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118 results on '"Möslein, Florian"'

102. Compliance with ECJ judgments vs. compatibility with EU law -- Free movement of capital issues unresolved after the second ruling on the Volkswagen law: Commission v. Germany.

Author

Möslein, Florian

Subjects
CAPITAL, ACTIONS & defenses (Law)
Abstract

The article discusses the European Court of Justice (ECJ) case Commission v. Germany on the free movement of capital issues. The European Commission claimed that the special rights mentioned in the case violate the free movement of capital. Advocate General Nils Wahl considered the complaint relating to the Article of Association of carmaker Volkswagen inadmissible. The court eventually rejected the complaint as inadmissible.

Published
2015

106. CONTRACT GOVERNANCE WITHIN CORPORATE GOVERNANCE: A LESSON FROM THE GLOBAL FINANCIAL CRISIS.

Author

Möslein, Florian

Subjects
CORPORATE governance, GLOBAL Financial Crisis, 2008-2009, CONTRACTS -- Government policy
Abstract

The 2009 Nobel Prize for Economics was awarded to Elinor Ostrom and Oliver Williamson for their work on economic governance. Williamson once defined governance as "an effort to implement the 'study of good order and workable arrangements', where good order includes both spontaneous order in the market [...] and intentional order." Even though corporate governance has been studied quite well over the last decades, the global financial crisis revealed important weaknesses in governance mechanisms. Yet this crisis did not primarily emerge due to specific corporate structures, but rather had its roots in the instability of markets. Hence the study of good order and workable arrangements needs to take markets into account as well. Contract governance is an important lesson of the recent crisis. By this token, the destruction of financial values might create a legal innovation, posing new challenges not only for regulators and legal academics, but also for management practice. Contract governance provides an important link between the corporation and its contractual environment. By virtue of this link, contract governance can contribute to avoid future crises and make the system of market economy more stable in the long run. [ABSTRACT FROM AUTHOR]

Published
2011

108. Die Trennung von Wertpapier- und sonstigem Bankgeschäft: Trennbankensystem, ring-fencing und Volcker-Rule als Mittel zur Eindämmung systemischer Gefahren für das Finanzsystem / The seperation of investment and commercial banking: Dual banking system, ring-fencing and Volcker rule as means to reduce systemic risk for the financial system

Author

Möslein, Florian

Abstract

Die Trennung von Wertpapier- und sonstigem Bankgeschäft hatte vor allem in den USA eine lange Tradition. Seit der globalen Finanzkrise werden entsprechende Vorgaben jedoch weltweit, nunmehr allerdings in veränderten Gestaltungsvarianten rechtspolitisch diskutiert; der deutsche Gesetzgeber hat ihre Einführung kürzlich bereits beschlossen. Während zur Begründung traditionell vor allem institutsbezogene Erwägungen angeführt wurden, sind seit der Finanzkrise Fragen der Systemstabilität in den Vordergrund gerückt. Allerdings ist keineswegs erwiesen, dass die Einführung eines Trennbankenregimes Systemrisiken zu reduzieren vermag. Zudem beschränkt ein solches Regime die institutionelle Vielfalt und droht deshalb, selbst destabilisierend zu wirken. Die Gestaltungsvarianten, die als Alternativen zum klassischen Trennbankensystem diskutiert werden, können diese Bedenken nicht zerstreuen. Eine Aktivitätsbeschränkung nach dem Vorbild der US-amerikanischen Volcker Regel wirft erhebliche Abgrenzungsprobleme auf und lässt überdies eine Zunahme unregulierter Schattenbanken befürchten. Die konzerninterne Spartentrennung, wie sie auf europäischer Ebene sowie in Großbritannien und Deutschland geplant bzw. beschlossen ist, bietet ebenfalls keine aussichtsreiche Handhabe gegen ein Übergreifen systemischer Risiken. Einerseits stehen einzelne Konzerngesellschaften nach geltendem Unternehmensrecht keineswegs völlig unverbunden nebeneinander, sondern befinden sich in einem Konzernverbund; andererseits droht das Anlegervertrauen in den Gesamtkonzern selbst bei Schieflage nur einzelner Sparten erschüttert zu werden. Insgesamt überwiegen daher die Bedenken gegen strukturelle Trennbankenregeln, die maximalinvasiv in gewachsene Bankenstrukturen eingreifen, zugleich aber hochkomplex sind und deshalb sowohl Umgehungsgefahren als auch Risiken nicht intendierter Nebenwirkungen bergen. Als Alternative bietet sich indessen eine anreizorientierte, zielgenauere Regulierung von Wertpapierhandelsgeschäften an.

Published
2013
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112. On Assessing Trustworthy AI in Healthcare. Machine Learning as a Supportive Tool to Recognize Cardiac Arrest in Emergency Calls

Author

Zicari, Roberto V, Brusseau, James, Blomberg, Stig Nikolaj, Christensen, Helle Collatz, Coffee, Megan, Ganapini, Marianna B, Gerke, Sara, Gilbert, Thomas Krendl, Hickman, Eleanore, Hildt, Elisabeth, Holm, Sune, Kühne, Ulrich, Madai, Vince I, Osika, Walter, Spezzatti, Andy, Schnebel, Eberhard, Tithi, Jesmin Jahan, Vetter, Dennis, Westerlund, Magnus, Wurth, Renee, Amann, Julia, Antun, Vegard, Beretta, Valentina, Bruneault, Frédérick, Campano, Erik, Düdder, Boris, Gallucci, Alessio, Goffi, Emmanuel, Haase, Christoffer Bjerre, Hagendorff, Thilo, Kringen, Pedro, Möslein, Florian, Ottenheimer, Davi, Ozols, Matiss, Palazzani, Laura, Petrin, Martin, Tafur, Karin, Tørresen, Jim, Volland, Holger, and Kararigas, Georgios

Subjects
ComputingMethodologies_PATTERNRECOGNITION, 46 Information and Computing Sciences, 8.3 Policy, ethics, and research governance, 42 Health Sciences, 3 Good Health and Well Being, 8 Health and social care services research, 4203 Health Services and Systems, Cardiovascular, GeneralLiterature_MISCELLANEOUS, 3. Good health
Abstract

Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and other services that advance population health and wellbeing. However, the use of AI in healthcare also brings potential risks that may cause unintended harm. To guide future developments in AI, the High-Level Expert Group on AI set up by the European Commission (EC), recently published ethics guidelines for what it terms “trustworthy” AI. These guidelines are aimed at a variety of stakeholders, especially guiding practitioners toward more ethical and more robust applications of AI. In line with efforts of the EC, AI ethics scholarship focuses increasingly on converting abstract principles into actionable recommendations. However, the interpretation, relevance, and implementation of trustworthy AI depend on the domain and the context in which the AI system is used. The main contribution of this paper is to demonstrate how to use the general AI HLEG trustworthy AI guidelines in practice in the healthcare domain. To this end, we present a best practice of assessing the use of machine learning as a supportive tool to recognize cardiac arrest in emergency calls. The AI system under assessment is currently in use in the city of Copenhagen in Denmark. The assessment is accomplished by an independent team composed of philosophers, policy makers, social scientists, technical, legal, and medical experts. By leveraging an interdisciplinary team, we aim to expose the complex trade-offs and the necessity for such thorough human review when tackling socio-technical applications of AI in healthcare. For the assessment, we use a process to assess trustworthy AI, called 1Z-Inspection® to identify specific challenges and potential ethical trade-offs when we consider AI in practice.

113. On Assessing Trustworthy AI in Healthcare: Machine Learning as a Supportive Tool to Recognize Cardiac Arrest in Emergency Calls

Author

Zicari, Roberto V., Brusseau, James, Blomberg, Stig N., Collatz Christensen, Helle, Coffee, Megan, Ganapini, Marianna B., Gerke, Sara, Krendl Gilbert, Thomas, Hickman, Eleanore, Hildt, Elisabeth, Holm, Sune, Kühne, Ulrich, Madai, Vince I., Osika, Walter, Spezzatti, Andy, Schnebel, Eberhard, Tithi, Jesmin J., Vetter, Dennis, Westerlund, Magnus, Wurth, Renee, Amann, Julia, Vegard, Antun, Beretta, Valentina, Bruneault, Frédérick, Campano, Erik, Düdder, Boris, Gallucci, Alessio, Goffi, Emmanuel, Haase, Christoffer B., Hagendorff, Thilo, Kringen, Pedro, Möslein, Florian, Ottenheimer, Davi, Ozols, Matiss, Palazzani, Laura, Petrin, Martin, Tafur, Karin, Tørresen, Jim, Volland, Holger, and Kararigas, Georgios

Subjects
Artificial intelligence, ComputingMethodologies_PATTERNRECOGNITION, Ethical trade-off, Case study, Explainable AI, Healthcare, Cardiac arrest, Trust, GeneralLiterature_MISCELLANEOUS, Trustworthy AI, 3. Good health
Abstract

Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and other services that advance population health and wellbeing. However, the use of AI in healthcare also brings potential risks that may cause unintended harm. To guide future developments in AI, the High-Level Expert Group on AI set up by the European Commission (EC), recently published ethics guidelines for what it terms “trustworthy” AI. These guidelines are aimed at a variety of stakeholders, especially guiding practitioners toward more ethical and more robust applications of AI. In line with efforts of the EC, AI ethics scholarship focuses increasingly on converting abstract principles into actionable recommendations. However, the interpretation, relevance, and implementation of trustworthy AI depend on the domain and the context in which the AI system is used. The main contribution of this paper is to demonstrate how to use the general AI HLEG trustworthy AI guidelines in practice in the healthcare domain. To this end, we present a best practice of assessing the use of machine learning as a supportive tool to recognize cardiac arrest in emergency calls. The AI system under assessment is currently in use in the city of Copenhagen in Denmark. The assessment is accomplished by an independent team composed of philosophers, policy makers, social scientists, technical, legal, and medical experts. By leveraging an interdisciplinary team, we aim to expose the complex trade-offs and the necessity for such thorough human review when tackling socio-technical applications of AI in healthcare. For the assessment, we use a process to assess trustworthy AI, called 1Z-Inspection® to identify specific challenges and potential ethical trade-offs when we consider AI in practice., Frontiers in Human Dynamics, 3, ISSN:2673-2726

118. Kryptoaktien : Erweiterung des eWpG durch das Zukunftsfinanzierungsgesetz

Author

Möslein, Florian

Subjects
Law / Commercial, Law / Civil Law, Law / Comparative
Abstract

Der Sammelband enthält die Schriftfassung der Vorträge zur Tagung "Elektronische Aktien", die am 15. Mai 2023 in der Hessischen Landesvertretung in Berlin stattfand. Die Tagung wurde gemeinsam von der Projektgruppe "Tokenisierung und Finanzmarkt (ToFi)" des Zentrums verantwortungsbewusste Digitalisierung (ZEVEDI) und dem Institut für das Recht der Digitalisierung (IRDi) der Philipps-Universität Marburg anlässlich des Gesetzgebungsverfahrens zum Zukunftsfinanzierungsgesetz veranstaltet. Behandelt werden namentlich die gesetzgeberische Konzeption, der europäische und der techniksoziologische Kontext sowie das Gesellschafts-, Kapitalmarkt- und Wertpapierrecht der elektronischen Aktien.

Published
1970

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