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Background and charge
The Committee was appointed in the spring of 1990 by George Nemhauser, Chairman of the Mathematical Programming Society (MPS). Its charge follows:
``The purpose of the committee should be to devise a position for MPS to adopt and publicize regarding the effects of patents on the advancement of research and education in our field. The committee may also wish to comment on the recent past history.''
This is the report of the Committee. It comprises a main body with our assumptions, findings of fact, conclusions, and recommendations. There are two appendices, prepared by others, containing a great deal of specific factual information and some additional analysis.
Assumptions
MPS is a professional, scientific society whose members engage in research and teaching of the theory, implementation and practical use of optimization methods.
It is within the purview of MPS to promote its activities (via publications, symposia, prizes, newsletter), to set standards by which that research can be measured (such as criteria for publication and prizes, guidelines for computational testing, etc.), and to take positions on issues which directly affect our profession.
It is not within the purview of MPS to market software products, and MPS should not become involved in issues related to the commercial aspects of our profession except where it directly affects research and education.
The Committee is unable to make expert legal analyses or to provide legal counsel. The main body of this report is therefore written from the perspective of practitioners of mathematical programming rather than from that of attorneys skilled in the law.
MPS is an international society. However, the Committee has interpreted its charge as applying apecifically to U.S. patent law and its application to algorithms. All comments and conclusions of this report should be read with this fact in mind.
Facts about patents and copyrights
The three principal forms of legal protection for intellectual property are the copyright, the patent, and the trade secret. Copyrights and patents are governed by federal law, trade secrets by state law. Setting aside the issue of trade secrets, some of the distinctions between copyrights and patents can be summarized as follows.
Type of property protected: Patents protect ideas, principally ``nonobvious'' inventions and designs. It is well estabished that ``processes'' are patentable. The Patent Office currently grants patents on algorithms and software, on the basis of the ambiguous 1981 U.S. Supreme Court decision in Diamond v. Diehr.
Copyrights do not protect ideas. Instead, they protect the expression of ideas, in ``original works of authorship in any tangible medium of expression.'' The principle that software is copyrightable appears to have been well established by the 1983 decision of the U.S. Court of Appeals in Apple v. Franklin.
How protection is obtained: Federal law is now in essential conformity with the Bern Copyright Convention. As a consequence, international copyrights are created virtually automatically for most works of authorship. Government registration of copyrights is simple and inexpensive to obtain.
By contrast, patents are issued by the U.S. Patent Office only after an examination procedure that is both lengthy (three years or more) and costly ($10,000 and up in fees and legal expenses). An inventor must avoid public disclosure of his invention, at least until patent application is made, else the invention will be deemed to be in the public domain. Patent application proceedings are confidential, so that trade secret protection can be obtained if a patent is not granted.
Length of protection: U.S. patents are for 17 years. Copyrights are for the lifetime of the individual plus 50 years or, in the case of corporations, 75-100 years.
Facts about algorithms
Algorithms are typically designed and developed in a highly decentralized manner by single individuals or small groups working together. This requires no special equipment, few resources, and little cost. The number of people involved is also quite large compared to the needs of the marketplace. Independent rediscovery is a commonly occurring phenomenon.
There is a long and distinguished history of public disclosure by developers of mathematical algorithms via the usual and widely-accepted channels of publication in scientific journals and talks at professional meetings. These disclosures include the theoretical underpinnings of the method, implementation details, computational results, and case studies of results on applied problems. Indeed, algorithm development is based on the tradition of building upon previous work by generalizing and improving solution principles from one situation to another.
The commercial end product of an algorithm (if there is any) is generally a software package, where the algorithm is again generally implemented by a very small number of individuals. Of course, a larger group of people may be involved in building the package around the optimization software to handle the user interface, data processing, etc. Also, others may be involved to handle functions like marketing, distribution, and maintenance.
Competition in the marketplace has been traditionally based on the performance of particular implementations and features provided by particular software products. The product is often treated like a ``black box'' with the specific algorithm used playing a rather minor role.
The cost of producing, manufacturing, distributing and advertising optimization software is often quite small. Even when this is not the case, it is generally the implementation of algorithms that is costly, rather than their development. Software manufacturers have a need to protect their investment in implementation, but have little need to protect an investment in algorithmic development. In the absence of patents, algorithms–like all of mathematics and basic science– are freely available for all to use.
Traditionally, developers of optimization software have protected their investments by keeping the details of their implementation secret while allowing the general principles to become public. Software copyrights are also an appropriate form of protection, and are now widely used. Moreover, despite unresolved legal questions concerning the ``look and feel'' of software, the legal issues of copyright protection seem to be relatively well settled.
Often an optimization package is a small (but important) part of an overall planning process. That process is often quite complex; it may require many resources and great cost to complete, and the potential benefits may be uncertain and distributed over a long time period. In such situations it is usually quite difficult to quantify the net financial impact made by the embedded optimization package.
Public policy issues
Will algorithm patents promote invention? Article I, Section 8 of the U.S. Constitution empowers Congress ``To promote the Progress of Science and useful Arts, by securing for limited Times to Authors and Inventors the exclusive Right to their respective Writings and Discoveries.'' Inasmuch as patents are intended to provide an incentive for invention, it seems appropriate to inquire whether patenting of algorithms will, in fact, create an incentive for the invention of algorithms.
Given the existing intensity of research and the rapid pace of algorithmic invention, it seems hard to argue that additional incentives are needed. In fact, there is good reason to believe that algorithm patents will inhibit research, in that free exchange of ideas will be curtailed, new developments will be held secret, and researchers will be subjected to undesired legal constraints.
Will algorithm patents provide needed protection for software manufacturers? Copyright and trade secret protection appear to provide the sort of protection most needed by software manufacturers. By their nature, patents seem to offer a greater potential for legal confrontation than copyrights. Instead of providing protection, algorithm patents actually pose a threat to smaller software houses lacking the resources to defend themselves in costly patent litigation. It can be argued that patents encourage an oligarchical industrial structure and discourage competition.
Is the Patent Office able to deal with algorithm patents? There is abundant evidence that the Patent Office is not up to the job. Many algorithmic ``inventions'' have been granted undeserved patents, greatly increasing the potential for legal entanglement and litigation. Moreover, it seems unlikely that there will be any substantial improvement in the quality of patent examinations.
Conclusions
It seems clear from the previous discussion that the nature of work on algorithms is quite different from that in other fields where the principles of patents apply more readily. This in itself is a strong argument against patenting algorithms.
In addition, we believe that the patenting of algorithms would have an extremely damaging effect on our research and on our teaching, particularly at the graduate level, far outweighing any imaginable commercial benefit. Here is a partial list of reasons for this view: • Patents provide a protection which is not warranted given the nature of our work. • Patents are filed secretly and would likely slow down the flow of information and the development of results in the field. • Patents necessarily impose a long-term monopoly over inventions. This would likely restrict rather than enhance the availability of algorithms and software for optimization. • Patents introduce tremendous uncertainty and add a large cost and risk factor to our work. This is unwarranted since our work does not generate large amounts of capital. • Patents would not provide any additional source of public information about algorithms. • Patents would largely be concentrated within large institutions as universities and industrial labs would likely become the owners of patents on algorithms produced by their researchers. • Once granted, even a patent with obviously invalid claims would be difficult to overturn by persons in our profession due to high legal costs. • If patents on algorithms were to become commonplace, it is likely that nearly all algorithms, new or old, would be patented to provide a defense against future lawsuits and as a potential revenue stream for future royalties. Such a situation would have a very negative effect on our profession.
Recommendations
The practice of patenting algorithms is harmful to the progress of research and teaching in optimization, and therefore harmful to the vital interests of MPS. MPS should therefore take such actions as it can to help stop this practice, or to limit it if it cannot be stopped.
In particular: • The MPS Council should adopt a resolution opposing the patenting of algorithms on the grounds that it harms research and teaching. • MPS should urge its sister societies (e.g., SIAM, ACM, IEEE Computer Society, AMS) to take a similar forthright position against algorithm patents. • MPS should publish information in one or more of its publications as to why patenting of algorithms is undesirable. • The Chairman of MPS should write in his official capacity to urge members of Congress to pass a law declaring algorithms non-patentable (and, if possible, nullifying the effects of patents already granted on algorithms). • MPS should support the efforts of other organizations to intervene in opposition to the patenting of algorithms (for example, as friends of the court or with Congress). It should do so by means such as providing factual information on mathematical programming issues and/or history, and commenting on the impact of the patent issue to our research and teaching in mathematical programming. MPS should urge its members to do likewise.
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