As artificial intelligence tools like ChatGPT become integrated into our daily routines, a legal expert raises a concern about their influence on our perspectives. Prof. Michal Shur-Ofry from the Hebrew University of Jerusalem notes that advanced AI systems often provide generic content, which may come with drawbacks.
Prof. Shur-Ofry points out that when everyone receives similar mainstream responses from AI, it could limit our exposure to diverse voices and narratives. This situation could gradually narrow the range of ideas we consider. The article discusses how large language models (LLMs) tend to favor popular localized content, even when various responses are possible, illustrating this with examples of notable 19th-century figures and popular television series.
The underlying reason for this trend lies in how these models learn, primarily from English datasets, which skews their outputs towards specific common narratives, while sidelining less prevalent cultures. As less common information is frequently excluded, the AI’s projection of reality becomes increasingly homogenous, leading to potential cultural homogenization, reduced social tolerance, and a diminished shared community history.
To counteract this, Prof. Shur-Ofry advocates for a new principle in AI governance: multiplicity, which encourages exposing users to diverse valid options rather than just popular responses. She emphasizes the importance of AI literacy, helping users understand LLMs and prompting critical analysis of the information provided. Her collaborative efforts aim to enhance the diversity of AI outputs, reinforcing that technology can reflect the richness of human experiences.
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