Edmund Terem Ugar

Recently clinicians have become more reliant on technologies such as artificial intelligence (AI) and machine learning (ML) for effective and accurate diagnosis and prognosis of diseases, especially mental health disorders. These remarks, however, apply primarily to Europe, the USA, China and other technologically developed nations. Africa is yet to leverage the potential applications of AI and ML within the medical space. Sub-Saharan African countries are currently disadvantaged economically and infrastructure-wise. Yet precisely, these circumstances create significant opportunities for the deployment of medical AI, which has already been deployed in some places in the continent. However, while AI and ML have come with enormous promises in Africa, there are still challenges when it comes to successfully applying AI and ML designed elsewhere within the African context, especially in diagnosing mental health disorders. We argue, in this paper, that there ought not to be a homogeneous/generic design of AI and ML used in diagnosing mental health disorders. Our claim is grounded on the premise that mental health disorders cannot be diagnosed solely on ‘factual evidence’ but on both factual evidence and value-laden judgements of what constitutes mental health disorders in sub-Saharan Africa. For ML to play a successful role in diagnosing mental health disorders in sub-Saharan African medical spaces, with a precise focus on South Africa, we allude that it ought to understand what sub-Saharan Africans consider as mental health disorders, that is, the value-laden judgements of some conditions.

Remote work, understood here as a working environment different from the traditional office working space, is a phenomenon that has existed for many years. In the past, workers voluntarily opted, when they were allowed to, to work remotely rather than commuting to their traditional work environment. However, with the emergence of the global pandemic (corona virus-COVID-19), people were forced to work remotely to mitigate the spread of the virus. Consequently, researchers have identified some benefits and adverse effects of remote work, especially in the age of COVID-19, ranging from flexible time and environment to technostress and isolation. In this paper, using a phenomenological approach, specifically, the sub-Saharan African experiences, I contend that remote work in the age of advanced technologies has obscured the value of relationality due to the problem of isolation in sub-Saharan African workplaces. For sub-Saharan Africans, relationality is a prerequisite moral value to becoming a person. In addition, relationality contributes to meaningfulness in the workspace. Obscuring the value of relationality in the aforementioned locale leads to meaninglessness in the workspace. Furthermore, this paper contributes to the existing literature on meaningful work by critically showing the importance of the value of relationality as a key element that adds meaning to work in sub-Saharan Africa.

_ Memory and Forgetting in the Digital Age _ is a descriptive subtitle of the book, _Remember Me_ by the Italian theoretical philosopher Davide Sisto. The book’s central aim is to provide a philosophical argument on the consequences of digital networks such as social media and the internet in the way we remember and forget. Sisto does not subscribe to the well-known conception of memory and forgetting as opposites. He considers memory and forgetting to be the same thing; they have the same properties and are indistinguishable This is because remembering is forgetting, and forgetting is remembering. Memory does not pose the assumption that the past can be recalled totally but tries to fictionalise the past. The past begins to fade and deviate, and this deviation requires the act of forgetting. However, the proliferation of technologies and the internet has changed how we conceptualise forgetting and memory. The internet has provided the past with the opportunity to emancipate itself from the present and autonomously own itself and set its own trajectory. The past no longer sits in a space to be forgotten but now has the power to influence and shape the present.

Techno-colonialism, which I argue here to specifically mean the transfer of technology and its values and norms from one locale to another, has become a serious concern with the advancement of socially disruptive technologies1 of the Fourth Industrial Revolution (4IR), like artificial intelligence and robots. While the transfer of technology from one locale, especially economically advanced countries, to developing countries comes with economic benefits for both regions, it is important to understand that technologies are not value- neutral; they come with the values, cultures, and worldviews of their designers. However, despite the nonvalue-neutrality of the technologies of the 4IR, they are still relevant for subSaharan Africa’s development. Thus, using a phenomenological approach, especially the sub-Saharan African experiences of past histories of colonialism, I prescribe cautionary measures that sub-Saharan Africans ought to take in approaching the current industrial revolution and its technologies.

Sex robots, in a broad ethical sense, challenge our traditional social norms, sexual interactions, and how we visualise the human body. As a distinct sex stimulation technology, sex robots are ethically problematic because of the humanlike characteristics that these technologies embody. In this paper, I argue, on the one hand, that the design of sex robots objectifies the human body, from an African perspective, because of their humanoid appearance. This objectification of the human body contradicts the African conception of the human body as possessing inalienable dignity, vitality, and sacredness. On the other hand, I show how the designs of sex robots reinforce adverse stereotypical gender norms and standards of beauty. This paper is significant because it deploys sub-Saharan African values of sex and the human body to make a novel contribution to the ethical discourse of sex robots.