SYMBOLIC SYSTEMS 205:
Systems: Theory, Science, and Metaphor (3 units)
Spring Quarter 2006-2007, Stanford University
Instructor:  Todd Davies
Meeting Time: Wednesdays 7:15-9:45 PM (first meeting on April 4)
Location: 460-334
Instructor's Office: 460-040C (Margaret Jacks Hall, lower level)
Phone: x3-4091; Fax: x3-5666
Email: davies at csli.stanford.edu
Office Hours: Tuesdays, Wednesdays, and Thursdays 10:30 - 11:55 AM

Course websites:

Version: June 7, 2007
-- Note: This page will change throughout the quarter. Please check back periodically for updates.. --

Prerequisite: Completion of at least one course from the Symbolic Systems undergraduate core in each of the following areas: (a) philosophy, (b) linguistics or psychology, and (c) computer science

Symbolic Systems 205 is a small, upper-division reading- and discussion-based seminar.  The general topic of the course is systems science: the exploration of abstract properties of systems, such as network connectivity, complexity, feedback, self-organization, and emergence, with applications in natural, social, and artificial domains.  Systems theories have often been met with skepticism within traditional disciplines, and have been attacked as being too general to be useful and too vague to be testable.  A continuing goal of the course is to ascertain the merits of such criticisms, and of the theories themselves.  It is often claimed that viewing phenomena as systems under a particular framework can lead to novel insights, and such frameworks have frequently seeped into the broader culture to influence how people think and talk.  Each new wave of systems science generally draws both criticism and praise of the aforementioned types and it is a goal of this course to evaluate such claims afresh as new theories appear.

The theme is meant to change each time the course is taught, and for this year the theme is:

Positive Feedback Cycles:
Virtuous, Vicious, and Misunderstood

The Theme: Positive Feedback Cycles

In colloquial use, the phrase "positive feedback" typically refers to something most of us seek: a signal from others that we have done a good job. In systems theory, however, "positive feedback" does not necessarily have a good connotation, and complimentary remarks about one's performance may or may not produce it. "Positive feedback" in this more technical sense simply refers to a condition in which the output or activity of a process is self-reinforcing. A classic example is the quickly loudening sound produced when a microphone is placed near a loudspeaker, as in the diagram below (courtesy of Media College):

An audio feedback loop

In the above example, the output or activity is noise from the loudspeaker, which is picked up by the microphone and then "fed back" to the speaker via the mixer and the amplifier. The result is a rapid increase in volume coming from the speaker -- an increase due entirely to the way in which the system is put together. The microphone is intended to amplify noise (e.g. human voices) coming from sources outside of the sound system, but instead it is overrun by the system's amplification of its own noise. The process continues until the noise becomes unbearable, in what is often called a "vicious cycle". Examples of vicious cycles abound in various domains, from viral epidemics to currency crises.

But positive feedback can also be helpful and productive. In fact, the sound system described above makes use of positive feedback internally to amplify the signal. An encouraging reaction to a job well done can sometimes motivate continued or improved performance the next time, leading to more encouragement, better performance, and so on in a "virtuous cycle". Positive feedback helps us to stop our cars when they are in motion, and is a crucial aspect of bodily processes such as childbirth contractions and blood clotting in response to a wound.

Systems theorists have emphasized the importance of feedback cycles from the field's earliest days, and in fact the first major manifestation of systems thinking -- cybernetics -- is often defined as the study of feedback. Positive feedback is contrasted with "negative" feedback, in which a high level of activity attenuates, rather than amplifies, subsequent output of the system, so that activity is self-limiting rather than self-reinforcing. Examples include a thermostat automatically shutting down a furnace after it has heated up a building, and our need to rest after a period of heavy exercise. Natural processes often involve positive feedback up to a point but then become self-limiting at some threshold, e.g. appetite, sexual arousal, and sleepiness. But there is always a danger that critical resources will be exhausted before a positive feedback process is halted, which may lead to catastrophe. Alternatively, a system may just operate for long periods outside of its desirable range, e.g. chronically sleep-deprived people in competitive environments, caught in the phenomenon known as the "hedonic treadmill".

For cognitive science, an interesting apparent fact about positive feedback is that people underestimate its importance in many situations. The microphone-speaker phenomenon illustrates this. People are surprised by the effect when they first encounter it, and often have to be told what to do in order to get rid of the screaching noise. Psychological depression may in part reflect difficulty both in anticipating the positive feedback loops involved in depression (life's problems are made worse by depression, which leads to more depression) and also in finding the "upward spiral" that begins with small improvements in activity and mood, which facilitate further such increases. A failure to appreciate positive feedback can have devastating effects on individuals, societies, and possibly the entire planet.

General Course Plan

The plan is to divide the quarter into three phases. In phase I (weeks 1 through 3), we will review the major developments in systems science since its origins in the mid-20th century. In phase II (weeks 4-7), we will discuss a common set of readings chosen around a different theme each week, looking at a few areas where positive feedback cycles have been applied. .Phase III of the course (weeks 8-10) will consist of student-led presentations and discussions of topics chosen by students for their focus topics. Focus topics are areas of study or phenomena in which positive feedback cycles appear to play an important role.

A tentative schedule of readings is given below. Class sessions, beginning in the second week, will be followed by screenings of assigned films, beginning at 9:45. Films will also be either available in the library during the week they are assigned, or viewable via the Internet, so attendance at the screenings is optional but encouraged for those who can stay.

Each student is required to (a) attend and participate regularly, (b) do the assigned reading and film viewing and post at least one reaction comment on the course blog per week, by 6 pm on the day of class, and (c) select and present a focus topic in class, provide sample readings for the class at least one week ahead of their presentation, and lead a discussion on their focal topic during phase II of the course. There is no final paper or exam in the course.

See the discussion guidelines for tips on how to contribute to in-class discussions. See the presentation guidelines for tips on leading a discussion during the last three weeks of the course.

Schedule

Week 1 - April 4. Introduction and overview. Meet and greet, go over the syllabus.

Week 2 - April 11. An overview of systems science I. Systems thinking, feedback, and cybernetics.

Assigned:

Other:

Week 3 - April 18. An overview of systems science II. Self-organization, complexity, and networks.

Blog comment scores due by email to the instructor by Friday, April 20, 5 pm.

Week 4 - April 25. Reputation and Quality. The Matthew effect and cumulative advantage.

Week 5 - May 2. Income and Wealth. Investment, success, and inequality.

Week 6 - May 9. Belief and Desire. Psychological effects.

Assigned:

Other (note: citation does not constitute endorsement of content):

Week 7 - May 16. Technology and History. Our past and future: global warming, politics and singularity.

Blog comment scores due by email to the instructor by Monday, May 21, 12:01 pm.

Week 8 - May 23. Student Presentations I.

"Stereotype Threat" (Siobhan):

"Psychological Health" (Jessica):

Week 9 - May 30. Student Presenations II.

"Prisons and Crime" (Jack):

"Currency Crises" (Jorge):

Week 10 - June 6. Student Presentations III.

"Homophily" (David and Erich):

Blog comment scores due by email to the instructor by Saturday, June 9, 10 pm.

Possible Topics for Presentationa:

Grading

The course grade will be based on the following breakdown:

Grades for the presentation/discussion leading and attendance/partifcipation will be assigned by me alone. Grades for blog posts, however, will be graded in the following way:

At three points in the quarter: following weeks 2-3 (10 points), 4-7 (20 points), and 8-10 (15 points), I will solicit from each person the following scores (out of the points available during that period), to be sent to me by email:

Before reading your self/peer scores, I will assign my own score (Ti) to each student's comments. I will not share any information about your scoring with anyone else in the class - only I will know how you scored yourselves and each other. Assuming you are student k and there are n students (indexed by i) in the class, your total score for the period being scored will be:

(1/3) Tk

+

(1/3) {Sk / [1 + ln(1 +| Sk - Tk|)]}

+

(1/3) [∑i≠k Pik / (n-1)] / {1 + ln[1 +∑i≠k |Ti - Pki| / (n-1)]}

This formula combines my score for you with your own self-evaluation and your peers' evaluations of you weighted by a meta-evaluation (how well your scores agree with mine). This is an incentivizing system, but it makes it very hard to get a perfect score. As you will see, though, that is okay once you understand that scores are bound to appear lower than they otherwise will be. Don't worry - it won't mean that everyone will get a low grade at the end. The main things to understand are that (a) your total score will depend on what you, I, and your peers each think, and (b) your total score will benefit a lot if you assign scores to yourself and others that you think will be close to the ones I will assign. It should work okay if I assign scores that people think are fair. The formula above is friendlier than the one I initially came up with, and I think it will be easier for everyone to deal with. We'll have a few iterations to test it out.

It may seem like I am weighting my own opinion excessively (by defining my own scores to be the standard for comparison with self/peer scores), but remember that if I were grading in the usual way, your own and your fellow students' evaluations of you wouldn't count at all. This system is designed to get everyone thinking seriously about the value of their own and others' contributions. And I will certainly welcome your feedback on the scoring system as we proceed, especially at the end of the course when we have had a real chance to see how it works.