SYMBOLIC SYSTEMS 209:
Battles Over Bits (3 units)
Autumn Quarter 2007-2008, Stanford University
Instructor:  Todd Davies
Meeting Time: Tuesdays 7:15-9:45 PM (first meeting on September 25)
Location: 460-126 (Joseph Greenberg Room, Margaret Jacks Hall, 1st floor)
Instructor's Office: 460-040C (Margaret Jacks Hall, lower level)
Phone: x3-4091; Fax: x3-5666
Email: tdavies at csli.stanford.edu
Office Hours: Tuesdays, Wednesdays, and Thursdays 10:30 AM - 12:00 Noon
Course website: http://www.stanford.edu/class/symbsys209 (this syllabus)
Course blog: http://symbsys209.edublogs.org

Updated December 3, 2007

Prerequisite: Completion of Psych 40, Psych 55, Psych 70, or SymbSys 170/270; or consent of the instructor

Background:

In the age of the Internet, information has increasingly taken on the characteristics of what economists call a "public good".  A public good is one that is non-rival in consumption, meaning that one person's consumption of the good does not preclude or interfere with someone else's.  If I have a private good, such as an apple, then if I eat it up, you may not.   If I give it to you, I no longer have it.  When information is only available in a bundled physical form such as a book or a videotape, then it too has characteristics of a private good.  If I lend you a book, then I no longer have it, unless I have two copies of the same book. But on the Internet, I can send you a digital file of the book without losing my own copy and we can then both read it.  Your consumption will not preclude or interfere with mine.  The information has thus become nonrival, or a "public good". 

A public good may have the additional property of being nonexcludable, meaning that it is either difficult or impossible for the producer of the good to select who can and who cannot consume it.  Excludability is necessary if you want to force people to pay for something. If a good is nonexcludable, then if one person pays for and consumes the good, many more can consume it without paying.  When information is nonrival, then producers of it are hard-pressed to prevent people from sharing it, since there is little cost to the consumers and much they can gain from each other through trading.  With digital information such as songs, movies, and software, producers attempt to restrict file sharing with copy protection technology, but effective copy protection is extremely difficult to achieve, and is in some sense impossible for analog-convertible media. When copy protection fails, information is nonexcludable. 

Exclusion can, however, be enforced by the state.  Laws can be passed making it illegal for anyone to obtain information without paying the producer, and surveillance technology increases the government's ability to monitor compliance.  Thus, the Internet has increased incentives for producers of information who want to keep it excludable to try to get the government to enforce the exclusion, through legal mechanisms such as copyrights.  This has led to an instance of what appears to be the loser's paradox: as the producers of information have lost economic power, they have gained government favor; as network communication technology has made information much easier to share, laws to prevent sharing have been strengthened. 

Access to communication and to the Internet itself have also become more like public goods through developments in wireless technology.  If there is enough spectrum to allow everyone to move as much data as they want through the air, then we might expect long-distance communication to be treated much like breathing: free to all without the need to pay a fee.  Once again, however, government can step in and declare that wireless communication must be licensed, a barrier to entry that then allows holders of the licenses to charge a fee for accessing their networks.  Public goods (or quasi-public goods) can arise through government choice, as when a government builds a free highway system, or when a portion of spectrum is unlicensed.  Increasingly, local governments have been attempting to create free broadband networks.  Proprietary network providers have acted to prevent this, however, on grounds that government-subsidized free networks constitute unfair competition with their fee-based services.

Copyrights, trademarks, patents, and licenses are all ways of legally restricting how people can use information.  As such, they depend on the notion of "intellectual property" -- legal ownership and rights to control information that has been produced through human effort.  In the United States, intellectual property generally entails economic rights: e.g., the right to receive payment for information, or the right to a monopoly in the market for an information-derived product.  An alternative perspective, however, has arisen from the "free software" movement -- the idea of a "copyleft" license like the GNU General Public License (GPL).  The GPL relinquishes a producer's economic claims on the use and distribution of computer code for users who agree to share any improvements they make to the code under the same license.  The GPL and related licenses are the basis of the "open source" approach to software development.  Open source programs such as the Linux operating system and the Firefox web browser have been denounced by proprietary software vendors and, though the debate has cooled down somewhat, many in the software industry view the whole concept as a threat to themselves, the industry, and even the economy as a whole. 

The attempts by vested interests to influence public attitudes and government policy have led to numerous legal and political battles.  In all of these "battles over bits", proprietary and commercial interests generally make two broad arguments: (1) some form of exclusion is necessary for information and communication industries to make a profit; and (2) the possibility of making a profit is a necessary incentive for producing the communication technology and information that most people want.   In this course, we will examine these and other arguments and assumptions underlying recent battles over bits, applying critical thinking as well as theory and evidence from several disciplines.

Course Plan (tentative):

This year, I propose to organize the course around a single book: The Wealth of Networks by Yochai Benkler (2006).  After an overview and introduction to some background material from psychology in week 1, the whole class will read Benkler's book over weeks 2 through 7.  For the last three weeks of the course, students will present and lead discussions about other works they have read related to the themes of the course, and we will have a summation at the end. The exact schedule of the last three weeks will depend on the number of students enrolled and their interests.

The written component of the course will take place on a course blog, with weekly blog comments graded in a mixed instructor/self/peer scheme (see below for details).  Blog postings must be made ahead of each class session so that everyone can read them before that week's discussion.  I will lead the discussions of Benkler's book over the first phase of the course (weeks 1-7), turning it over to student presenters/discussion leaders in the latter phase (weeks 8-10).  A tentative schedule is given below.

Requirements:

Each student is required to (a) attend and participate regularly, (b) do the assigned reading 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.

Schedule:

Week 1 (September 25) -- Overview and Background

Week 2 (October 2) - The Wealth of Networks 1&2

Required Reading:

Supplementary Reading:

Supplementary Event:

Week 3 (October 9) -- The Wealth of Networks 3&4

Required Reading:

Week 4 (October 16) -- The Wealth of Networks 5&6

Required Reading:

Supplementary Reading:
 Supplementary Events:
 Week 5 (October 23) - The Wealth of Networks 7&8

Required Reading:

Supplementary Event:
 Week 6 (October 30) -- The Wealth of Networks 9&10

Required Reading:

Supplementary Reading:
 Supplementary Event:
 Week 7 (November 6) -- The Wealth of Networks 11&12

Required Reading:

Supplementary Reading (compiled by Jessica, every student should pick one, read and share it):

Week 8 (November 13) -- Student-led Discussions I

Presentations:

Supplementary Event:

Week 9 (November 27) -- Student-led Discussions II

Presentations:

Supplementary Reading:
 Supplementary Event:

Week 10 (December 4) -- Student-led Discussions III

Presentations:

Supplementary Event:

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:

Each week, I will solicit from each student the following scores (out of 5 points possible), 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.

Pool of Suggested Readings for Student-Led Discussions (Weeks 8-10):