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Mitigating algorithmic bias and discrimination in medical machine learning technologies : african philosophical resources to the rescue
Dissertation   Open access

Mitigating algorithmic bias and discrimination in medical machine learning technologies : african philosophical resources to the rescue

Edmund Terem Ugar
Doctor of Philosophy (PHD), University of Johannesburg
2025
Handle:
https://hdl.handle.net/10210/520465

Abstract

Should artificial intelligence/machine ethicists be concerned with the singularity/intelligent explosion (the view that superintelligent technologies will emerge in the future) and their potential harms, or should they channel their ethical ounce on mitigating the current ethical challenges of machine learning, such as algorithmic bias and discrimination? I argue that the discussion on the intelligent explosion/technological singularity/super intelligence is futuristic hypes that poses a distraction from the pressing and immediate problems that come with current designs of AI, especially machine learning technologies. This paper underscores that the discussion on AI and machine ethics has to move from the utopian futuristic hype of conceiving these machines as potential human-like agents with goals that are antithetical to human goals and their capacity to pursue these goals. AI ethics conversation should be on innovating new approaches to fully mitigate current ethical bumps of these technologies, such as bias and discrimination. As I will show in this paper, the current utopic hypes of these technologies is not feasible in the near future. Thus, it is belaboured for AI ethicist to channel all their ethical arsenals into ensuring the responsible design of utopic technologies. Rather, these ethical arsenals should be used innovatively to ensure responsible designs of current technologies in ...
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