This Policy Brief examines the existing data protection regime both in Nigeria and globally and suggests ways to improve the data protection efforts in Nigeria. It considers Nigeria’s principal data protection laws, generally applicable across all sectors (including public and private institutions). By examining and juxtaposing some of the exemptions in legislation, an opportunity for abuse of data subjects’ rights may have been inadvertently created by laws that were enacted to do otherwise. This Policy Brief proffers preferable outcomes that may guide engagement with policymakers to rectify this situation.
Category: Jake Okechukwu Effoduh, L.L.B.
Jake Okechukwu Effoduh, LLB
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Unveiling AI Concerns for Sub-Saharan Africa and its Vulnerable Groups
In Sub-Saharan Africa (SSA), artificial intelligence is still in its early stages of adoption. To ensure that the already existing class imbalance in SSA communities does not hinder the realization of the Sustainable Development Goals, such as data security, safety, and equitable access to AI technologies, acceptable reliability measures must be put in place (as policies). This paper identifies some of the vulnerabilities in AI and adds a voice to the risks and ethical concerns surrounding the use of AI and its impact on SSA and its vulnerable groups. Our systematic literature review of related research between January 2014 and June 2024 shows the current state of AI adoption in SSA and the socio-political challenges that impact its development, revealing key concerns in data Governance, safety privacy, educational and skill gaps, socioeconomic impacts, and stakeholder influence on AI adoption in SSA. We propose a framework for designing data governance policies for the inclusive use of AI in SSA.
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Book Review: Litigating Artificial Intelligence by Jesse Beatson, Gerold Chan, and Jill R. Presser
It is no longer news that artificial intelligence (AI) is being deployed across the board in the legal industry, although the extent of AI use varies by jurisdiction.
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Leveraging responsible, explainable, and local artificial intelligence solutions for clinical public health in the Global South
In the present paper, we will explore how artificial intelligence (AI) and big data analytics (BDA) can help address clinical public and global health needs in the Global South, leveraging and capitalizing on our experience with the “Africa-Canada Artificial Intelligence and Data Innovation Consortium” (ACADIC) Project in the Global South, and focusing on the ethical and regulatory challenges we had to face. “Clinical public health” can be defined as an interdisciplinary field, at the intersection of clinical medicine and public health, whilst “clinical global health” is the practice of clinical public health with a special focus on health issue management in resource-limited settings and contexts, including the Global South. As such, clinical public and global health represent vital approaches, instrumental in (i) applying a community/population perspective to clinical practice as well as a clinical lens to community/population health, (ii) identifying health needs both at the individual and community/population levels, (iii) systematically addressing the determinants of health, including the social and structural ones, (iv) reaching the goals of population’s health and well-being, especially of socially vulnerable, underserved communities, (v) better coordinating and integrating the delivery of healthcare provisions, (vi) strengthening health promotion, health protection, and health equity, and (vii) closing gender inequality and other (ethnic and socio-economic) disparities and gaps. Clinical public and global health are called to respond to the more pressing healthcare needs and challenges of our contemporary society, for which AI and BDA can help unlock new options and perspectives. In the aftermath of the still ongoing COVID-19 pandemic, the future trend of AI and BDA in the healthcare field will be devoted to building a more healthy, resilient society, able to face several challenges arising from globally networked hyper-risks, including ageing, multimorbidity, chronic disease accumulation, and climate change.
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Artificial intelligence, law, and vulnerabilities
Social vulnerability is a measurement of the ability of communities to adequately respond to external stresses (Blaikie et al., 1994), such as the ongoing “SARS-CoV-2” – Severe Acute Respiratory Syndrome Coronavirus 2 (Bankoff & Hilhorst, 2004). During these periods of upheaval, people with disabilities, racial, ethnic, and religious minorities, children from low-income families, the elderly, migrants and refugees, the immunocompromised and those with chronic health conditions, and the homeless among others are considered to be at greater risk from the adverse effects, and potential losses incurred by these external stressors. They are also the slowest to recover from such emergencies. For example, recent data from the COVID-19 pandemic shows that vulnerable populations were much more likely to contract the virus, were less likely to receive the vaccine because of hesitancy and distrust of “Big Pharma”, yet they were more in need of social assistance compared to other segments of society (Cheong et al., 2021; Kazemi et al., 2022; St‐Denis, 2020). Classified as “socially vulnerable” by the United Nations (n.d.), these populations are almost always economically marginalized, politically under-represented, and socially underserved. (Un)surprisingly, they are predominantly racialized (Black and other people of color), and have a long history of enduring violations of their civil rights and freedoms, even during disaster response and recovery efforts. The factors and/or characteristics that determine the social vulnerability of a group differ from country to country, however, there are some universal similarities. Risk factors that contribute to the vulnerability of these groups include poverty, unemployment, and lack of access to resources (e.g., adequate healthcare, education, housing, safe drinking water, transportation, and other social services) (Cutter et al., 2003). Socially vulnerable populations are also stigmatized and discriminated against by the wider society, and even criminalized in law, policy, and practice. Forced to live in environments of severe inequality, they are unable to thrive, feel safe, and actively participate in all aspects of society (UNDP, n.d.). When compared to the general population, the capacity of socially vulnerable groups to cope with, respond to, and recover from the adverse impacts of crises is hindered by the inordinate obstacles they encounter in their daily lives (Wisner et al., 2004). These obstacles are indicators of structural inequities and barriers that hamper fair and equitable access (for all) to the resources needed to satisfy one’s basic needs. Social vulnerability is then a combination of the risk factors and socio-cultural markers listed above, which hinder full participation in economic, social, political, and cultural life (UN DESA, 2016). The amplification of existing inequities during crises like the COVID-19 pandemic has re-ignited discussions about global inequities and the challenges they present to socially vulnerable populations.