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Introduction to AI summary

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Elaborate summary of the introduction to AI course in the Pre-master data science and society. Includes the course materials as well as additions from the book and extra explanations about the calculations.

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  • July 10, 2022
  • 65
  • 2021/2022
  • Summary

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Introduction to Artificial Intelligence
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Discussion: reading and questions related to the reading. It is a group project. You have a
week to complete it. Then we will meet and discuss together.

Mid-term exam: examines the material that we discussed in the first half of the course.
(30%)

Final exam: will examine the first and the second half of the course. (70%).
You need to pass both.
It will be an open book exam.

You need to submit your assignments. Your assessment is whether you contributed.

Exam is open book exam: you can only bring paper-based material to the exam. You can
bring notes, slides, book, or print out relevant parts of relevant chapters.


Lecture 1

AI experts warn the United Nations of a third revolution in warfare. Fully autonomous
weapons that engage targets without human intervention. “Once developed, they will
permit armed conflict to be fought at a scale greater than ever, and at timescales faster
than humans can comprehend”.

How safe can AI be?
On the one hand:
- Stephen Hawking says: “AI could spell the end of the human race”.
- Elon Musk says it’s “like summoning the demon”.
On the other hand:
- Brett Kennedy (JPL) says: “I have first-hand knowledge of how hard it is for us to
make a robot that does much of anything”.
- Alan Winflied (U. of Britol) says: “fear of future super intelligence – robots taking
over the world – are greatly exaggerated”.

Be very, very skeptical:
- “AI’s record of barefaced public deception is unparalleled in the annals of academic
study” – Theodore Roszak.
- AI researchers have been making bold claims since the late 1950s.
- Repeatedly, AI’s progress has been much slower than expected.
- It’s easy to imagine full AI, hence easy to convince/scare people.

Artificial intelligence is:
- “The science and engineering of making intelligent machines” – John McCarthy
- “The science of making machines do things that would require intelligence if done by
men” – Marvin Minsky (1968)

, - “The exciting new effort to make computers think… machines with minds, in the full
and literal sense” – John Haugeland (1985)
- “The art creating machines that perform functions require intelligence when
performed by people” – Ray Kruzweil (1990)

What do we mean by artificial?
If machine intelligence is artificial, what is “real” intelligence?
- Must “real” intelligence be made of biological stuff?
o This is known as carbon/protoplasm chauvinism.
o What if we work out how to engineer biological agents?
- Must “real” intelligence be the product of biological evolution?
o Should nature be the only source of “real” intelligence?
o What if we work out how to evolve biological agents?
So, we seem to mean two things when we use the term artificial:
- By artificial, we mean non-biological. Here, it’s all about the kind of stuff we use to
build an agent.
- By artificial, we might mean constructed by humans. Here, it’s all about the origin of
the agent, and who designed and built it.

Intelligence: intelligence is the computational part of the ability to achieve goals in the
world. Varying kinds and degrees of intelligence occur in people, many animals, and some
machines (this quote will be used for this course when talking about intelligence). – John
McCarty. In the book, we adopt the view that intelligence is concerned mainly with rational
action. Ideally, an intelligent agent takes the best possible action in a situation.

Nigel questions:
1. Can Nigel think?
2. Can Nigel learn? No, he does not learn from successes.
3. Is Nigel more intelligent than us? He is maybe better in a very specific topic, but he is
not necessarily more intelligent. He was built by an engineer, so how can he possibly
be more intelligent than that? → think carefully about it because sometimes
machines can do more than what they were designed to do.
4. Is Nigel creative? He sticks to the same plan each time, so he is not creative.
5. Does Nigel have emotions?
6. Is Nigel conscious? He is aware of his surroundings and environment therefore he
must be conscious. He is not conscious in the same way a human is, but he is
conscious in some sense. He has preferences for some things (for example not to
bump into too many walls) therefore he must be conscious at some level. We never
know if they are conscious or not unless they tell us.
These are examples of answers given in class.

The Dartmouth Summer Research Project on Artificial Intelligence (1956): The proposal of
the founding fathers of AI can be seen as the first AI hypothesis: that is what they meant
when they were talking about AI: “every aspect of learning or any other feature of
intelligence can in principle be so precisely defined that a machine can be made to simulate
it”.

,Some comments:
- Simulate: so, it’s not real then?
- Or any other feature of intelligence: what is meant by that?

Artificial Intelligence has grown into a field of study with many goals




Is AI a science or an engineering? Its both.

, One of the major goals is to design machines that can solve problems in general.

The contrast between the rational and the psychological: should AI be guided by the
psychological (our understanding of how humans work) or the rational (our understanding
of logic, probability theory etc.). Four ways of using AI.




Acting humanly: the turning test approach: was designed to provide a satisfactory
operational definition of intelligence. A computer passes the test if a human interrogator,
after posing some written questions, cannot tell whether the written responses come from
a person or from a computer. The computer would need to possess the following
capabilities:
- Natural language processing to enable it to communicate successfully in English;
- Knowledge representation to store what it knows or hears;
- Automated reasoning to use the stored information to answer questions and to
draw new conclusions;
- Machine learning to adapt to new circumstances and to detect and extrapolate
patterns.
Turning’s test avoided direct physical interaction between the interrogator and the
computer because physical simulation of a person is unnecessary for intelligence. However,
the total turning test includes a video signal so that the interrogator can test the subject’s
perceptual abilities, as well as the opportunity for the interrogator to pass the physical
objects. Top pass the total Turning Test, the computer will need:
- Computer vision to perceive objects, and
- Robotics to manipulate objects and move about.

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