1. Why are computers so stupid and what can be done about it?
Artificial intelligence
and commonsense knowledge

2. Two well-known truths about computers
Computers are great and amazing and a lot of fun to deal with. Computers are stupid and frustrating and it can be a huge amount of work to get what you want out of them.

3. Computers can play chess better than the greatest chess masters.
But
They’re no use for answering a question like “Give me an example where White can take Black’s queen, but if he does, Black can immediately checkmate.”

4. Computers can compute the interaction of two galaxies colliding.
But
They’re no use for answering a question like, “Can you ever get a solar eclipse one day and a lunar eclipse the next day?”.
If you ask “Draw me a picture of the Solar System as viewed from Betelgeuse,” you probably have a good bit of work to do.

5. An immense amount of information about movies is available at imdb
An immense amount of information about movies is available at imdb.com, Wikipedia, etc.
But
If you say “Get me a film still showing a girl with a dog from one movie from every decade since 1920,” you have to do a lot of this yourself.

6. General rule
You can easily do something on a computer if someone has anticipated that you will want to do exactly that, written a program for it, and you can find the program.
Otherwise, you have work to do.

7. A different kind of computer stupidity
(Boring example, but that’s the point.) NYU “upgraded” its software for student registration. This has caused endless problems. We want to have a rule that a student can register for at most 4 classes. Answers: Can’t be done/Will cost a lot of money. Incompetent software engineering.

8. Artificial Intelligence
“Then somehow it achieved self-awareness, and in a few nanoseconds had enslaved the human race.”
Many tasks that are very easy for people are extremely difficult for computers:
Vision
Natural Language
Operating in a rich environment (kitchen).

9. Commonsense Knowledge and Natural Language
Lexical disambiguation:
“This gift is for Stuart.”
“This gift is for Christmas.”
“This bowl is for soup.”

10. Reference disambiguation: Winograd schemas
“Jane knocked on Susan’s door, but she didn’t answer.” “Jane knocked on Susan’s door, but she didn’t get an answer” “The trophy doesn’t fit in the suitcase, because it’s too small.” “The trophy doesn’t fit in the suitcase, because it’s too large.”

11. Ambiguity is ubiquitous
“If you are a fan of the justices who fought through the Rehnquist years to pull the Supreme Court to the right, then Alito is a home run --- a strong and consistent conservative with the skill to craft opinions that make radical results appear inevitable and the ability to build trusting professional relationships across ideological lines.”
Andrew Siegel, The New Republic, 11/14/05

12. Ambiguity is ubiquitous
“If you are a fan of the justices who fought through the Rehnquist years to pull the Supreme Court to the right, then Alito is a home run --- a strong and consistent conservative with the skill to craft opinions that make radical results appear inevitable and the ability to build trusting professional relationships across ideological lines.”

13. Concert / party. Warmish spring afternoon
Concert / party. Warmish spring afternoon. Street in suburban neighborhood. Wooded hill behind. Canvas awning above, mended with duct tape. Large mug front center. People in back.

14. Messy kitchen
Bottle is empty
Fridge in corner
Toaster oven, paper
towel on counter.
Plant is hung from curtain rod.
Daytime

17. Two approaches to artificial intelligence
Corpus-based machine learning
Knowledge-based techniques

18. Corpus-based machine learning
You have:
Large body of data (text, pictures, etc.)
A task
Find many patterns of superficial features that are relevant to the task.
Determine how to combine them to carry out the task.
Critical: These are done without any real understanding of the task or content.

19. Notable successes Speech transcribing Google translate
Autonomous vehicle
Automatic check reading

20. Watson, the Jeopardy champion
The key insight in Watson is that you can win Jeopardy just by matching texts found on the web, with essentially no understanding of the question or answer. You can see this in Watson’s mistakes:

21. Commonsense Knowledge
The knowledge about the world that everyone has by age 7.
Learned by living in the world, not book-learning
Time, Space, Physical objects, People, Animals and Plants …
“If an open bottle full of liquid is turned upside down, the contents will pour out.”
“Hitting someone will not make them like you.”
“An animal is the same species as its parents.”
So obvious that it’s not worth talking about.

22. The research program
Determine the knowledge needed for reasoning in a domain.
Develop a notation that is clearly defined and that can express that knowledge.
Encode all the domain knowledge.
Find ways to automate reasoning with this knowledge.
Integrate the knowledge with the task.

23. “The trophy doesn’t fit in the suitcase because it’s too large”
“The trophy doesn’t fit in the suitcase because it’s too large”. Interpretation of “trophy is too large”: The trophy does not fit in the suitcase, and any larger trophy will also not fit, but some smaller trophy would fit. Interpretation of “suitcase is too large”: The trophy does not fit in the suitcase and would not fit in any larger suitcase, but would fit in some smaller suitcase.

24. Fact
If an object fits in a container, it fits in any larger container. So we can rule out the second reading. In logical notation: ∀o,c1,c2 FitsIn(o,c1) ⋀ Larger(c1,c2) ⇒ FitsIn(o,c2) Commonsense spatial reasoning

25. How far have we gotten?
A lot is known about representing: Ontology, general reasoning methods, time,
A fair amount is known about: Space, knowledge and belief, interactions between people, plans and goals.
A little is known about: physical reasoning.
Not much is known about other categories.

26. Successes
Debugging. This kind of deep understanding and reasoning has been used to find quite subtle bugs in very complex programs (operating systems, aircraft control, etc.) and hardware design.
Theorem proving: A couple of original mathematical theorems have been proven.
Other: None, really.

27. Why not?
Commonsense reasoning is a small, complex part of any AI task.
Little payoff until there is a lot of commonsense knowledge.
Software development starts with simple useful systems, and adds features. It is unwelcoming to systems that need to be very complex from the start.
Shortcuts lead to chaos.

28. How to proceed Look in depth at a variety of different domains.
Get good solutions to basic issues
Do not rely on natural language text.
Patience. This is a large, difficult project, which may take centuries.