Exploring the ethical challenges of generative AI

Generative AI introduces two major ethical challenges that require thoughtful solutions.

First, these systems can perpetuate unfair biases if trained on data reflecting societal prejudices. Biased data ingrains prejudices into models, leading them to make discriminatory choices harmful to marginalized groups.

Second, the immense complexity of generative AI makes it very opaque. Even experts struggle to explain how these models make decisions internally. This lack of interpretability prevents properly auditing the systems for issues such as biases. It hinders public trust. In the following sub-section, we will learn more about these challenges.

Trust and accountability challenges of generative AI

One of the most pressing concerns regarding generative AI is the lack of transparency in its complex inner workings. Akin to a black box whose reasoning and decision-making processes remain obscured from view and human understanding...