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Systemic Racism and Chatbot Limitations: The Need for Discerning Insights

Writer's picture: Aly CardinalliAly Cardinalli



ChatGPT, an advanced language model developed by OpenAI, is designed to generate human-like text in response to a given input. While this technology has proven incredibly useful in numerous applications, it is essential to recognize its limitations and potential biases. In this blog post, we will explore how ChatGPT's algorithms may inadvertently perpetuate systemic racism and the need for individuals to remain discerning when processing the information it provides.


ChatGPT filters its output to prevent providing what it considers "harmful information," which includes topics related to spells and witchcraft. Even historical and harmless instances like a "money bath" will not be answered, as the model aims to avoid any possible associations with negative consequences. However, it's worth noting that the model does not extend this censorship to religious content, such as providing quotes from the Psalms. This disparity highlights potential inconsistencies and biases in the model's content filtering system.





Furthermore, the dataset on which ChatGPT is trained may already contain biased information, contributing to systemic racism in the way it processes and delivers search results. For example, language models may be more likely to associate certain communities with negative stereotypes due to the skewed representation in their training data. This unintended consequence underscores the need for ongoing efforts to create more diverse and inclusive datasets for language model development.


In conclusion, while ChatGPT and other similar AI-based technologies offer numerous benefits, it's crucial to remain aware of their limitations and potential biases. As users, we must approach the information provided by these models with discernment, recognizing the systemic racism that can permeate their outputs. By staying vigilant and advocating for more inclusive AI training practices, we can help pave the way for a more equitable and fair digital landscape.

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