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: peterson@cs.colostate.edu
Texts:
Hand-out
readings will also be distributed occasionally in class.
(
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:
·
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.
·
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.
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.
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.
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.
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)?
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), Micro-worlds (SHRDLU), Schank's
"Frames."
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.
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.
Connectionism: A new paradigm for AI: Neural Nets, how
they work; What they explain. NN shortcomings: Fodor/Smolensky debate.
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.
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.
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 20%
Paper II 25%
Mid-term 20%
Homework and discussion 5%
Final 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.