Risks of Algorithmic Bias in Library Use of ChatGPT-like Tools and Regulatory Strategies
Although there is significant potential for libraries to use ChatGPT-like tools,the risks of algorithmic discrimination they introduce cannot be overlooked.Across the entire lifecycle—from data collection and training to service provision,user interaction,and result presentation—algorithmic bias can arise,often with new characteristics such as hidden and intersectional biases.The main causes of algorithmic discrimination include designer biases,user biases,and technological barriers.Designer bias can lead algorithmic models to inherit and amplify societal biases;user bias may exacerbate unequal service access due to variations in users'digital literacy;and technological barriers may prevent disadvantaged groups from accessing and utilizing intelligent technologies.The adverse effects of algorithmic discrimination are significant,potentially transforming information inequality into social status inequality,leading to unequal distribution of discourse power in knowledge production,and diminishing individual agency.To mitigate these risks,libraries should first analyze the sources of discrimination,then implement ethical algorithm interventions to counteract designer bias,enhance users'digital literacy to reduce user bias,and foster an inclusive digital environment to overcome technological service barriers,ensuring the responsible use of ChatGPT-like tools in libraries.
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