![]() This essay seeks to identify whether an approach, combining these two dominant academic fields of study may create a more successful solution in reducing AI bias. We need a combination of both approaches within a clear framework of action (Fig. On the other hand, it is the approach by data scientists and programmers that characterise AI biases as bugs implying that it is just a technical issue like security that needs to be fixed. ![]() Whilst useful in creating debate, these tend to present either no solutions at all or overly simplified single solutions. On one side, the theories are formed from a philosophical or sociological perspective, which study problems either existing or expected in the future. They have also been instrumental in devising novel solutions to such dilemmas, creating ethical frameworks intended to enhance the rapidly evolving technology-based solutions present in every corner of modern life.Įxisting literature analysing AI bias tend to originate from one of two, very separate, academic spheres. In recent years, researchers in this discipline have highlighted and created debate around potential issues surrounding AI such as regarding data privacy or discriminatory outcomes. ![]() Attempting to move understanding beyond the existing philosophical debates, this study bases itself within the emerging field of Applied Ethics. This essay explores the highly pertinent topic of bias within artificial intelligence (AI). ![]()
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