Math You Can't Use: Patents, Copyright, and Software

192 Pages·2005·0.83 MB·English

by  Ben Klemens

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MA H
YOU CAN’T USE
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MA H
YOU CAN’T USE
Patents,Copyright,and Software
Ben Klemens
Brookings Institution Press
Washington,D.C.
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THE BROOKINGS INSTITUTION
The Brookings Institution is a private nonprofit organization devoted to research,
education, and publication on important issues of domestic and foreign policy.
Its principal purpose is to bring the highest quality independent research and analysis
to bear on current and emerging policy problems. Interpretations or conclusions in
Brookings publications should be understood to be solely those of the authors.
Copyright © 2006
THE BROOKINGS INSTITUTION
1775 Massachusetts Avenue, N.W., Washington, D.C. 20036
www.brookings.edu
All rights reserved
Library of Congress Cataloging-in-Publication data
Klemens, Ben.
Math you can’t use : patents, copyright, and software / Ben Klemens.
p. cm.
Summary: “Gathering persepectives from law, computer science, mathematics, and
economics, examines the intellectual property issues surrounding computer software
and suggests how patents might accommodate the unique structure of code and copy-
right for software could be more effectively implemented”—Provided by publisher.
Includes bibliographical references and index.
ISBN-13: 978-0-8157-4942-4 (cloth : alk. paper)
ISBN-10: 0-8157-4942-2 (cloth : alk. paper)
1. Intellectual property. 2. Intellectual property—United States. 3. Computer
software—Law and legislation. I. Title.
K1519.C6.K54 2005
346.04'8—dc22 2005027332
9 8 7 6 5 4 3 2 1
The paper used in this publication meets minimum requirements of the
American National Standard for Information Sciences—Permanence of Paper
for Printed Library Materials: ANSI Z39.48-1992.
Typeset in Sabon
Composition by R. Lynn Rivenbark
Macon, Georgia
Printed by R. R. Donnelley
Harrisonburg, Virginia
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Contents
Preface vii
CHAPTER ONE
Introduction 1
CHAPTER TWO
Optimal Breadth 12
CHAPTER THREE
From Equations to Software 24
CHAPTER FOUR
Patenting Math 44
CHAPTER FIVE
Profiting from Overbroad Patents 73
CHAPTER SIX
The Decentralized Software Market 92
CHAPTER SEVEN
Interoperability 108
CHAPTER EIGHT
Protecting Text 131
CHAPTER NINE
Policy Recommendations 151
Glossary 161
References 167
Index 171
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Preface
I
am a quant. Almost all of my work involves either pure
math or writing computer code to calculate numbers—even this book
will rely on one mathematical theorem (which I promise will be painless).
In my free time, I’ve done things like write a video game and a short guide
to statistical analysis using the C programming language.
But this is a policy book about writing good laws, so let me summarize
what I want from the law: to be left alone to write code and do math.
I am not trying to rationalize or alibi theft; I just want to be able to do cal-
culations and write programs using my own ingenuity without worrying
that anyone will have a claim on my results.
I am not exactly worried that a jackbooted lawyer might kick down
my door at three in the morning. I distribute little of my code to the
world, and statistics is not the most lucrative of fields. But I can’t write
code in a vacuum and need tools written by others to do the hard parts.
With increasing frequency, software projects are being shut down or crip-
pled because of legal problems. As a result, I can do less.
When my brother bought a Linux PC so he could run simulations of
new circuit designs, he asked me (his twenty-four-hour tech support hot-
line) how he could use the machine to listen to his music in MP3 format.
“Sorry,” I explained, “that would infringe patents. You’ll need to pur-
chase a copy of Windows, since Microsoft has negotiated the appropriate
licenses.” What about using the PC to watch the DVDs in his living
vii
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viii PREFACE
room? Nope, violates federal law. Can’t be done unless you want to be an
outlaw and download C code from Brazil and recompile it on your PC.
How about just watching QuickTime movies from the Internet? Sorry
again, but QuickTime depends on the Sorensen Codec, and Sorensen
won’t let Linux programmers write anything that can read its data struc-
tures. Opening Word documents? You cando that, with OpenOffice.org,
but there’s an application pending with the U.S. Patent and Trademark
Office that may let Microsoft shut that down.
As for the electrical engineering simulations he’d originally bought the
computer for?Those might be OK, but see page 63 for a list of patents
that his simulations may inadvertently infringe if he calculates his Fourier
transforms in certain manners. (His work frequently involves simulating
integrated circuits, and he holds hardware patents 6,147,653 and
6,239,755. However, he has never written a video game.)
Another time, he mentioned that he was thinking about writing a
package to do simulations for nonlinear optics problems, since there are
none on the market now. “I’m safe using algorithms published in journal
articles?” he asked. The answer is once again no. On page 88,I discuss a
data compression method from a peer-reviewed journal that led to patent
headaches for those who were foolish enough to apply a published math-
ematical algorithm without consulting a lawyer first. In my own statisti-
cal work, I make use of factor analysis reasonably often, but some meth-
ods of factor analysis are now covered by patent 6,807,536.
An entirely new economic arrangement has appeared in mathematics
and its offspring, computer science. Before, we were free to do whatever
our abilities allowed, since mathematical and computational results were
in the public domain—nobody could own an idea. This arrangement
worked to bring us the mathematical and computationally advanced
world we live in today. But in the past decade, a new set of rules has been
imposed: an individual can own a mathematical result that he or she has
discovered and can sue those who do not ask permission to use that
result—even if the other person independently derived it.
The ownership of mathematical algorithms is truly a new concept and
engenders one of the main questions underlying economics and law: what
can a single human being claim ownership of? Although people some-
times describe property ownership as “natural,” it is clearly a social
invention, designed to overcome economic and social problems. For
example, the Earth was here 4.5 billion years before I was, and yet I am
the sole owner of that piece of it that rests under my house. As a society,
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PREFACE ix
we have established this property right as a sensible solution to the
sitcom-esque problems that would arise if anybody could show up at my
home and use it as their own. Conversely, the benefits to private owner-
ship of the sidewalk in front of my house are significantly fewer, so soci-
ety has granted no one private ownership of it. There are other economic
arguments for the ownership of abstractions like the design of a machine,
which I discuss in this book.
The reader has no doubt been exposed to more than enough rhetoric
about the fact that we live in an information age and our economic
progress depends on the efficient movement and processing of informa-
tion—and efficient information usage depends on better mathematical
algorithms. But does inventing (and enforcing) the concept of ownership
of a mathematical theorem make for a better economy? Is a mathemati-
cal algorithm more like a house or a sidewalk?
This is the first book to seriously ask whether it makes sense to allow
for ownership of a computational algorithm. This question is not about
the metaphysics of ownership, but about economic practicalities: because
individuals can own the results of their research, they are more likely to
innovate, but when you can’t use the math without permission, imple-
menting and using the innovations become more costly. Since the new
protections are not unambiguously a plus, we have to do the cost-benefit
analysis to determine whether the new innovation they bring about is
worth the trouble they cause.
The Credits
Thanks to the following people, who suffered through my illegible
early drafts:
Robert Axtell, Derrick Higgins, and Guy Klemens (Computation)
Joseph Harrington and Brian Kahin (Economics)
Chris Kelaher, Mary Kwak, and Vicky Macintyre (Editorial issues)
Matthew Bye (Legal issues)
Derrick Higgins and Arika Okrent (Linguistics)
Josh Epstein, Carol Graham, and Peyton Young (Center on Social and
Economic Dynamics)