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As WTO members increasingly invoke security exceptions and the first panel report insofar was issued in Russia-Traffic in Transit, the methodical and procedural preliminaries of their adjudication must be reassessed. The preliminaries pertain to justiciability and to the proper interpretive approach for their vague terms that seemingly imply considerable discretion to WTO members, all the more as general exceptions are subject to expansive interpretation. Reading security exceptions expansively appears not viable as they miss the usual safeguard against abuse (i.e. the chapeau of Arts XX GATT/XIV GATS). This lack of safeguards rather suggests caution in conceptualising them expansively, as do the systemic consequences of recent attempts to re-politicise security exceptions which run the risk of nullifying the concept of multilateral trade regulation altogether. Furthermore, the appropriate standards of review and proof must be explored which have to strike a balance between control and deference in national security.
Artificial Intelligence (“AI”) is already being employed to make critical legal decisions in many countries all over the world. The use of AI in decision-making is a widely debated issue due to allegations of bias, opacity, and lack of accountability. For many, algorithmic decision-making seems obscure, inscrutable, or virtually dystopic. Like in Kafka’s The Trial, the decision-makers are anonymous and cannot be challenged in a discursive manner. This article addresses the question of how AI technology can be used for legal decisionmaking and decision-support without appearing Kafkaesque.
First, two types of machine learning algorithms are outlined: both Decision Trees and Artificial Neural Networks are commonly used in decision-making software. The real-world use of those technologies is shown on a few examples. Three types of use-cases are identified, depending on how directly humans are influenced by the decision. To establish criteria for evaluating the use of AI in decision-making, machine ethics, the theory of procedural justice, the rule of law, and the principles of due process are consulted. Subsequently, transparency, fairness, accountability, the right to be heard and the right to notice, as well as dignity and respect are discussed. Furthermore, possible safeguards and potential solutions to tackle existing problems are presented. In conclusion, AI rendering decisions on humans does not have to be Kafkaesque. Many solutions and approaches offer possibilities to not only ameliorate the downsides of current AI technologies, but to enrich and enhance the legal system.
National immigration policies increasingly meet with fierce political resistance from lower levels of government, in particular municipalities. Amongst industrialized countries, the USA and Germany are probably the most extreme examples. In the USA, a growing numbers of subnational entities, including some of the country’s largest cities, openly refuse to cooperate with federal immigration authorities. In retaliation, the Trump administrations has threatened several of these so-called ‘sanctuary cities’ to claim back past and to withdraw further federal funding from a number of jointly funded programs. Several court cases in this matter are pending. In stark contrast, an increasing number of German municipalities – labelled by the author as ‘non-sanctuary cities’ - have sought from their respective state governments a formal limitation of migration inflows into their territory, citing an overload on critical local administrative and not least housing resources. This paper contributes to the pertinent literature on multi-level governance in the area of immigration, first, by applying the economic theory of fiscal federalism to identify the theoretically appropriate level of government for defining and enforcing immigration policy. Second, the phenomenon of ‘sanctuary cities’ vs. ‘non-sanctuary cities’ and their potential impact on the design and enforcement of national immigration policies will be analyzed.