Diversity, merit and power in the c-suite of the FTSE100

This research seeks to contribute to the boardroom diversity debate by examining gender and ethnicity in the c-suite of the FTSE 100, both theoretically and empirically. The research considers the c-suite appointment process through the lens of UK Corporate Governance Code guidance to appoint on merit. From an empirical perspective, the research has two strands. Firstly, it gathers and analyses profile data on the FTSE 100 c-suite, for both 2016 and 2017. Secondly, with reference to the guidance of the Code, it analyses corporate diversity statistics in light of corporate diversity policies provided in the annual reports. Key findings of the research include support for the theory that homosocial reproduction among the FTSE 100 c-suite is still prevalent, and disadvantages women and ethnic minorities. The findings suggest there are higher barriers to c-suite entry, particularly for women. Analysis of annual reports suggests that the majority of the FTSE100 have managerialised the meaning of diversity and most appointment policies create little to no obligation to genuinely consider diversity. The research argues that it is a mis-use of the merit concept and the distribution of power that is perpetuating the c-suite’s lack of diversity

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

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.</jats:p

Co-Design of a Trustworthy AI System in Healthcare: Deep Learning Based Skin Lesion Classifier

This paper documents how an ethically aligned co-design methodology ensures trustworthiness in the early design phase of an artificial intelligence (AI) system component for healthcare. The system explains decisions made by deep learning networks analyzing images of skin lesions. The co-design of trustworthy AI developed here used a holistic approach rather than a static ethical checklist and required a multidisciplinary team of experts working with the AI designers and their managers. Ethical, legal, and technical issues potentially arising from the future use of the AI system were investigated. This paper is a first report on co-designing in the early design phase. Our results can also serve as guidance for other early-phase AI-similar tool developments.</jats:p

The Regulation of Corporate Governance in European Financial Market Infrastructures: A Critique

1This article is the first to consider the variations in governance requirements applicable to European financial market infrastructures. It charts the tangled combination of laws, codes and regulations that apply to the governance of the largest European central counterparties, central securities depositories, and international central securities depositories. Despite the similarity of these institutions in terms of their sector, criticality, complexity and purpose, there are substantive variations in what is required of their governance. Here we question whether this variance is an appropriate reflection of differing institutional needs or a by-product of piecemeal regulatory reform.Our research found no apparent need to regulate for consistency of board size or structure, nor in relation to specificities of committee requirements. However, there are convincing arguments that change is needed around the meaning and application of independence. The current approach to FMI directorial independence is a poor fit given the sectors highly technical nature, its interconnectedness, and the limited pool of available expertise. On top of this, expertise, diversity, and commitment can become trade-offs for adherence to the requirements of independence. We argue that regulation needs to be sensitively calibrated to ensure these important factors do not get squeezed out under the weight of formalized independence. It is our view that independence requirements can be structured to create better balanced boards where the needs of independence, expertise, diversity, and commitment can be weighed against each other in context.</jats:p