Immigration Enforcement and Fairness to Would-Be Immigrants

This chapter argues that governments have a duty to take reasonably effective and humane steps to minimize the occurrence of unauthorized migration and stay. While the effects of unauthorized migration on a country’s citizens and institutions have been vigorously debated, the literature has largely ignored duties of fairness to would-be immigrants. It is argued here that failing to take reasonable steps to prevent unauthorized migration and stay is deeply unfair to would-be immigrants who are not in a position to bypass visa regulations. Importantly, the argument here is orthogonal to the debate as to how much and what kinds of immigration ought to be allowed

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

Explanation for case-based reasoning via abstract argumentation

Case-based reasoning (CBR) is extensively used in AI in support of several applications, to assess a new situation (or case) by recollecting past situations (or cases) and employing the ones most similar to the new situation to give the assessment. In this paper we study properties of a recently proposed method for CBR, based on instantiated Abstract Argumentation and referred to as AA-CBR, for problems where cases are represented by abstract factors and (positive or negative) outcomes, and an outcome for a new case, represented by abstract factors, needs to be established. In addition, we study properties of explanations in AA-CBR and define a new notion of lean explanations that utilize solely relevant cases. Both forms of explanations can be seen as dialogical processes between a proponent and an opponent, with the burden of proof falling on the proponent

Arbitration Revisited: Preemption of California’s Unconscionability Doctrine after Concepcion

This commentary looks at a Supreme Court case, Imburgia v. DIRECTV, in which the Court faces the question of whether an arbitration agreement, made pursuant to the Federal Arbitration Act, preempts state unconscionability doctrine which would render that agreement unenforceable. The Author argues that holding that federal law implementing a policy favoring arbitration fully preempts state law doctrines from preventing the enforcement of arbitration agreements