Credimus

We believe that economic design and computational complexity---while already important to each other---should become even more important to each other with each passing year. But for that to happen, experts in on the one hand such areas as social choice, economics, and political science and on the other hand computational complexity will have to better understand each other's worldviews. This article, written by two complexity theorists who also work in computational social choice theory, focuses on one direction of that process by presenting a brief overview of how most computational complexity theorists view the world. Although our immediate motivation is to make the lens through which complexity theorists see the world be better understood by those in the social sciences, we also feel that even within computer science it is very important for nontheoreticians to understand how theoreticians think, just as it is equally important within computer science for theoreticians to understand how nontheoreticians think

A personal account of Turing’s imprint on the development of computer science

The rst part of the XX century saw the development of the digital computer and the eld of computer science. In the present paper, we sketch our vision of that period and of the role that Alan Turing and some of his contemporary peers played in that development.Preprin

Life Style Education: Are We Prepared for Changes?

The public should be aware of the sudden change of life style of some people that makes their life completely different from their previous ones. All of us must be ready to face any circumstances from this manifestation in the future.  The rich, wealthy and famous should be made aware that that type of life style is not wrong, but they should also be taught how to follow a normal way of life. Proper guidance and counselling on how to live normally needs to be provided with especially designed lectures and classes. Bringing these “students” to remote villages where the poor and the disadvantaged live may help them to understand the hardships of life around them. Having a short intern period within such a community will help them further understand the real life of the majority in their country. Furthermore, if they are always taught in an environment of luxury and are never faced with a normal education system and style of life, a major problem arises: if, in the future, our country is led by such graduates, who never went through our normal education system or lived a normal style of life, how can they understand and lead the majority in our country? This paper discusses this phenomenon

Not all computational methods are effective methods

An effective method is a computational method that might, in principle, be executed by a human. In this paper, I argue that there are methods for computing that are not effective methods. The examples I consider are taken primarily from quantum computing, but these are only meant to be illustrative of a much wider class. Quantum inference and quantum parallelism involve steps that might be implemented in multiple physical systems, but cannot be implemented, or at least not at will, by an idealised human. Recognising that not all computational methods are effective methods is important for at least two reasons. First, it is needed to correctly state the results of Turing and other founders of computation theory. Turing is sometimes said to have offered a replacement for the informal notion of an effective method with the formal notion of a Turing machine. I argue that such a view only holds under limited circumstances. Second, not distinguishing between computational methods and effective methods can lead to mistakes when quantifying over the class of all possible computational methods. Such quantification is common in philosophy of mind in the context of thought experiments that explore the limits of computational functionalism. I argue that these ‘homuncular’ thought experiments should not be treated as valid

The Policy Implications of Granting Patent Protection to Computer Software: An Economic Analysis

This Note analyzes the propriety of granting patent law protection to computer software by viewing this problem from economic, legal, public and technological policy perspectives. Part II explains the relationship between computer hardware and software, discusses the role of algorithms in software development,and traces the development of the computer software industry.Part III analyzes the economic policies underlying the patent system. Part IV identifies the patent law principles that are relevant to the software patentability issue and discusses their underlying policy foundations. Part V examines the Supreme Court\u27s application of these principles in the leading software patent cases and concludes that the Court\u27s failure to understand computer technology has caused it to withhold patent protection from computer software. Part V reveals that the Supreme Court has mischaracterized software algorithms by treating them as unpatentable mathematical laws. Part VI of this Note analyzes the benefits and costs of granting patent protection to computer software and demonstrates the compelling societal need for this protection. \u27Part VI also proposes an addition to the Patent Office of a small staff of computer science experts to remedy the administrative problem of processing software patent applications