As neuroscience projects increase in scale and cross international borders, different ethical principles, national and international laws, regulations, and policies for data sharing must be considered. These concerns are part of what is collectively called data governance. Whereas neuroscience data transcend borders, data governance is typically constrained within geopolitical boundaries. An international data governance framework and accompanying infrastructure can assist investigators, institutions, data repositories, and funders with navigating disparate policies. Here, we propose principles and operational considerations for how data governance in neuroscience can be navigated at an international scale and highlight gaps, challenges, and opportunities in a global brain data ecosystem. We consider how to approach data governance in a way that balances data protection requirements and the need for open science, so as to promote international collaboration through federated constructs such as the International Brain Initiative (IBI). ll
Recent advances in Artificial Intelligence (AI) have led to intense debates about benefits and concerns associated with this powerful technology. These concerns and debates have similarities with developments in other emerging technologies characterized by prominent impacts and uncertainties. Against this background, this paper asks, What can AI governance, policy and ethics learn from other emerging technologies to address concerns and ensure that AI develops in a socially beneficial way? From recent literature on governance, policy and ethics of emerging technologies, six lessons are derived focusing on inclusive governance with balanced and transparent involvement of government, civil society and private sector; diverse roles of the state including mitigating risks, enabling public participation and mediating diverse interests; objectives of technology development prioritizing societal benefits; international collaboration supported by science diplomacy, as well as learning from computing ethics and Responsible Innovation.
The extensive disruption to and digital transformation of travel administration across borders largely due to COVID-19 mean that digital vaccine passports are being developed to resume international travel and kick-start the global economy. Currently, a wide range of actors are using a variety of different approaches and technologies to develop such a system. This paper considers the techno-ethical issues raised by the digital nature of vaccine passports and the application of leading-edge technologies such as blockchain in developing and deploying them. We briefly analyse four of the most advanced systems – IBM’s Digital Health Passport “Common Pass,” the International Air Transport Association’s Travel Pass, the Linux Foundation Public Health’s COVID-19 Credentials Initiative and the Vaccination Credential Initiative (Microsoft and Oracle) – and then consider the approach being taken for the EU Digital COVID Certificate. Each of these raises a range of issues, particularly relating to the General Data Protection Regulation (GDPR) and the need for standards and due diligence in the application of innovative technologies (eg blockchain) that will directly challenge policymakers when attempting to regulate within the network of networks.
Drawing on more than eight years working to implement Responsible Research and Innovation (RRI) in the Human Brain Project, a large EU-funded research project that brings together neuroscience, computing, social sciences, and the humanities, and one of the largest investments in RRI in one project, this article offers insights on RRI and explores its possible future. We focus on the question of how RRI can have long-lasting impact and persist beyond the time horizon of funded projects. For this purpose, we suggest the concept of 'responsibility by design' which is intended to encapsulate the idea of embedding RRI in research and innovation in a way that makes it part of the fabric of the resulting outcomes, in our case, a distributed European Research Infrastructure.
Neuroscience research is producing big brain data which informs both advancements in neuroscience research and drives the development of advanced datasets to provide advanced medical solutions. These brain data are produced under different jurisdictions in different formats and are governed under different regulations. The governance of data has become essential and critical resulting in the development of various governance structures to ensure that the quality, availability, findability, accessibility, usability, and utility of data is maintained. Furthermore, data governance is influenced by various ethical and legal principles. However, it is still not clear what ethical and legal principles should be used as a standard or baseline when managing brain data due to varying practices and evolving concepts. Therefore, this study asks what ethical and legal principles shape the current brain data governance landscape? A systematic scoping review and thematic analysis of articles focused on biomedical, neuro and brain data governance was carried out to identify the ethical and legal principles which shape the current brain data governance landscape. The results revealed that there is currently a large variation of how the principles are presented and discussions around the terms are very multidimensional. Some of the principles are still at their infancy and are barely visible. A range of principles emerged during the thematic analysis providing a potential list of principles which can provide a more comprehensive framework for brain data governance and a conceptual expansion of neuroethics.
In the last few years, a growing and thriving AI ecosystem has emerged in Africa. Within this ecosystem, there are local tech spaces as well as a number of internationally driven technology hubs and centres established by big tech companies such as Twitter, Google, Facebook, Alibaba Group, Huawei, Amazon and Microsoft have significantly increased the development and deployment of AI systems in Africa. While these tech spaces and hubs are focused on using AI to meet local challenges (e.g. poverty, illiteracy, famine, corruption, environmental disasters, terrorism and health crisis), the ethical, legal and socio-cultural implications of AI in Africa have largely been ignored. To ensure that Africans benefit from the attendant gains of AI, ethical, legal and socio-cultural impacts of AI need to be robustly considered and mitigated.
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