Renmin University Philosophy Short Course
日期：2016-04-14
Computers, Artificial Intelligence, and Philosophy of Mind
Renmin University, Beijing, April 2016
Jack Copeland, FRS NZ, Distinguished Professor in Arts,
University of Canterbury, New Zealand
Overview
This course is an introduction to philosophical issues concerning computers and computing.
The course focuses especially on the work of Alan Turing and his revolutionary ideas and legacy. As a graduate student, Turing invented the fundamental logical principles of the modern computer; and while breaking the German Enigma code during World War II, he experimented with what is now called `heuristic search` and designed the electro-mechanical Bombe—an early computer and the first step on the road to modern Artificial Intelligence (AI).
Topics include: the Turing Test for computer thought; the `Chinese Room` argument against the possibility of strong AI; connectionist AI; the Church-Turing thesis; computational and hypercomputational models of mind; and the possibility of future computers having free will. An introductory section outlines the history of AI.
Time and place
Five 150-minute lectures, from 2-4:30 p.m. on April 18, 20, 22, 25, 27, at 600 Renwen Building.
Reading
Jack Copeland. Artificial Intelligence: A Philosophical Introduction. Wiley-Blackwell. (Kindle Edition 2015.)
Jack Copeland. The Essential Turing. Oxford University Press.
General reference works
Luciano Floridi. Guide to the Philosophy of Computing and Information. Blackwell.
Margolis, E., Samuels, R., Stich S. P. (eds). Oxford Handbook of Philosophy of Cognitive Science. Oxford University Press.
Preliminary reading
?Jack Copeland. Turing, Pioneer of the Information Age. Oxford University Press.?(A biography of Alan Turing, and exposition of his work in codebreaking, computing, Artificial Intelligence, and Artificial Life.)
Learning outcomes
This course aims to enable students to:
- Exhibit a general understanding of the philosophy and history of Artificial Intelligence.?
- Communicate clearly about topics in this field.
- Explain and analyse specific philosophical issues concerning computer science.
- Think independently about central problems in the philosophy of AI and at a level requiring in-depth knowledge and critical understanding.
Lectures
Lecture 1: Artificial Intelligence versus the Human Brain
An introduction to AI. What is AI and what are its goals? AI’s achievements. The `AI winter` and recent renaissance. Need an artificial intelligence be conscious? Origins: the early history of AI.
Reading
Copeland, Artificial Intelligence, chs 1-3.
The Essential Turing, `Artificial Intelligence`.
Lecture 2: The Imitation Game
Alan Turing’s famous test for computer intelligence: the nature and origins of the test. Turing’s predictions about the test. Has the test been passed? Defending the test against conceptual objections, including the `Blockhead Objection`, the `Rating Games Objection` and the `Chinese Room Objection`.
Reading
Copeland, Artificial Intelligence, chs 3, 6.
The Essential Turing, ch. 11 (Turing`s `Computing Machinery and Intelligence`).
Lecture 3: Connectionism: Computing with Neurons
Is the human brain a computer? The nature and origins of connectionism. Is the brain a connectionist network? John Searle’s conceptual arguments that the brain is not a connectionist network.
Reading
Copeland, Artificial Intelligence, chs 9, 10.
The Essential Turing, ch. 10 (Turing`s `Intelligent Machinery`).
Lecture 4: Can Computers have Freewill?
Freedom of the will appears to be a central human characteristic. Computers, though, are deterministic devices. Someone who knows the program and the input can predict the computer’s behavior in advance. What scope, then, for an artificial intelligence to exhibit free will?
Reading
Copeland, Artificial Intelligence, ch. 7.
The Essential Turing, ch. 13 (Turing`s `Can Digital Computers Think?`).
Lecture 5: Computability, The Church-Turing thesis, and Hypercomputation
The Church-Turing thesis states that every algorithm can be carried out by a Turing machine (Turing’s abstract computing device, now a foundational concept in computer science). This thesis is often taken to imply that the human brain must be a form of computer (and so AI must be possible); and moreover that any information-processing machine must be equivalent to a Turing machine. Hypercomputation, on the other hand, explores the possibility of information-processors that are more powerful than Turing machines.
Reading
Copeland, `Hypercomputation: Philosophical Issues`, Theoretical Computer Science, vol. 317 (2004), 251-267.
The Essential Turing, ch. 1 (Turing`s `On Computable Numbers`) and `Computable Numbers: A Guide`.
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