Please keep in mind that new technology like Generative AI (Gen AI) shouldn’t simply make your thinking or work easier, much less take the place of the uniquely singular abilities of human beings to grow cognitively, think creatively, or evaluate critically. If you use Gen AI to simply avoid work, you are doing it wrong. Instead, using Gen AI in the spirit of Douglas Engelbart’s “augmenting human intelligence” and Donna Haraway’s configuration of the cyborg point the way to beneficial heightening of human possibility instead of harmful erasure of the cognitive distinctions of humanity. If you use Gen AI, use it wisely and use it well. This post is the ninth in this series.
Science and technology are not neutral and bias free. While we might aim to elevate them above human biases, they are part of human culture and carry the weight of the best and worst of ourselves. Similarly, generative AI tools, trained on vast datasets that reflect the biases of society, can reproduce and amplify these distortions in their responses. This raises important questions about the role of AI in academic writing and the potential for perpetuating prejudice.
AI tools are not neutral; they reflect the biases present in their training data. For example, if a dataset contains stereotypical portrayals of certain groups, the AI will likely reproduce those stereotypes in its responses. This can result in biased or offensive content that undermines the credibility of a student’s work. Moreover, because AI-generated text is often polished and coherent, students may be less likely to question its content, thereby unintentionally perpetuating harmful ideas.
Consider a student writing a paper on gender roles in society. They prompt an AI tool to provide an analysis, and the AI responds with a well-written paragraph that reinforces outdated stereotypes. The student, assuming the AI is neutral, incorporates this analysis into their paper, potentially spreading biased ideas. This scenario highlights the danger of relying on AI without critically evaluating its responses.
It bears noting that while we influence the development of technology, it in turn influences human culture. In the case of AI tools, the technology is not only shaped by society but also actively reshapes it by amplifying existing biases. Students must recognize this dynamic and take steps to mitigate its impact on their work.
To address this problem, students should actively seek out diverse perspectives and critically evaluate AI-generated content. They can do this by comparing AI responses to credible sources and looking for inconsistencies or biases. Additionally, educators can play a crucial role by teaching students to recognize and challenge biases in AI-generated text. This might involve incorporating discussions of AI bias into the curriculum and providing tools for analyzing and addressing it.
While AI tools can be valuable writing assistants, they are not immune to the biases of the data they are trained on. The cyborg student must approach these tools with a critical eye, recognizing the potential for bias and taking steps to mitigate its impact. By doing so, they can produce work that is not only well-written but also equitable and inclusive.
