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Introduction to Generative AI

This library guide is a UIUC campus resource to read and reference for instructional, professional, and personal learning. Updates will occur on a semester basis. Last Updated: March 2024

Bias

Generative AI tools reflect the biases present in their training data, which may originate from various sources including: data inputters, anyone providing data or content (personal bias), the origin of the data (machine bias), and the exclusion of underrepresented or marginalized communities (selection bias). Moreover, users may inadvertently reinforce their existing beliefs by rephrasing prompts until they receive the answer they most desire (confirmation bias). Generative AI tools amplify and reinforce these biases, and it is crucial to remain critical of outputs/responses.

Otherwise, a growing sense of comfort, acceptance, and trust in what these tools provide can transform into depending on the machine to provide answers, realizations, and/or decisions (automation bias). Refer to academic resources to verify information and analyze the company’s data collection policies or procedures.

Digital Humanities Librarian Mary Ton provides an example of ChatGPT 3.5 bias in her Make my emails sound more masculine experiment conducted on June 1, 2023.