The Possibility of Artificial Intelligence, SPRING 2007

Phil 355 / Psy 355: T/Th 10:30 – 11:50

Professor William Seeley, 323 Stager Hall

Office Hours: T/Th 12:00 – 1:00 & by appointment

william.seeley@fandm.edu

Course Description:

What are minds? Are minds like computers? If so, how much is a computer like a mind? Is it possible for a machine or a computer to think? If it were possible, what would these thoughts be like? Would they be just like ours? Could machines feel emotions or make genuinely moral choices? Do these questions have any bearing on the possibility of artificial intelligence? Underlying all these issues is a central question concerning the nature of thinking itself. Before we can know what sorts of things can be thinkers we must first come to an agreement on what it is to be a thinker at all.

It was once thought that thinking, the ability to form rational thoughts, was what set human beings from the rest of the universe. Today cognitive scientists look to commonalities between minds and computers to help them understand complex cognitive tasks like visual perception, rationality, and language development. In this course we will examine and evaluate some contemporary concepts and issues in philosophy, psychology , and computer science that are critical to both research in artificial intelligence and the computational theory of mind. The topics covered in this course will include: intentionality, representation, consciousness, the computational theory of mind, artificial life, and alternatives to the traditional (GOFAI) model for AI.

Course Goals:

The goals of this course are threefold. We will try to come to an understanding of what artificial intelligence is, and more importantly what it is not, as a research program in psychology and computer science. In this context we will evaluate the validity of several philosophical problems associated with artificial intelligence. This debate will be used to evaluate the traditional GOFAI model and introduce contemporary alternatives.

Texts:

Mindware, Andy Clark (New York: Oxford, 2001).

Mind Design II, ed. John Haugeland (Cambridge, MA: MIT Press, 1997).

What Computers Still Can’t Do, Hubert Dreyfus (Cambridge, MA: MIT Press, 1993).

Flesh and Machines, Rodney Brooks (New York: Vintage Books, 2002)

Electronic resources and pdf files on eDisk

Requirements:

one 4 page paper due February 15.

one 6 page paper on an assigned topic due at the midterm. Students will be given a choice between two topics that require them to synthesize the material from the first half of the semester.

XOR Exercise: a set of exercises designed by Kim Plunkett & jeffery Elman to teach students about connectionist systems.

one 8 - 10 page final paper on a topic of your choosing (50%). All students must clear final paper topics with me before April 1^st. The final paper is due at the first day of exams.

Late papers will NOT be accepted!

Schedule of Readings:

Topic 1 : Introduction: What is AI?

Brooks: “We Are Special/We Are Not Special”

Clark: Chapter 1, “Meat Machines: Mindware as Software”

Haugeland: “What Is Mind Design?” 1-28

Dennett: “Artificial Intelligence as Philosophy and Psychology”

Copeland: Chapter 2, "Some Dazzling Exhibits"

Intelligent By Design: http://www.pbs.org/saf/1303/features/AI.htm

Kismet: http://www.ai.mit.edu/projects/sociable/ongoing-research.html

Play with ELIZA: http://www.manifestation.com/neurotoys/eliza.php3

Topic 2: Minds, Patterns, and Representations

Copeland: Chapter 4, "The Symbol System Hypothesis"

Clark: Chapter 3, “Patterns, Contents, & Causes”

Dennett: "True Believers: The Intentional Strategy and Why It Works"

Turing: “Computing Machinery & Intelligence”

Newell & Simon: “Computer Science as Empirical Enquiry: Symbols & Search”

Searle: “Minds, Brains, & Programs”

Copeland: “The Chinese Room from a Logical Point of View”

Short paper (1000) words:

a: Why can't/can the Chinese room understand Chinese?

b: Should neural prosthetics change Searle’s mind?

Topic 3: The Frame Problem:

Minsky: “A Framework for Representing Knowledge”

Dennett: "Cognitive Wheels: The Frame Problem of AI"

Dreyfus: “Phase I: Cognitive Simulation”

Topic 4: AI at an Impasse?

Dreyfus: “Assumptions Underlying Persistent Optimism”

Topic 6: Connectionism?

Clark: Chapter 4, "Connectionism"

Rumelhart: ”The Architecture of Mind: A Connectionist Approach”

Churchland: “On the Nature of Theories: A Neurocomputational Perspective”

Rosenberg: “Connectionism & Cognition”

Fodor & Pylyshyn: "Connectionism and Cognitive Architecture: A Critical Analysis"

Paul Smolensky: "Connectionism and the Language of Thought”

Plunkett & Elman: “The Methodology of Simulations”

Connectionist Modeling:

Plunkett & Elman (XOR exercise in AI lab)

“Learning to use the simulator” (Chapter 3)
“Learning internal representations” (Chapter 4)

Topic 7: Challenges to the Traditional Model

Heideggarian AI:

Dreyfus: “Alternatives to the Traditional Assumptions”

Preston: “Heidegger and Artificial Intelligence”

Robotics & A-Life:

Clark: Chapter 6: “Robotics & Artificial Life”

Brooks: “Intelligence without Representation”

Smith: “The Owl and the Electric Encyclopedia. Artificial Intelligence”

Kirsch: “Today the Earwig, Tomorrow Man?”

Dynamics:

Clark: Chapter 7: “Dynamics”

van Gelder: “Dynamics & Cognition”

Markman & Dietrich: “In Defense of Representation”

Affective Computing:

Picard: “Affective Computing: Challenges”

Ball & Breese: “Emotion and Personality in a Conversational Agent”

Some Miscellaneous Notes and Guidelines:

Moral behavior is the grounds for, and the framework of, a healthy society. In this regard it is each of our responsibility as an individual within the community of our classroom to act responsibly. This includes following the rules and guidelines set out by the College for academic behavior. Plagiarism is a serious matter. It goes without saying that each of you is expected to do his or her own work and to cite EVERY text that is used to prepare a paper for this class. As a general rule, I ask that you not use the internet for your research except as assigned in class.

The reading list for this class is arranged in topics as opposed to individual sessions. I will announce the particular readings for each class as we go along. This will allow us some flexibility in discussion so that we can spend more time on issues of interest to the class. I reserve the right to make changes to the syllabus as we go along in order to accommodate class interests. I will also occasionally upload supplementary materials to eDisk for students interested in pursuing particular issues beyond class discussion.

Bibliography:

Topic 1: Introduction: What is AI?

Rodney Brooks, “We Are Special/We Are Not Special,” Flesh and Machines: How Robots Will Change Us (New York: Vantage), 2002, 148-196.

Andy Clark, “Chapter 1: Meat Machines: Mindware as Software,” Mindware (New York: Oxford, 2001), 7-27.

John Haugeland, “What Is Mind Design?” in ed. John Haugeland, Mind Design II (Cambridge, MA: MIT Press, 1997), 1-28.

Daniel Dennett, “Artificial Intelligence as Philosophy and Psychology,” Brainstorms (Cambridge, MA: MIT Press, 1993), 109-128.

Jack Copeland, “Chapter 2: Some Dazzling Exhibits," Artificial Intelligence (Malden, MA: Blackwell Publishers, 1993), 11-32.

Topic 2: Minds, Patterns, and Representations

Andy Clark, “Chapter 2: Symbol Systems,” Mindware (New York: Oxford, 2001), 28-42.

Andy Clark, “Chapter 3: Patterns, Contents, & Causes,” Mindware (New York: Oxford, 2001), 43-61.

Daniel Dennett, "True Believers: The Intentional Strategy and Why It Works," in ed. John Haugeland (Cambridge, MA: MIT Press, 1997), 57-80.

Alan Turing, “Computing Machinery & Intelligence,” in ed. John Haugeland, Mind Design II (Cambridge, MA: MIT Press, 1997), 29-56.

Allen Newell & Herbert A. Simon, “Computer Science as Empirical Enquiry: Symbols & Search,” in ed. John Haugeland, Mind Design II, (Cambridge, MA: MIT Press, 1997), 81-110.

John Searle, “Minds, Brains, & Programs,” in ed. John Haugeland, Mind Design II (Cambridge, MA: MIT Press, 1997), 183-204.

Jack Copeland, “The Chinese Room from a Logical Point of View,” in eds. John Preston & Mark Bishop, Views into the Chinese Room (New York: Oxford University Press, 2002), 109-122.

Topic 3: The Frame Problem:

Marvin Minsky, “A Framework for Representing Knowledge,” in ed. John Haugeland, Mind Design II (Cambridge, MA: MIT Press, 1997), 111-142.

Hubert Dreyfus, “Phase I: Cognitive Simulation,” What Computers Still Can’t Do (Cambridge, MA: MIT Press, 1993), 1-66.

Topic 4: AI at an Impasse?

Hubert Dreyfus, “Assumptions Underlying Persistent Optimism,” What Computers Still Can’t Do (Cambridge, MA: MIT Press, 1993), 155-227.

Topic 6: Connectionism?

Andy Clark, “Chapter 4: Connectionism," Mindware (Cambridge, MA: MIT Press, 2001), 62-83.

David Rumelhart, ”The Architecture of Mind: A Connectionist Approach,” in ed. John Haugeland, Mind Design II (Cambridge, MA: MIT Press, 1997), 205-232.

Paul Churchland, “On the Nature of Theories: A Neurocomputational Perspective,” in ed. John Haugeland, Mind Design II (Cambridge, MA: MIT Press, 1997), 251-292.

Jay Rosenberg, “Connectionism & Cognition,” in ed. John Haugeland, Mind Design II (Cambridge, MA: MIT Press, 1997), 293-308.

Jerry Fodor & Zenon Pylyshyn, "Connectionism and Cognitive Architecture: A Critical Analysis," in ed. John Haugeland, Mind Design II (Cambridge, MA: MIT Press, 1997), 309-350.

Paul Smolensky, "Connectionism and the Language of Thought," in eds. Macdonald and Macdonald, Connectionism (Malden, MA: Blackwell, Publishers, 1995), 164-198

Plunkett & Elman, “The Methodology of Simulations,” Exercises in Rethinking Innateness (Cambridge, MA: MIT Press, 1997), 1-30.

Simulation Project:

Plunkett & Elman, “Learning to use the simulator” (Chapter 3), Exercises in Rethinking Innateness (Cambridge, MA: MIT Press, 1997), 31-74.

Plunkett & Elman , “Learning internal representations” (Chapter 4), Exercises in Rethinking Innateness (Cambridge, MA: MIT Press, 1997), 75-98.

Topic 7: Challenges to the Traditional Model

Hubert Dreyfus, “Alternatives to the Traditional Assumptions,” What Computers Still Can’t Do (Cambridge, MA: MIT Press, 1993), 231-282.

Beth Preston, “Heidegger and Artificial Intelligence,” Philosophy and Phenomenological Research,53(1), 1993, 43-69.

Andy Clark, “Chapter 6: Robotics & Artificial Life,” Mindware (Cambridge, MA: MIT Press, 2001), 103-119.

Rodney Brooks, “Intelligence without Representation,” in ed. John Haugeland, Mind Design II (Cambridge, MA: MIT Press, 1997),395-420.

Brian Smith, “The Owl and the Electric Encyclopedia,” Artificial Intelligence, 47, 1991, 251-288.

David Kirsch, “Today the Earwig, Tomorrow Man?” Artificial Intelligence, 47, 1991, 161-184.

Andy Clark, “Chapter 7: “Dynamics,” Mindware (Cambridge, MA: MIT Press, 2001),120-139.

Timothy van Gelder, “Dynamics & Cognition,” Mind Design II (Cambridge, MA: MIT Press, 1997), 421-450.

Arthur Markman & Eric Dietrich, “In Defense of Representation,” cognitive Psychology, 40, 2000, 138-171.

Rosalind Picard, “Affective Computing: The Challenges,” The AI Magazine, Fall 1982, 1-9.

Rosalind Picard, “Envisioning Affective Computing,” Affective Computing (Cambridge, MA: MIT Press, 1997), 19-137.

Rosalind Picard, “Building Affective Computing,” Affective Computing (Cambridge, MA: MIT Press, 1997), 139-246.

Gene Ball and Jack Breese, “Emotion and Personality in a Conversational Agent,” in eds. Justine Cassell, Joseph

Sullivan, Scott Prevost, & Elizabeth Churchill, Embodied Conversational Agents (Cambridge, MA: MIT Press, 2000), 198-219.