It is the objective of this article to review the existing literature and to address theoretical deficits in the study of policy convergence. First, we briefly present the central indicators we apply for the assessment of policy convergence. In a second step, we identify and compare different causal mechanisms of crossnational policy convergence. Having elaborated on the major causes of policy convergence, however, we still know little about the conditions under which these factors actually lead to convergence. This is the central objective of the third part of our analysis, in which we develop theoretical expectations on different indicators of cross-national policy convergence.

Background This paper aims to move the debate forward regarding the potential for artificial intelligence (AI) and autonomous robotic surgery with a particular focus on ethics, regulation and legal aspects (such as civil law, international law, tort law, liability, medical malpractice, privacy and product/device legislation, among other aspects). Methods We conducted an intensive literature search on current or emerging AI and autonomous technologies (eg, vehicles), military and medical technologies (eg, surgical robots), relevant frameworks and standards, cyber security/safety‐ and legal‐systems worldwide. We provide a discussion on unique challenges for robotic surgery faced by proposals made for AI more generally (eg, Explainable AI) and machine learning more specifically (eg, black box), as well as recommendations for developing and improving relevant frameworks or standards. Conclusion We classify responsibility into the following: (1) Accountability; (2) Liability; and (3) Culpability. All three aspects were addressed when discussing responsibility for AI and autonomous surgical robots, be these civil or military patients (however, these aspects may require revision in cases where robots become citizens). The component which produces the least clarity is Culpability, since it is unthinkable in the current state of technology. We envision that in the near future a surgical robot can learn and perform routine operative tasks that can then be supervised by a human surgeon. This represents a surgical parallel to autonomously driven vehicles. Here a human remains in the ‘driving seat’ as a ‘doctor‐in‐the‐loop’ thereby safeguarding patients undergoing operations that are supported by surgical machines with autonomous capabilities.

Differentiated integration has been the subjecc of political discussion and academic thought for a long time. Ir has also become an important feature of European integration since the 1990s. By contrast, it is astonishing how poor our research and knowledge about the phenomenon iso Whereas there is an abundance of conceptual work and some normative analysis, positive theories on the causes or effects of differentiated integration are rare. Empirical analysis has concentrated on a few important cases of treaty law (such as EMU and Schengen) while there is no systematic knowledge about differentiated integration in secondary law. The aim of this article is therefore twofold: to review the existing typological and theory-oriented research and to outline a research agenda striving for systematic empirical and explanatory knowledge. KEY WORDS Differentiated integration; European integration; flexible integration.

In recent years, there is growing interest in the study of cross-national policy convergence+ Yet we still have a limited understanding of the phenomenon: Do we observe convergence of policies at all? Under which conditions can we expect that domestic policies converge or rather develop further apart? In this article, we address this research deficit+ From a theoretical perspective, we concentrate on the explanatory power of three factors, namely international harmonization, transnational communication, and regulatory competition+ In empirical terms, we analyze if and to what extent we can observe convergence of environmental policies across twenty-four industrialized countries between 1970 and 2000+ We find an impressive degree of environmental policy convergence between the countries under investigation+ This development is mainly caused by international harmonization and, to a considerable degree, also by transnational communication, whereas regulatory competition does not seem to play a role+ It became obvious with the fourth report of the Intergovernmental Panel on Climate Change 1 in spring 2007 that the need to combat climate change and to deal with its consequences is one of the world's most pressing problems+ Because the human contribution to climate change is related to a broad range of activities, such as energy use and production, transport, industrial and agrarian production, and tropical deforestation, combating it-through the reduction of greenhouse gas emissions-is not only costly but also requires profound behavioral changes+ Moreover, the global nature of the climate problem underlines the need for inter-

their un-debuggability, and their inability to "explain" their decisions in a human understandable and reconstructable way. So while AlphaGo or DeepStack can crush the best humans at Go or Poker, neither program has any internal model of its task; its representations defy interpretation by humans, there is no mechanism to explain their actions and behaviour, and furthermore, there is no obvious instructional value. .. the high performance systems can not help humans improve. Even when we understand the underlying mathematical scaffolding of current machine learning architectures, it is often impossible to get insight into the internal working of the models; we need explicit modeling and reasoning tools to explain how and why a result was achieved. We also know that a significant challenge for future AI is contextual adaptation, i.e., systems that incrementally help to construct explanatory models for solving real-world problems. Here it would be beneficial not to exclude human expertise, but to augment human intelligence with artificial intelligence.