Download Robotics

Living in a Robot Society
Artificial Intelligence, Humans & Robots
Dr. Koen V. Hindriks
Interactive Intelligence
Technische Universiteit Delft
[email protected]
http://ii.tudelft.nl/~koen/
twitter: @konradvh
Koen Hindriks
AG Jaarcongres 2016
Outline
• Man versus Machine – Smarter Machines
• Living in a Robot Society
• Who is in Control? Man + Machine
• Example robots in care & education
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
2
MAN VERSUS MACHINE
SMARTER MACHINES
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
3
Artificial Intelligence (AI)
Weak AI
Creating machines that can perform a task that
requires humans to apply intelligence.
• Many examples.
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
4
Artificial Intelligence (AI)
Strong AI
Creating a machine with its own
agenda that outperforms humans
at every (intellectual) skill.
– EU
– US BRAIN Initiative
• Not there now, not sure we will ever get there.
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
5
Computing Primes
Computing machines are much(!) better at …
computing than humans are.
Important for security and automating finance.
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
6
Chess (IBM Deep Blue 1997)
Algorithm = Game tree search + heuristics
Human Game
Database
No human has won even a single game against
a sufficiently strong computer under tournament
conditions since 2005.
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
7
Self-Driving Car
(Stanford’s Stanley 2005)
Full Automation Human Factors Challenge
1. Driver workload: Partial automation leaves
driver under-loaded for paying attention.
2. Situation awareness: Driver likely to “tune
out”, losing awareness of driving hazards.
3. Complacency: If automated system works
99% of the time, driver assumes 100%.
4. Skill degradation: If driver doesn’t have to
drive, s/he forgets highest driving skills.
Steven Shladover, University of California.
Won DARPA Grand Challenge and navigated
successfully across 132 miles without a driver.
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
8
Jeopardy (IBM Watson 2011)
Algorithms = NLP + ML + Betting Strategy
Question
Analysis
Hypothesis
Generation
Ranking
& Betting
Internet data (Wikipedia, etc.)
Humans beaten at a game they were supposed
by most to outperform machines.
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
9
Go (Google’s AlpaGo 2016)
Algorithm = Deep Learning +
Reinforcement Learning
Human
Games
Bootstrapping
Machine
Learn through
Self-play
Go is more difficult than chess for a machine
because the game has less structure and the
space of options is much larger.
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
10
Have Games been “Solved”?
Machines beat humans at perfect information
games but not yet at imperfect information
games.
Man-Machine Heads-Up, No-Limit Texas Hold
'em, Poker Competition (CMU’s Claudico 2015,
loss close to tie)
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
11
LIVING IN A ROBOT SOCIETY
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
12
AI Key Enabler for Robotics
• Amazing achievements, major progress in AI.
Now a mature engineering science.
• Key enabler for automation and robotics.
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
13
Robotics Market Potential
Drivers for potential:
• Falling prices
• Performance improvements
Source: BCG
KPMG Tech Trend Index
Koen Hindriks
▲
12%
Robotics
▲
10%
Cloud
Computing
▲
26%
Digital Payment
AAAIJaarcongres
2015
AG
2016
14
Robotics: Increase in Welfare
• More efficient production processes, tailored
much more to our needs.
• Better healthcare.
• Better education.
• Improved sustainability.
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
15
Where are we heading?
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
16
Dream: Personal Service Robot
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
17
Empower Rather than Replace
Computers and robots are complements for
humans, not substitutes.
Peter Thiel: “The most valuable businesses of
coming decades will be built by entrepreneurs
who seek to empower people rather than try to
make them obsolete.”
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
18
The Robot Society
In a robot society, (mobile) robots enter our
daily living space (move out of the factory).
My focus: social robots for care & education.
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
19
WHO IS IN CONTROL?
MAN + MACHINE
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
20
Who is in control?
• Machines have been getting smarter only
because of us.
• There are no machines that want anything in
any sense similar to how we want things.
Complementarity:
The Future = Man + Machine.
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
21
Lazy: Humans are the Problem
Users get isolated in a filter bubble &
become separated from information
that disagrees with their viewpoints.
Users rely or “trust” on machine:
75% of what people watch is from
some sort of recommendation.
Driver does not pay attention, “tunes
out”, assumes 100% reliability, and
forgets driving skills.
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
22
Wicked: Humans are the Problem
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
23
Crashes: Software is the Problem
Why did my laptop crash?
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
24
Crashes: Software is the Problem
2010, May 6 Flash Crash: NYSE dropping 9% in minutes.
Why did the stock market crash?
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
25
Crashes: Software is the Problem
Why did my self-driving car crash?
• Now: VW emission scandal, car recalls
(Toyato: 13M cars, GM: 9M cars, etc.)
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
26
Meaningful Human Control
End of the day we want humans to be
responsible & liability issues clearly addressed.
The Biggest Challenge
=
Ensure that humans remain in control!
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
27
A Few Examples from the large Robotics Landscape
ROBOTS FOR
CARE AND EDUCATION
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
28
ASUS Zenbo
Only $599!?!
Release date not yet known.
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
29
Semi Autonomous Care Robot
(SACRO)
Aim: develop robot platform that can support daily
activities in home care context.
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
30
Robot Care Systems
• Aim: support elderly to more actively and
safely spend their time and live longer
independently in their own home.
• LEA: Lean Elderly Assistant
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
31
RoboCARE Lab
• Autism: Social skill development through interactions
with robot
Aim: robot companion
• Elderly care: Assistance & cognitive stimulation
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
32
Tinybots: Tessa
• Aim: support people with dementia
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
33
RoboBuddy
• Aim: buddy for people with early stages of
dementia
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
34
Personalised Assistant for
healthy Lifestyle (PAL)
Aim: support children (7-14) with diabetes to motivate
them to maintain a healthy lifestyle.
Robot as motivator, teacher, and fun pal.
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
35
Personalised Assistant for
healthy Lifestyle (PAL)
“… pitiful
when he
falls, he may
hurt himself”
“Charlie and
I are pretty
much
friends”
“Charlie has
taught me a lot”
“Charlie often
says nice
things to me”
“I like him”
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
36
RoboTutor
• Aim:
– Teaching assistant
– Computational thinking
– Learn to interact with robots
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
37
Happy or Sad Robot
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
38
Interacting with Politicians
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
39
Learn to Interact with Robots
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
40
AI, Humans, and Robots
Smarter Machines
•Weak AI: perception, learning,
language, problem solving.
•Strong AI not there.
Robots in Care & Education
Living in a Robot Society
•AI key enabler for robotics.
•Empower humans not replace.
Who is in Control?
•Humans & bugs are problem,
need new reliability standards.
•Meaningful human control.
Koen Hindriks
AAAIJaarcongres
2015
AG
2016
41