PSY 322/ORF 322 Human-Machine Interaction
Spring Term 2002-03
Lectures 1:30 p.m. to 3:00 p.m.
Occasional Laboratories (to be scheduled)
Instructors

Professors: A. L. Kornhauser (ORF) E-407 EQuad, x8-4657, alaink@princeton.edu

J. J. Gelfand (PSY) jjg@princeton.edu

J. Cooper (PSY) jcoops@princeton.edu

G. Harman (PHI) 118 1879 Hall, x8-4301, harman@princeton.edu

R. G. Jahn (MAE) rgjahn@princeton.edu

P. N. Johnson-Laird (PSY) phil@princeton.edu
Description and Objectives
This course studies the fundamentals of human-machine interactions from both the human
psychology and philosophy side as well as the machine engineering and design side. This multidisciplinary approach will utilize faculty and readings from psychology, philosophy, physical
sciences and engineering. Starting from a framework of the elements of human-machine
interactions, the course focuses on the following specific issues:

What are the fundamental differences between humans and machines, specifically: how can
we use machines to study people, what are the functional elements of sensors, memory,
control and actuators in humans? Views of the brain at work.

Philosophical aspects of human-machine interactions. Turing's test for machine intelligence
and possible problems with the test. Searle's Chinese Room Argument.

Thinking by machines and humans. Deduction by machines and humans; a taxonomy of
thought. Are humans rational? Induction by machines and humans. Creativity by machines
and humans.

Computers in the social environment; motivational issues. Individual differences in humanmachine interactions. Issues of gender, age and personality.

The decisions and control by humans and machines. The structure of the human and
machine vision systems including approaches to machine vision and image processing.
Information content in images. Application of computer vision to drive an "auto" mobile,
artificial neural networks for massively parallel computing. Concepts of Decision
Engineering, helping individuals make better real-time decisions.

The role of consciousness in human-machine interactions: Are the information processing in
the human mind and that in the intelligent machines invariably linearly separable, or are
there possibilities of resonant synergism? Design and implementation of experiments on the
question, including: issues of statistical analysis, scale of effects, replicability, and
protection from artifacts. Theoretical models of the anomalous interactions, and their
implications and applications.
Course Requirements

Readings must be done before class; written assignments are due every other week.

There will be two (2) 1 hour exams.

There will be a term project and an oral presentation of the project.

Each student is expected to participate in at least one laboratory session in the PEAR lab, to
be scheduled midway through the course. Reading preparation for this session will be
indicated, and a written laboratory report will be required. For those especially interested in
this research, the laboratory is available for more detailed projects for the term papers.

In addition, students taking this course as their first or second psychology course must do
four hours of participation in approved psychology department experiments.

Grading: A-F, no pass-fail. Grade based on exams (20% each), course project and oral
presentation (25%), homework and labs (15%) and class participation (20%).
Required Texts
1. Collection of Readings from Psy/Orf 322. (Copies to be available for $20. Please make
check payable to Princeton University.)
2. Jahn & Dunne, Margins of Reality, Harcourt-Brace, 1987. (Copies available from
Micawber's Bookstore on Nassau Street, next to Foot Locker. Please buy at beginning of the
semester, otherwise the Store sends them back to the publisher.)
3. Two Decades of PEAR: An Anthology of Selected Publications (Copies to be available for
$15. Please make check payable to Princeton University.)
Class Schedule
Overview and Course Organization
Week 1
Mon 2/3 Broad Overview of the Course by Course Participants. Presentation of the framework of
human-machine interaction in a problem solving environment.
Segment 1: Engineering Description of the Mind - Professor A.L. Kornhauser
Wed 2/5 Models of Human Information Processing -- A. Kornhauser Skill-rule-and- knowledgebase approaches, semiotic interpretation of human acts, mental models of aggregation, abstraction
and analogy.
Readings: Card, Moran & Newell, The Psychology of Human-Computer Interactions, 1983, Ch1,2.
Segment 2: The Mind-Body Problem -- Professor G.H. Harman
Week 2
Mon 2/10. The Mind-Body Problem. Descartes' argument for two distinct substances, body and
mind. Various forms of dualism---substance, events, properties, phenomena. Possible relations
between two distinct realms: dualistic interaction, epiphenomenalism. Rejections of dualism:
idealism, physicalism.
Readings: Rene Descartes, Meditations on First Philosophy (II and VI) and excerpt from Passions
of the Soul.
Wed 2/12. Problems for physicalism. Does everything reduce to or arise from physical phenomena?
Or is there some non-physical principle? Compare the relation between mechanical and electomagnetic phenomena. Reasons to think that the mental does not reduce to the physical: intelligence,
free will, creativity, quality of experience, morality, religion.
Readings: Kwame Anthony Appiah, "Mind," chapter 1 of Thinking It Through, 2003.
Segment 3: Human and Machine Thinking -- Professor P. N. Johnson-Laird
Week 3
Mon 2/17. Deductions by Machines - P. N. Johnson-Laird. How do we get machines to think? One
answer: get them to think logically. Formal logic can be implemented in various computer
programs, e.g., systems based on "natural deduction", or the resolution rule. Another answer: get
machines to use rules with specific contents. Expert systems. The problems with these approaches:
intractability, lack of decision procedures, need to make inferences that undo previous conclusions.
Readings: Sections 6.2 to 6.4 of Ch 6. Agents that Reason Logically, in S. J. Russell and P. Norvig,
Artificial Intelligence: A Modern Approach. Englewood Cliffs, NJ: Prentice-Hall, 1995, pp. 153174.
Wed 2/19. Deductions by Humans - P. Johnson-Laird. Are human beings rational? Do they make
deductions in the same way as machines, i.e., by deriving conclusions using rules of inference?
Demonstrations of typical patterns of performance in deductive reasoning, including illusory
inferences that everyone gets wrong. How human reasoning is semantic rather than a syntactic
process; it appears to depend on constructing mental models of situations.
Readings: Johnson-Laird, P.N. (2002) "Logic and reasoning." In Ramachandran, V.S. (Ed.)
Encyclopedia of the Human Brain. San Diego, CA: Academic Press. Vol 2, pp. 703-716.
Week 4
Mon 2/24. Probabilistic Thinking by Humans and Machines - P. Johnson-Laird. Representing
uncertainty: the advantages of the probabilistic calculus. Extensional vs. nonextensional reason
about probabilities. Common errors in human reasoning about probabilities. Bayes' theorem in
expert systems and in human thinking. A theory of na•ve probabilistic reasoning. Belief networks in
artificial intelligence.
Readings: Gigerenzer and Hoffrage (1995) "How to Improve Bayesian Reasoning Without
Instruction: Frequency Formats," Psychological Review, 102, 684-704.
Wed 2/26. Creativity in Humans and Machines - P. Johnson-Laird. Can machines be creative? A
working definition of creativity. A taxonomy of creative processes: Three computational
architectures. Non-determinism. Some algorithms for creativity in science and art.
Readings: Ch.'s 13-15, and Appendices 1 and 2 of P. McCorduck, Aaron's Code: Meta-Art,
Artificial Intelligence, and the work of Harold Cohen. New York: Freeman,1991. Pp. 85-110; 199208
Segment 4: Can the Mind be Studied Objectively? -- Professor G.H. Harman
Week 5
Mon 3/3. Arguments for physicalism. Avoiding crazy physics. Evolution leads to animals and
people. Using physical principles to explain teleology. The evolution of inner representation.
Behaviorism and functionalism.
Readings: Daniel C. Dennett, Chapters 1-2, Darwin's Dangerous Idea. Armstrong, "The Causal
Theory of Mind."
Wed 3/5. Objective and subjective accounts of mental life. Can functionalism explain what it is like
to have an experience? Interpretation and translation versus explanation in terms of laws and
regularities. Differences between physical and cognitive sciences.
Readings: Nagel, "What Is It Like to Be a Bat?"
Segment 5: Perception -- Professor J. Gelfand
Week 6
Mon 3/10. Perception and Thinking by Humans and Machines - J.J. Gelfand
Readings: S. Epstein, J. Gelfand and E. Twersky-Lock, "Learning Game-Specific SpatiallyOriented Heuristics", Constraints, 3, (1998), pp. 239-253.
Midterm Examination
Wed 3/12. MID-TERM HOURLY EXAM (covers everything through Monday 3/11, Segments 13)
Mid Term Break
Segment 6: Individual Differences in Human Machine Interactions -- Professor J. Cooper
Week 7
Mon 3/24. Computers in the Social Environment - J. Cooper. Principles of social interaction, e.g.,
social comparison, social influence. The computer as a participant in the social system.
Readings: Lepper & Malone, "Making Learning Fun: A Taxonomy of Intrinsic Motivation for
learning," in Aptitude Learning and Instruction, edited by Snow and Farr, 1987, Vol. III, Ch. 10, p
223-253
Wed 3/26. Motivational Issues in Computer Education for Children -- J. Cooper. Achievements in
learning from computers. Intrinsic motivation: wanting to learn more in computer education.
Readings: Lepper & Malone, "Intrinsic Motivation and Instructional Effectiveness in Computerbased Education."
Week 8
Mon 3/31. Gender and the Computer - J. Cooper. Understanding anxiety and motivation as a
function of gender. How do males and females differ in their approach to avoidance of computers?
Are gender differences a function of software, of hardware? To what extent are gender differences
in computing a function of social content?
Readings J., Hall, J. and Huff, C.(1990). "Situation stress as a consequence of sex-stereotyped
software". Personality and Social Psychology Bulletin, Vol 16, pp. 419-429. Robinson-Staveley, K.
and Cooper, J. (1990). "Mere presence, gender and reactions to computers: Studying human-
computer interaction in the social context". Journal of Experimental Social Psychology, Vol. 25,
168-183.
Wed 4/2. Personality Differences in Computing - J. Cooper. Study of research findings on
personality differences in computing.
Readings Huff, C. and Cooper, J. (1987). "Sex bias in educational software: The effect of designers'
stereotypes on the software they design." J. Applied Social Psychology, Vol 17, pp. 519-532.
Cooper, J. and Stone, J. (1996). "Gender, computer-assisted learning, and anxiety: With a little help
from a friend." J. Educational Computing Research, Vol 16, pp. 65-89.
Segment 7: Learning and Doing with Machine - Professors A.L. Kornhauser & J. Gelfand
Week 9
Mon 4/7 Views of Viewing: The Anatomy of Vision and the Modeling of Visual Cognition -- A.
Kornhauser. A look at the human vision system; its anatomy, its operation and the modeling of the
system. Overview of the anatomy of the retina and the visual pathways, computational models of
low-level and high-level vision. Approaches to the modeling of the human vision system and visual
cognition. Computational models of low-level and high-level vision.
Readings: from J.H. Schwartz, Principles of Neural Science, Ch 27, "The Retina and
Phototransduction," Ch 28, "Anatomy of the Central Visual Pathways." From D. L. Osherson,
Visual Cognition and Action, Vol 2, Ch 1, "Computational Theories of Low-Level Vision," Ch 2,
"High-Level Vision," Ch 3 "Mental Imagery."
Wed 4/9 Learning with Machines and Artificial Neural Networks -- A. Kornhauser.
Foundations of artificial neural systems. Comparison of real and artificial neural systems. The
evolution of highly parallel distributed processing models known as neural networks. Presentation
of various mathematical frameworks, different approaches to learning; choices of training sets.
Specific examples using back-propagation networks.
Readings: Simpson, Artificial Neural Systems, Ch. 1-4. Kornhauser, "Neural Network Approaches
for Lateral control of Autonomous Highway Vehicles". Proc. Of VNIS Conf. Dearborne Mich. Oct.
1991, p 1143-1151.
Week 10
Mon 4/14 Helping Humans Make Better Decisions -- A. Kornhauser. With vast amounts of realtime information available, what kind of machines will help the individual make better decisions?
What are the communication, computing and interface requirements? How will the supporting
information be gathered and distributed. What about quality? A pragmatic example: getting from A
to B, how to navigate, guide and control.
Readings: To be selected by you as an assignment in preparation for this class.
Wed 4/16 The Thinking Brain -- J.J. Gelfand
Readings: to be distributed in class.
Final Project Descriptions Due Monday 4/21
The project combines a term paper with a brief visual presentation. Your plan for the project should
be discussed by one or two of the faculty in this course well in advance of Monday 4/21.
Segment 8: Consciousness and Human-Machine Interactions -- Professor R.G. Jahn
Week 11
Mon 4/21. Princeton Engineering Anomalies Research. Purpose, history, style, agenda.
Human/Machine Experiments I:
1. Benchmark Random Event Generators; Technical and Procedural Variants
2. Results and Interpretations; Implications and Applications
Readings Jahn and Dunne, Margins of Reality, Section II; Two Decades of PEAR: An Anthology of
Selected Publications, Articles #14 ("Correlations of Random Binary Sequences with Pre-Stated
Operator Intention"), #6 ("Experiments in Remote Human/Machine Interactions"), #8 ("Count
Population Profiles in Engineering Anomalies Experiments"), #10 ("Series Position Effects in
Random Event Generator Experiments"), and #11 ("Gender Differences in Human/Machine
Anomalies").
Wed 4/23. Princeton Engineering Anomalies Research (continued). Human/Machine Experiments
II: Field Applications. Information Acquisition and Remote Perception.
Readings Margins of Reality, Section III; Two Decades of PEAR: An Anthology of Selected
Publications, Article #7 ("FieldREG II: Consciousness Field Effects, Replications and
Explorations"); Remote Perception Research at PEAR (handout).
Week 12
Mon 4/28. Theoretical Modeling and Review of Science History.
Readings Margins of Reality, Sections I, IV, V; Two Decades of PEAR: An Anthology of Selected
Publications, Articles #12 ("Anomalies: Analysis and Aesthetics") and #15 ("Science of the
Subjective"). Secondary References: Heisenberg, Physics and Philosophy, Harper/Collins, 1962
Hoffman, The Strange Story of the Quantum, P. Smith 1963; S.C. Florman, The Existential
Pleasures of Engineering, St. Martin, 1976; W. James, The Will to Believe and other Essays in
Popular Philosophy, Dover, 1956; Jahn and Dunne, Collected Thoughts on Role of Consciousness
in the Physical Representation of Reality, PEAR, 1984.
Wed 4/30. Quantum Mechanics of Consciousness; A Modular Model of Mind/Matter Interactions.
Readings Margins of Reality, Section IV; Two Decades of PEAR: An Anthology of Selected
Publications, Article #2 ("On the Quantum Mechanics of Consciousness, with Application to
Anomalous Phenomena"); "A Modular Model of Mind/Matter Interactions" (handout).
Thursday evening 5/1 SECOND-HOURLY EXAM (covers weeks 7-12)
Reading Period
Term Project Symposium
Monday May 12, 2002. 9:00am-1:00pm TERM PROJECT SYMPOSIUM Formal 10 minute
presentation of term project. Use of visual aids is highly recommended.