Download PHILOSOPHY 305F - Colorado State University Computer Science

PHILOSOPHY 305F
PHILOSOPHICAL ISSUES IN COMPUTER SCIENCE
SYLLABUS
FALL 1999
12:30-1:45 TR
PROF. JAMES PETERSON
OFFICE: 211 USC, PH 491-7137
EMAIL: [email protected]
TEXTS:

Haugeland, John; Artificial Intelligence: The Very Idea. (Hereafter referred to as
AI:TVI)

Boden, Margaret, ed.; The Philosophy of Artificial Intelligence. (Hereafter PAI)

Dreyfus, Hubert; What Computers Still Can't Do. (Hereafter CCD)

Johnson, Deborah; Computer Ethics. (Hereafter CE)

Seech, Z.; Writing Philosophical Papers
Hand-out readings will also be distributed occasionally in class.
(Reading assignments will ordinarily range from 50 to 100 pages per week.)
GENERAL COURSE DESCRIPTION:
This course covers major issues in what has come to be called Cognitive Science -the study of the conditions for the possibility of artificially producing "intelligent"
computers (or any intelligence whatsoever). In addition, social and ethical issues relating
to computer science will be separately considered.
COURSE REQUIREMENTS:
o
Grades will be assigned on the basis of class participation, including discussion,
homework, examinations and papers. Since some material will be presented only
in class, class attendance is essential.
o
There will be two examinations (a mid-term and a final), there will be two papers
due (3-6 pages each), several small homework assignments, including reading
questions. Completing the required reading assignments is essential to passing
this course.
Following is a tentative schedule of topics (weeks and topics are approximate):
BACKGROUND
24 August (first day):
Introduction, course requirements, grading practices, texts, course topics, purpose
of the course, etc. Overview of topics.
26 August:
What is Cognitive Science? What is “critical” philosophy? "Artificial" intelligence,
cognitive science: some major issues (in brief): Standards of "intelligence?" The
Cognitivist hypothesis: is thinking merely nomological "information" processing?
Are our minds really formal systems that can be duplicated digitally? How do
machine data representations "mean" things? How do we? The assumptions of AI.
Strong AI vs. Weak AI. Levels of description.
Readings: (PAI: Introduction)
Weeks 2 & 3:
The pitfalls of speaking metaphorically: the meanings of “information,” “code,”
“memory.” Examining our prejudices and beliefs. Philosophical/Historical
background of calculative rationality and the computational theory of mind, for
Pre-socratics, Plato, Aristotle, Hobbes, Descartes, Hume, and Kant.
Readings: (Dreyfus, CCD, Introduction (pp. 67-87); Introduction to the MIT Press
Edition (pp. ix-lii), AI:TVI, Intro & Ch 1; Seeth, Intro, Ch1, Ch2 (through pp.23).
Week 4:
General intro to: formal systems, types/tokens, game playing, deterministic
systems. Digital vs analog systems. Formal Equivalence, medium independence.
Automatic Formal systems. The paradox of thought and materialism.
Writing philosophical papers.
Readings: (AI:TVI, Ch. 2)
Meanings and interpretations of Formal Systems: Syntax vs. Semantics, where do
meanings come from? What are they, anyway? Internal vs external meanings.
Interpretations and truth. Assumptions of AI: intelligence can be wholly captured
by rule governed systems, such systems are media independent, etc. Classical AI
corollaries.
Readings: (AI:TVI, Ch 3).
Week 5:
The philosophical importance of Turing Machines, what Turing machines are,
equivalence notions, Universal Turing Machines. Computability, Church/Turing
thesis. How do we know the Church/Turing thesis applies to human beings
(pro/con)?
Readings: (AI:TVI, Ch 4)
Does computer architecture matter? Symbolic Computing, Von Neumann
Architecture; Neural Nets, Connectionist models.
Landmark Attempts at AI: Heuristic Search (Logic Theorist, General Problem
Solver, Chess programs), Turing tests and the "Doctor" programs (ELIZA), Microworlds (SHRDLU), Schank's "Frames."
Readings: (AI:TVI, Ch.'s 4 & 5).
Week 6:
Examining Strong AI assumptions: What are people really like?? Rule governed
action vs. holistic action; knowing how and knowing that (Can you know how and
not that?); learning and expertise; the intricate and unisolatable network of
human knowledge and meaning; finite provinces of meaning; common sense
(everyday life) as foundation ("paramount reality") of all meaning; self-awareness,
imagination, feelings, moods, strivings, purposes, will.
Readings: (Dreyfus; CCD, Introduction to the Revised Edition pp. 1-65)
THE CHALLENGE OF HUMAN CAPABILITIES
(WEEKS 7 - 12)
The Turing Test (PAI: Turing, "Computing Machinery and Intelligence"; Handout:
"Lessons from a Restricted Turing Test."). Searle's Criticism of AI (PAI: "Minds, Brains,
and Programs")
The Knowledge Representation Problem: Frames and Scripts. Readings: PAI: Dennett;
"Cognitive Wheels: The Frame Problem of AI")
Connectionism: A new paradigm for AI: Neural Nets, how they work; What they explain.
NN shortcomings: Fodor/Smolensky debate. Readings: (Copland, Jack; AI’s Fresh Start,
Parallel Distributed Processing (handout); Dreyfus and Dreyfus, "Making a Mind vs.
Modeling a Brain", Ch. 13 in PAI)
Motivation: An egological critique of GOFAI. The materialist's fallacy. How difficult is
AI really? The nature of human intelligence, and the unstated assumptions AI makes
about it. The role of cultural practices and skill acquisition in human understanding.
The non-additive and complex nature of human knowledge. The role and nature of
context, analogy, and typification in understanding. The relationship of relevance to
understanding. How motivation determines relevance. Readings: Handout: Jonas,
"Cybernetics and Purpose: A Critique"; CCD pp. pp. 155-305.
INFORMATION ETHICS
WEEKS 13-15
Philosophical Theories of Ethics: justifiability, generalizability. Inadequate theories:
egoism, naive ethical relativism, divine command theory. Viable candidates:
utilitarianism and deontology. Integrity and Virtue. A framework for analyzing concrete
cases.
Ethics and Computers:
Piracy: copying software: why is it wrong? The swimming pool analogy; loss of
autonomy. What sort of intellectual property is software? Legal protections:
trade secrets, copyrights, patents. The Lotus “look and feel” problem.
Privacy: The Dangerous Dossier -- The risks of anonymous data accumulation:
miscollection, misinterpretation, faulty distribution. Existing dangers: True Name
Theft. Denial of service, employment.
Misuse: What do hackers ethically do wrong? The no-harm, no foul fallacy. How
secure must a computer system be?
Professional Ethics: Risks and Liabilities – what are the ethical responsibilities of the
computer scientist? Who is responsible when something goes wrong? Diffuse
responsibility, following orders. Contractual responsibilities.
Social Implications of Information Technology: Computers as tools, as extensions of one’s
intellect. Dangers of dependence and social over-reliance on information technology.
Computation as a substitute for thought. The costs of technology - cultural and fiscal.
Computers as an agent of good or evil.
Readings: CE.
Course Requirements:
In addition to requisite reading and class attendance, this course requires two substantial
papers, a mid-term and a final, reading assignments and homework assignments, including
questions drawn from readings to be turned in from each reading assignment, to be weighted as
follows:
Paper I
Paper II
Mid-term
Reading Questions
Homework and discussion
Final
20%
25%
20%
5%
5%
25%
Papers will be 3-6 typed, double-spaced, pages in length on topics approved in advance. The first
paper will be due the end of the 6th week of class. Paper II will be due about the 12th week of
class. Papers will be graded on philosophical acumen, argumentation, coherence, English usage,
and style. Late papers will be severely penalized.