Dan Hunter

Cyberspace as Place and the Tragedy of the Digital Anticommons

Cyberspace was once thought to be the modern equivalent of the Western Frontier, a place, where land was free for the taking, where explorers could roam, and communities could form with their own rules. It was an endless expanse of space: open, free, replete with possibility. This it true no longer. This Article argues that we are enclosing cyberspace, and imposing private property conceptions upon it. As a result, we are creating a digital anti-commons where sub-optimal uses of Internet resources is going to be the norm. Part I shows why initial discussions of cyberspace as place have mistaken the idea of how we think about cyberspace, with the normative question of how we should regulate cyberspace. It suggests that we can bracket the normative question, and still answer the descriptive question of whether we think of cyberspace as a place. Part II then examines the lessons of recent cognitive science, and demonstrates the importance of physical metaphors within our cognitive system. It then examines the evidence of our use a physical metaphor, “cyberspace as place”, in understanding online communication environments. Part III focuses on the unacknowledged, and unrecognized, influence that this metaphor has had on the development of the legal framework for the Internet. It examines tortious, criminal, and constitutional law responses to cyberspace, and concludes that the metaphor of “cyberspace as place” exercises a strong, and unrecognized, influence on the regulatory regimes of cyberspace. Part IV details the implications of this observation and show why they are extremely troubling. The conception of “cyberspace as place” leads to the implication that there is property online, and that this property should be privately owned, parceled out, and exploited. Though private ownership of resources of itself is not problematic, it can lead to the opposite of the tragedy of the commons: the tragedy of the anti-commons. Anti-commons property occurs when multiple parties have an effective right to preclude others from using a given resource, and as a result no-one has an effective right of use. Part IV argues that this is precisely where the “cyberspace as place” metaphor leads. We are moving to a digital anticommons, where no-one will be allowed to access competitors’ cyberspace “assets” without licensing or other transactionally-expensive (or impossible) permission mechanism. The Article shows how the “cyberspace as place” metaphor leads to undesirable private control of the previously commons-like Internet, and the emergence of the digital anti-commons. As we all come to stake out our little claim in cyberspace, then the commons which is cyberspace is being destroyed.

The IKBALS project: Multi-modal reasoning in legal knowledge based systems

In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work integrates rule based and case based reasoning with intelligent information retrieval.When using the case based reasoning methodology, or in our case the specialisation of case based retrieval, we need to be aware of how to retrieve relevant experience. Our research, in the legal domain, specifies an approach to the retrieval problem which relies heavily on an extended object oriented/rule based system architecture that is supplemented with causal background information. We use a distributed agent architecture to help support the reasoning process of lawyers.Our approach to integrating rule based reasoning, case based reasoning and case based retrieval is contrasted to the CABARET and PROLEXS architectures which rely on a centralised blackboard architecture. We discuss in detail how our various cooperating agents interact, and provide examples of the system at work. The IKBALS system uses a specialised induction algorithm to induce rules from cases. These rules are then used as indices during the case based retrieval process.Because we aim to build legal support tools which can be modified to suit various domains rather than single purpose legal expert systems, we focus on principles behind developing legal knowledge based systems. The original domain chosen was theAccident Compensation Act 1989 (Victoria, Australia), which relates to the provision of benefits for employees injured at work. For various reasons, which are indicated in the paper, we changed our domain to that ofCredit Act 1984 (Victoria, Australia). This Act regulates the provision of loans by financial institutions.The rule based part of our system which provides advice on the Credit Act has been commercially developed in conjunction with a legal firm. We indicate how this work has lead to the development of a methodology for constructing rule based legal knowledge based systems. We explain the process of integrating this existing commercial rule based system with the case base reasoning and retrieval architecture.

Uncertain reasoning using maximum entropy inference

The use of maximum entropy inference in reasoning with uncertain information is commonly justified by an information-theoretic argument. This paper discusses a possible objection to this information-theoretic justification and shows how it can be met. I then compare maximum entropy inference with certain other currently popular methods for uncertain reasoning. In making such a comparison, one must distinguish between static and dynamic theories of degrees of belief: a static theory concerns the consistency conditions for degrees of belief at a given time; whereas a dynamic theory concerns how ones degrees of belief should change in. the light of new information. It is argued that maximum entropy is a dynamic theory and that a complete theory of uncertain reasoning can be gotten by combining maximum entropy inference with probability theory, which is a static theory. This total theory, I argue, is much better grounded than are other theories of uncertain reasoning.

Using Cases to Build Intelligent Decision Support Systems

Cases are an increasingly important aspect of experiential reasoning and form a large part of current research into the semantics of databases. Little work has been done in classifying types of cases and experience, and showing how cases change depending upon the context of their use. This paper sketches an initial classification of cases in legal domains, which we believe is of general use in database research methodology. The paper then examines two systems which demonstrate how cases can be used in semantically distinct ways.

The Credit Act Advisory System (CAAS): conversion from an expert system prototype to a C++ commercial system

CAAS is a rule-based expert system, which provides advice on the Victorial Credit Act 1984. It is currently in commercial use, and has been developed in conjunction with a law firm. It uses an object-oriented hybrid reasoning approach. The system was initially prototyped using the expert system shell NExpert Object, and was then converted into the C++ language. In this paper we describe the advantages that this methodology has, for both commercial and research development.

Beyond rule based reasoning-the meaning and use of cases

Commercial legal expert systems are invariably rule based. Such systems are poor at dealing with open texture and the argumentation inherent in law. To overcome these problems we suggest supplementing rule based legal expert systems with case based reasoning or neural networks. Both case based reasoners and neural networks use cases-but in very different ways. We discuss these differences at length. In particular we examine the role of explanation in existing expert systems methodologies. Because neural networks provide poor explanation facilities, we consider the use of Toulmin argument structures to support explanation (S. Toulmin, 1958). We illustrate our ideas with regard to a number of systems built by the authors.<<ETX>>

Deductive, inductive and analogical reasoning in legal decision support systems

In this paper we provide an overview of a number of fundamental reasoning formalisms in artificial intelligence which can and have been used in modelling legal reasoning. We describe deduction, induction and analogical reasoning formalisms, and show how they can be used separately to model legal reasoning. We argue that these formalisms can be used together to model legal reasoning more accurately, and describe a number of attempts to integrate the approaches.

Designing intelligent litigation support tools : The IKBALS perspective

In the legal domain, it is rare to find solutions to problems by simply applying algorithms or invoking deductive rules in some knowledge‐based program. Instead, expert practitioners often supplement domain‐specific knowledge with field experience. This type of expertise is often applied in the form of an analogy. This research proposes to combine both reasoning with precedents and reasoning with statutes and regulations in a way that will enhance the statutory interpretation task. This is being attempted through the integration of database and expert system technologies. Case‐based reasoning is being used to model legal precedents while rule‐based reasoning modules are being used to model the legislation and other types of causal knowledge. It is hoped to generalise these findings and to develop a formal methodology for integrating case‐based databases with rule‐based expert systems in the legal domain.

Non-monotonic reasoning and the reversibility of belief change

Traditional approaches to nonmonotonic reasoning fail to satisfy a number of plausible axioms for belief revision and suffer from conceptual difficulties as well. Recent work on ranked preferential models (RPMs) promises to overcome some of these difficulties. Here we show that RPMs are not adequate to handle iterated belief change. Specifically, we show that RPMs do not always allow for the reversibility of belief change. This result indicates the need for numerical strengths of belief.

Blockchains, Orphan Works, and the Public Domain

This Article outlines a blockchain based system to solve the orphan works problem. Orphan works are works still ostensibly protected by copyright for which an author cannot be found. Orphan works represent a significant problem for the efficient dissemination of knowledge, since users cannot license the works, and as a result may choose not to use them. Our proposal uses a blockchain to register attempts to find the authors of orphan works, and otherwise to facilitate use of those works. There are three elements to our proposal. First, we propose a number of mechanisms, including automated systems, to perform a diligent search for a rights holder. Second, we propose a blockchain register where every search for a work’s owner can be recorded. Third, we propose a legal mechanism that delivers works into orphanhood, and affords a right to use those works after a search for a rights holder is deemed diligent. These changes would provide any user of an orphan work with an assurance that they were acting legally as long as they had consulted the register and/or performed a diligent search for the work’s owner. The Article demonstrates a range of complementary legal and technological architectures that, in various formations, can be deployed to address the orphan works problem. We show that these technological systems are useful for enhancement of the public domain more generally, through the existence of a growing registry of gray status works and clarified conditions for their use. The selection and design of any particular implementation is a choice for policy makers and technologists. Rather than specify how that choice should look, the goal here is to demonstrate the utility of the technology and to clarify and promote its role in reforming this vexed area of law.