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This research examines the impact of digital neo-colonialism on the Global South and encourages the development of legal and economic incentives to protect Indigenous cultures globally. Data governance is discussed in an evolutionary…
As societal challenges grow more complex, access to data for public interest use is paradoxically becoming more constrained. This emerging data winter is not simply a matter of scarcity, but of shrinking legitimate and trusted pathways for…
Due to the emergence of data-driven technologies in Aotearoa New Zealand that use M\=aori data, there is a need for values-based frameworks to guide thinking around balancing the tension between the opportunities these create, and the…
To address the need for regulating digital technologies without hampering innovation or pre-digital transformation regulatory frameworks, we provide a model to evolve Data governance toward Information governance and precise the relation…
Data mining is an increasingly important technology for extracting useful knowledge hidden in large collections of data. There are, however, negative social perceptions about data mining, among which potential privacy violation and…
Data is essential to train and fine-tune today's frontier artificial intelligence (AI) models and to develop future ones. To date, academic, legal, and regulatory work has primarily addressed how data can directly harm consumers and…
Digitalization opens up new opportunities in the collection, analysis, and presentation of data which can contribute to the achievement of the 2030 Agenda and its Sustainable Development Goals (SDGs). In particular, the access to and…
The article presents a brief review of the Brazilian legislation that impacts indigenous communities' digital privacy rights through governmental data collection. Furthermore, the article aims to discuss the need to collect sensitive data…
The emergence of AI twins, digital replicas that encapsulate an individual's knowledge, memories, psychological traits, and behavioral patterns, raises novel legal and ethical challenges for data governance and personal identity. Built from…
The shift towards pluralism in global data ethics acknowledges the importance of including perspectives from the Global Majority to develop responsible data science practices that mitigate systemic harms in the current data science…
Data are essential in developing healthcare artificial intelligence (AI) systems. However, patient data collection, access, and use raise ethical concerns, including informed consent, data bias, data protection and privacy, data ownership,…
Data cooperatives offer a new model for fair data governance, enabling individuals to collectively control, manage, and benefit from their information while adhering to cooperative principles such as democratic member control, economic…
Genetic data collection has become ubiquitous, producing genetic information about health, ancestry, and social traits. However, unregulated use, especially amid evolving scientific understanding, poses serious privacy and discrimination…
Researchers find weaknesses in current strategies for protecting privacy in large datasets. Many anonymized datasets are reidentifiable, and norms for offering data subjects notice and consent over emphasize individual responsibility. Based…
As machine learning and data science applications grow ever more prevalent, there is an increased focus on data sharing and open data initiatives, particularly in the context of the African continent. Many argue that data sharing can…
The sharing of data and digital assets in a decentralized settling is associated with various legislative challenges, including, but not limited to, the need to adhere to legal requirements with respect to privacy (e.g. data protection…
In the current data driven era, synthetic data, artificially generated data that resembles the characteristics of real world data without containing actual personal information, is gaining prominence. This is due to its potential to…
Scientific data governance should prioritize maximizing the utility of data throughout the research lifecycle. Research software systems that enable analysis reproducibility inform data governance policies and assist administrators in…
Socio-economic data mining has a great potential in terms of gaining a better understanding of problems that our economy and society are facing, such as financial instability, shortages of resources, or conflicts. Without large-scale data…
This chapter seeks to frame the elemental and invisible problems of AI and big data in the African context by examining digital sites and infrastructure through the lens of power and interests. It will present reflections on how these sites…