How much of commonsense and legal reasoning is formalizable? A review of conceptual obstacles

Fifty years of effort in artificial intelligence (AI) and the formalization of legal reasoning have produced both successes and failures. Considerable success in organizing and displaying evidence and its interrelationships has been accompanied by failure to achieve the original ambition of AI as applied to law: fully automated legal decision-making. The obstacles to formalizing legal reasoning have proved to be the same ones that make the formalization of commonsense reasoning so difficult, and are most evident where legal reasoning has to meld with the vast web of ordinary human knowledge of the world. Underlying many of the problems is the mismatch between the discreteness of symbol manipulation and the continuous nature of imprecise natural language, of degrees of similarity and analogy, and of probabilities

Legal Fictions and the Essence of Robots: Thoughts on Essentialism and Pragmatism in the Regulation of Robotics

The purpose of this paper is to offer some critical remarks on the so-called pragmatist approach to the regulation of robotics. To this end, the article mainly reviews the work of Jack Balkin and Joanna Bryson, who have taken up such ap- proach with interestingly similar outcomes. Moreover, special attention will be paid to the discussion concerning the legal fiction of ‘electronic personality’. This will help shed light on the opposition between essentialist and pragmatist methodologies. After a brief introduction (1.), in 2. I introduce the main points of the methodological debate which opposes pragmatism and essentialism in the regulation of robotics and I examine how legal fictions are framed from a pragmatist, functional perspective. Since this approach entails a neat separation of ontological analysis and legal rea- soning, in 3. I discuss whether considerations on robots’ essence are actually put into brackets when the pragmatist approach is endorsed. Finally, in 4. I address the problem of the social valence of legal fictions in order to suggest a possible limit of the pragmatist approach. My conclusion (5.) is that in the specific case of regulating robotics it may be very difficult to separate ontological considerations from legal reasoning—and vice versa—both on an epistemological and social level. This calls for great caution in the recourse to anthropomorphic legal fictions

Designing Normative Theories for Ethical and Legal Reasoning: LogiKEy Framework, Methodology, and Tool Support

A framework and methodology---termed LogiKEy---for the design and engineering of ethical reasoners, normative theories and deontic logics is presented. The overall motivation is the development of suitable means for the control and governance of intelligent autonomous systems. LogiKEy's unifying formal framework is based on semantical embeddings of deontic logics, logic combinations and ethico-legal domain theories in expressive classic higher-order logic (HOL). This meta-logical approach enables the provision of powerful tool support in LogiKEy: off-the-shelf theorem provers and model finders for HOL are assisting the LogiKEy designer of ethical intelligent agents to flexibly experiment with underlying logics and their combinations, with ethico-legal domain theories, and with concrete examples---all at the same time. Continuous improvements of these off-the-shelf provers, without further ado, leverage the reasoning performance in LogiKEy. Case studies, in which the LogiKEy framework and methodology has been applied and tested, give evidence that HOL's undecidability often does not hinder efficient experimentation.Comment: 50 pages; 10 figure

Chief Justice Robots

Say an AI program someday passes a Turing test, because it can con-verse in a way indistinguishable from a human. And say that its develop-ers can then teach it to converse—and even present an extended persua-sive argument—in a way indistinguishable from the sort of human we call a “lawyer.” The program could thus become an AI brief-writer, ca-pable of regularly winning brief-writing competitions against human lawyers. Once that happens (if it ever happens), this Essay argues, the same technology can be used to create AI judges, judges that we should accept as no less reliable (and more cost-effective) than human judges. If the software can create persuasive opinions, capable of regularly winning opinion-writing competitions against human judges—and if it can be adequately protected against hacking and similar attacks—we should in principle accept it as a judge, even if the opinions do not stem from human judgment

A Logic Programming Approach to Knowledge-State Planning: Semantics and Complexity

We propose a new declarative planning language, called K, which is based on principles and methods of logic programming. In this language, transitions between states of knowledge can be described, rather than transitions between completely described states of the world, which makes the language well-suited for planning under incomplete knowledge. Furthermore, it enables the use of default principles in the planning process by supporting negation as failure. Nonetheless, K also supports the representation of transitions between states of the world (i.e., states of complete knowledge) as a special case, which shows that the language is very flexible. As we demonstrate on particular examples, the use of knowledge states may allow for a natural and compact problem representation. We then provide a thorough analysis of the computational complexity of K, and consider different planning problems, including standard planning and secure planning (also known as conformant planning) problems. We show that these problems have different complexities under various restrictions, ranging from NP to NEXPTIME in the propositional case. Our results form the theoretical basis for the DLV^K system, which implements the language K on top of the DLV logic programming system.Comment: 48 pages, appeared as a Technical Report at KBS of the Vienna University of Technology, see http://www.kr.tuwien.ac.at/research/reports