Southern actors and the governance of labour standards in global production networks: The case of South African fruit and wine

Recent studies highlight the emergence of standards, including multi-stakeholder initiatives developed and applied within the global South where supplier firms are usually based. This trend has created a complex ethical terrain whereby transnational standards flow through global production networks and intersect with domestic initiatives at places of production. The paper complements global production network analysis with the concepts of ‘space of flows’ and ‘space of places’ and insights from relational economic geography, to examine how some multi-stakeholder initiatives in the global South can shape the broader governance of labour standards in global production networks. The following questions are addressed: How is the governance of labour standards in global production networks shaped by dynamic spatial interactions between actors? What role have diverse Southern multi-stakeholder initiatives played in influencing the governance of South African fruit and wine? We draw on research conducted over seven years into two standards in South Africa, the Wine and Agriculture Ethical Trade Association and Sustainability Initiative of South Africa. Our analysis shows that these two Southern-based multi-stakeholder initiatives contributed to shaping the broader governance of labour standards through dynamic non-linear waves of interaction over time, involving both collaborative and contested exchanges between actors across space of flows and places. We further argue that despite the development of multi-stakeholder initiatives by Southern actors, commercial power asymmetries in global production networks limit their ability to promote significant improvements for producers and workers.

The Ethics of Consent in a Shifting Genomic Ecosystem

The collection and use of human genetic data raise important ethical questions about how to balance individual autonomy and privacy with the potential for public good. The proliferation of local, national, and international efforts to collect genetic data and create linkages to support large-scale initiatives in precision medicine and the learning health system creates new demands for broad data sharing that involve managing competing interests and careful consideration of what constitutes appropriate ethical trade-offs. This review describes these emerging ethical issues with a focus on approaches to consent and issues related to justice in the shifting genomic research ecosystem.

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.

Covid-19: A Trade-off between Political Economy and Ethics

This paper investigates the trade-off between economics and ethics applying them to “lockdowns” as a policy measure to counter the Covid-19-pandemic. This is an academic research on the nature and mechanism of trade-offs in so far as they apply to decision making. In the course of the line of inquiry pursued here, several different ways of trading off are assessed. In applying them to the pandemics, each yield a different answer to the adequacy of lockdowns as measures against the pandemic. The economic trade-off found “optimalcy” conditions, the utilitarian-ethical trade-off failed to do so revealing that there is a problem using “scientific evidence” as basis for such a trade-off. The value-ethical trade-off found out that lockdowns do not pass the test of proportionality within the usual constitutional framework.

Choice and Trade-offs: Parent Decision Making for Neurotechnologies for Pediatric Drug-Resistant Epilepsy

This qualitative study investigated factors that guide caregiver decision making and ethical trade-offs for advanced neurotechnologies used to treat children with drug-resistant epilepsy. Caregivers with affected children were recruited to semi-structured focus groups or interviews at one of 4 major epilepsy centers in Eastern and Western Canada and the USA (n = 22). Discussions were transcribed and qualitative analytic methods applied to examine values and priorities (eg, risks, benefits, adherence, invasiveness, reversibility) of caregivers pertaining to novel technologies to treat drug-resistant epilepsy. Discussions revealed 3 major thematic branches for decision making: (1) features of the intervention—risks and benefits, with an emphasis on an aversion to perceived invasiveness; (2) decision drivers—trust in the clinical team, treatment costs; and (3) quality of available information about neurotechnological options. Overall, caregivers’ definition of treatment success is more expansive than seizure freedom. The full involvement of their values and priorities must be considered in the decision-making process.

Choosing how to discriminate: navigating ethical trade-offs in fair algorithmic design for the insurance sector

Here, we provide an ethical analysis of discrimination in private insurance to guide the application of non-discriminatory algorithms for risk prediction in the insurance context. This addresses the need for ethical guidance of data-science experts, business managers, and regulators, proposing a framework of moral reasoning behind the choice of fairness goals for prediction-based decisions in the insurance domain. The reference to private insurance as a business practice is essential in our approach, because the consequences of discrimination and predictive inaccuracy in underwriting are different from those of using predictive algorithms in other sectors (e.g., medical diagnosis, sentencing). Here we focus on the trade-off in the extent to which one can pursue indirect non-discrimination versus predictive accuracy. The moral assessment of this trade-off is related to the context of application—to the consequences of inaccurate risk predictions in the insurance domain.

Marks & Spencer

The case of Marks & Spencer illustrates how a company has used a sustainability scorecard that awards provisional, bronze, silver, and gold ratings to participating suppliers to promote its sustainability programme. The scores are based on environment, human resources and ethical trade, and lean manufacturing. Suppliers undertake self-assessments of the scorecard at least once a year, which are subject to audit and assurance. The programme has delivered substantial savings through waste reduction and environmental efficiency amounting to over £600 million since 2007.