI methods give only probabilistic
guarantees
 Research Question: How can we ensure
safe performance of AI-based
autonomous systems?
"a young boy is holding a
baseball bat."
Credit: Andrej Karpathy, Li Fei-Fei

20. Cyber Attacks
 High-stakes systems  large and enticing “attack surface”

21. Cyber Attacks on AI Systems
Training Set Poisoning:
 Make yourself invisible to a computer
vision system
 Make yourself look “normal” to an
anomaly detection system
 Bias the behavior of the system
 Bid slightly higher on certain stocks
 Prefer to show certain advertisements
Credit: Katherine Hannah

22. Mixed Autonomy
 Auto-pilot unexpected hand-off to
pilots
 Pilots lack situational awareness
and make poor decisions
 Question: How can we make
imperfect autonomous systems
safe?
AF447 Pilots Final Conversation
Pilot 1: “What the...how is it we
are going down like this?”
Pilot 2: “See what you can do with
the commands up there, the
primaries and so on...Climb climb,
climb, climb
Credit: www.aviationlawmonitor.com

23. Incomplete/incorrect Commands
 “Fetch me some water”
 Question: How can the
computer reliably infer
what the user
intended?
Credit: www.disney.com

24. Trustable AI for Autonomy
Many research teams are at work
Verification and Self-Monitoring
Knowledge of Desirable and Acceptable Behavior
Improved User Interaction

25. Technological
Unemployment

26. 1980 1990 2000 2010
40
80
120
160
200
240
280
320
US Industrial Production
US Manufacturing Employment
Index:01.1972=100
Similar trends are seen worldwide
Source: Andrew McAfee / US Federal Reserve
US is Producing More with Fewer
Employees

27. As AI advances, many existing jobs have
the potential to be automated
Source: Frey & Osborne, 2014: “The future of employment: How susceptible are jobs to computerisation?”

28. Three Reasons to be Optimistic
 AI often complements human intelligence rather than
replacing it
 Increases in productivity increases in wealth
increases in consumption demand for new
goods and experiences  new kinds of jobs
 A focus on current jobs, underestimates the creativity
of people to develop new products and services, new
industries, etc.

29. What will be the new jobs?
 Jobs involving hard-to-automate skills
 high levels of social skills
 deep understanding of human experience
and emotion
 high levels of creativity
 Jobs where human + machine is better
than either alone
 Augmented Cognition
 combining strategic thinking with detailed
tactics: “Centaur Chess”
 combining physical dexterity with
information access: augmented reality
vehicle maintenance
Source: Tartajubow.blogspot.com
Source: metaio / designboom.com

30. Historical and cultural artifacts become
more valuable
 AI cannot produce another Roman
Empire, Greek Civilization, or Al Andaluz
 AI + Augmented Reality may make
tourism even more compelling and
meaningful
Credit: http://www.hellovisitspain.com

31. Life-Long Personal AI Assistant?
 Human-machine pairs work best when they
know each other very well
 strengths and weaknesses
 easy communication
 preferred ways of sharing tasks
 A vision:
 Student enrolls in technical college
 Student is given an AI personal assistant
 The student and the assistant train together
 Learn how to solve problems jointly and efficiently
 Employer hires the pair together
source: starwars.wikia.com

32. Tool AI
High-Stakes
Autonomy
Near-Term
Risks
?
Technological
Unemployment

33. Some people are very afraid
December 2, 2014
October 27, 2014

34. AI Misconceptions
Intelligence is Not a Threshold Phenomenon
 Progress in AI is the accumulation of thousands of incremental
improvements
 Robots will not “wake up” one day and be “truly intelligent” or
“superintelligent” or “conscious” or “sentient”
 “Tool AI” systems are already smarter than people along many
dimensions

35. AI Misconceptions
Autonomy Will Not Happen Spontaneously
 There is no threshold above which AI systems suddenly have free will
 Systems need to be designed and built to be autonomous
 They must be given access to resources (money, power, materials,
generalized task markets, communications with people)

36. The danger of
“Autonomous AI” is not “AI”
but “Autonomy”
An autonomous system can be dangerous for many reasons:
 It could consume vast resources
 It could injure or kill people
 It could apply AI to help it do these things

37. How Can We Maintain Control of
Autonomous Systems?
Case 1: Decisions are made at human time scales
Examples:
 Aircraft autopilot
 Most factory robots
 Surgical robots
Humans can monitor and respond to problems
 Similar to supervision in a human organization

38. Case 2: Very High Speed Decision Making
Examples:
 stock market
 power grid
 self-driving cars
 ≥18,520 market crashes and spikes
have been detected 2006-2011
below the 950ms level
Flash Crash (10.5.2010)

39. Automated Monitoring
 Signals might predict or
detect flash crashes
 Example: Inventory of High-
Speed Traders
Normal market Flash crash
Source: Vuorenmaa, Tommi; Wang, Liang, 2013

40. When Monitoring Detects A Problem:
Then What?
Stock market:
 Halt trading
 Unwind transactions
Self-driving car:
 Slow down and pull over in a safe spot
Smart Electric Grid:
 ??

41. We Should Never Create a
Fully Independent Autonomous System
By definition, a fully independent
autonomous system is a system over
which we have no control

42. Summary
 AI has been making steady progress
 Exciting applications of Tool AI are coming soon
 Potential applications of Autonomous AI are being proposed
 Many of these involve high-stakes decision making
 There are many risks that must be addressed before it will be safe to field
such systems
 Information technology—including AI—may be contributing to
unemployment but the picture is far from clear
 Tool AI will not spontaneously become autonomous
 We must find ways to control autonomous AI systems