Artificial Intelligence
Natural Progression
• We can solve logical problems
• We can build machines to solve general problems
• Can we make the machine replace us?
• Roots in science fiction
– Androids
• An android is an anthropomorphic robot - i.e. a robot that looks
like a human. For example Valerie
• Turing test
– Can a computer behave in such a way that someone
interacting with it remotely cannot differentiate
between it and a human being?
What do humans do well
• Process information
– Language
– Images
•
•
•
•
•
Reason
Create
Relate to other humans
Make intuitive decisions
Experience and exhibit emotion
– Enjoy entertainment
What do computers do well
• Process data quickly
• Handle large amounts of data
Computers simulating humans
• Have to understand the process
• Build a good model for the process
• Resolve complexities
Example: Chess
• Number of possible unique chess games is 10120.
• In 1957, artificial intelligence pioneers Herbert Simon and
Allen Newell predicted that a computer would beat a
human at chess within 10 years.
• BELLE, a chess program by Ken Thompson and Joe
Condon, became the first computer to be awarded the title
of US chess master, in 1983.
• BELLE didn’t try to do what a human would do. Instead,
BELLE took advantage of what computers do well.
• In May 1997, IBM's Deep Blue Supercomputer
played a fascinating match with the reigning World
Chess Champion, Garry Kasparov and won 3 ½ to 2
½
Example: Chess
• Does this count as AI?
– Computer beating best human
– Computer not playing as human would
Other Successes
• Language understanding
– Eliza 1967
• Speech recognition
– Dragon Naturally speaking
– Phone company systems
– Voice mail systems
• Language translation
Difficulties
• Humans are complex beings and understand
– Language issues
• Time flies like an arrow
• Fruit flies like a banana
– Searching for tables
• Table
• table chair
• 98% correct is often not enough
– 40 typos in a page
• The search space can get very large
Techniques
• Build a search tree to model the state space
• Find good methods of evaluating possibilities
• Use your evaluation methods to prune the tree
First steps in TicTacToe
First move
center
corner
side
center
. . .
. O.
. . X
. . .
. X.
. . O
. . .
. XO
. . .
opp. corener
corner
side
adj. corner
adj side
opp side
Turing Test
• A person tries to distinguish between a man and a
woman (responses over a typewriter). If you
replace one by a machine, does the game change?
• A person and a machine are behind a curtain. An
interrogator sends questions to each, and receives
text message answers from each. Can the
interrogator tell which is which?
• Turing predicted machines would be able to be
programmed to pass the Turing (or imitation) test
• 50 years of philosophical debate have followed
Strong AI vs. Weak AI
• Strong artificial intelligence states that a
computer with the right program can in fact
be mental (like a human being)
• Weak artificial intelligence just aims to
solve problems, not necessarily to be mental
or model human behavior.
Weak AI
• A lot of it was based on rules
– Rule-based expert systems:
• If (Smoker) and (White Male) then (Chance of Lung Cancer by
Age 60 > x)
– Rule-based categorization
• If news story mentions baseball or hockey or … at least three
times, then it should be categorized under Sports
• Recently, greater focus on probabilistic and
statistical methods
Probabilistic Inference
• Xi are diseases, boxes are symptoms
• Prob. of each disease given each symptom is known
• Given new set of symptoms, infer probs. of diseases
Machine Learning (ML)
• An increasingly popular subfield of Artificial
Intelligence
• Usually aimed at performing some particular
task, not building sentient machines
• Design of systems that improve (hopefully) as
they acquire knowledge or experience
ML slides taken (and modified) from Ken Williams’ tutorial
Typical Machine Learning Tasks
• Clustering
– Grouping similar items together
• Categorization
– Of text, images, news, into categories
• Recognition
– Speech, Voice, Handwriting
• Game playing
– Chess
• Autonomous performance
– Robots that play soccer or navigate themselves
Typical ML Tasks
• Clustering
Typical ML Tasks
• Categorization
Typical ML Tasks
• Recognition
Vincent Van Gogh
Michael Stipe
Mohammed Ali
Ken Williams
Burl Ives
Winston Churchill
Grover Cleveland
Typical ML Tasks
• Recognition
Little red corvette
The kids are all right
The rain in Spain
Bort bort bort
Typical ML Tasks
• Game playing
Typical ML Tasks
• Autonomous performance
What Do ML Systems Do: News
Categorization
• Start with a set of news articles, that have been
manually tagged with categories (Sports, Politics,
Business, Baseball, Customer Loss)
• Build a statistical model to represent the
characteristics of each category, based on the
above “training data”
• Upon a new article (“test data”), test it against the
models for the categories to see where it fits best
• What is learned is the model from the training set.
Then the learned model is applied to the test set.
• E.g. Voice recognition
When is ML useful?
• When you have lots of training data
• When you can’t hire enough people, or when
people are too slow
• When you can afford to be wrong sometimes
– ML systems have accuracies ranging from 50 to 85%
• When you need to find patterns
What are the alternatives?
Back to AI and the Human Brain:
Work in other sciences
• Neural Nets
– Build models of machines that think and learn
• Brain mapping
– Determine what clumps of neurons do
– Eventually map individual neurons
Questions Worth Exploring
• State of art
– State of the art in AI
– Technology in general
• Nature of thinking
– How does the brain do it?
– Must a machine duplicate the brain?
• What is learning?
• Philosophical
– What makes a machine human
• Science Fiction
State of the Art
What would happen if we kept asking the robot why it just gave the
answer that it gave an infinite number of times. Could it explain?
For example:
Input: How are you today?
Output: Good.
Input: Why "good"?
Output: I'm having a lovely day.
Input: Why?
Output: I don't know.
Input: Why don't you know?
...and so on
State of the art
• Is there really any way that a computer can
create random numbers or is it always just
numbers that appear random to a human
being?
Nature of Thinking
Do machines really think or just follow orders?
• A machine that does AI has a set of rules and guidelines from which it
may not deviate. Do these rules make the machine nothing like the
brain, seeing as the brain has no rules or guidelines to work within, or
can these rules and guideline be equated to the capacity an individual's
brain has to learn and make sense of problems, ideas, objects, ect.?
Can machines learn to think?
• Are modern definitions of a computer "thinking by itself" still
dependent on continual human programming as the only means of
progress, or are there computers somewhere in the distant or even near
future that can actually be programmed to program themselves based
on input of users or even just experiences (the way that human beings
learn and are taught to think)?
Nature of thinking (cont)
• Can machine language and thought be
superior to human thought? If so, what does
this say for the future of society?
• If scientists can ever figure out the exact
code for the brain, would it be possible to
simulate it in a strong AI computer?
Learning
• Is it possible for a computer to learn? Can it adapt to
unfamiliar situations and "reprogram" itself?
• Because a machine cannot have experiences, how can a
machine learn from experiences and acquire the same type
of conditioning that humans acquire throughout their lives?
• Could a machine ever write a sonnet with the same
intensity and meaning as a human poet or truly enjoy the
taste of summer strawberries and cream?
• Can machines ever be programmed to experience
emotions?
Philosophical
• We now accept that a computer can beat a chess champion,
but we don't easily accept that a computer could experience
emotions in the same way that we do. Is this resistance a
general belief that human consciousness is so unique that it
could not be replicated by humans? Or is it another idea that
will be commonly accepted in a few more decades?
• If a computer can map out responses through a network of
possible answers and connecting ideas, would that make it
more human?
• See articles on Turing’s theories and their its
implications/rebuttals:
http://www.turing.org.uk/turing/scrapbook/test.html,
http://cogsci.ucsd.edu/~asaygin/tt/ttest.html
Computers vs. Humans
• If we create a machine that is a replica of a human brain,
using electrons in place of neurotransmitters, is that
machine a thinking machine? Even if it cannot think on its
own and needs to be able to read the brain activity of a
person in order to function. If it is able to follow human
neurotransmitter patterns is it thinking or merely copying?
• Is programming a "life history" into a computer possible?
• Is if possible for a computer to simulate creativity? Let’s
define creativity as the ability to figure out a solution
without the inputs necessary to draw that conclusion from
pure logic.
Science Fiction
• Do you think that it will be possible one day to store
information in the human's brain or to educate humans by
using computer programs? (Like in the movie “The
Matrix,” when the main character gets fighting techniques
and jump programs stored in his brain)
• How far are we from robots that look and move in ways
very similar to humans?
• Do you think that if in a point in time we develop
machines that could think and be human-like then they
would represent a danger for humans?