What Can and Can’t AI Do?

Can Computers Talk?
This is known as “speech synthesis ”translate text to phonetic forme.g., “fictitious ” -> fik-tish-e use pronunciation rules to map phonemes to actual sound

* e.g., “tish ” -> sequence of basic audio sounds

Difficulties

sounds made by this “lookup ” approach sound unnatural

sounds are not independent e.g., “act ” and “action ” modern systems (e.g., at AT&T) can handle this pretty well a harder problem is emphasis, emotion, etc humans understand what they are saying machines don ’t: so they sound unnatural

Conclusion:

  • NO, for complete sentences
  • YES, for individual words

Can Computers Recognize Speech?

Speech Recognition:

mapping sounds from a microphone into a list of words

classic problem in AI, very difficult “ Lets talk about how to wreck a nice beach”

* (I really said “________________________ ”)

Recognizing single words from a small vocabulary systems can do this with high accuracy (order of 99%)

* e.g., directory inquiries

limited vocabulary (area codes, city names)

computer tries to recognize you first, if unsuccessful hands you over to a human operator

* saves millions of dollars a year for the phone companies

* Recognizing normal speech is much more difficult

* speech is continuous: where are the boundaries between words?

* e.g., “John ’s car has a flat tire ”

* large vocabularies

* can be many thousands of possible words

* we can use context to help figure out what someone said

* e.g., hypothesize and test

*try telling a waiter in a restaurant:

“I would like some dream and sugar in my coffee”

* background noise, other speakers, accents, colds, etc

* on normal speech, modern systems are only about 60-70% accurate

* Conclusion:

* NO, normal speech is too complex to accurately recognize

* YES, for restricted problems (small vocabulary, single speaker)
Can Computers Understand speech?

* Understanding is different to recognition:

* “ Time flies like an arrow”

* assume the computer can recognize all the words

* how many different interpretations are there?

* 1. time passes quickly like an arrow?

* 2. command: time the flies the way an arrow times the flies

* 3. command: only time those flies which are like an arrow

* 4. “time-flies” are fond of arrows

* only 1. makes any sense,

* but how could a computer figure this out?

* clearly humans use a lot of implicit commonsense knowledge in communication

* Conclusion: NO, much of what we say is beyond the capabilities of a computer to understand at present
Can Computers Learn and Adapt?

* Learning and Adaptation

* consider a computer learning to drive on the freeway

* we could teach it lots of rules about what to do

* or we could let it drive and steer it back on course when it heads for the embankment

* systems like this are under development (e.g., Daimler Benz)

* e.g., RALPH at CMU

* in mid 90 ’s it drove 98% of the way from Pittsburgh to San Diego without any human assistance

* machine learning allows computers to learn to do things without explicit programming

* many successful applications:

* requires some “set-up” : does not mean your PC can learn to forecast the stock market or become a brain surgeon

Conclusion: YES, computers can learn and adapt, when presented with information in the appropriate way
Can Computers “see”?

* Recognition v. Understanding (like Speech)

* Recognition and Understanding of Objects in a scene

* look around this room

* you can effortlessly recognize objects

* human brain can map 2d visual image to 3d “map”

*

Why is visual recognition a hard problem?

* Conclusion:

* mostly NO: computers can only “see ” certain types of objects under limited circumstances

* YES for certain constrained problems (e.g., face recognition)
Can computers plan and make optimal decisions?

* Intelligence

* involves solving problems and making decisions and plans

* e.g., you want to take a holiday in Brazil

* you need to decide on dates, flights

* you need to get to the airport, etc

* involves a sequence of decisions, plans, and actions

* What makes planning hard?

* the world is not predictable:

* your flight is canceled or there ’s a backup on the 405

* there are a potentially huge number of details

* do you consider all flights? all dates?

* no: commonsense constrains your solutions

* AI systems are only successful in constrained planning problems

* Conclusion: NO, real-world planning and decision-making is still beyond the capabilities of modern computers

* exception: very well-defined, constrained problems

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