Generative AI models are powerful tools that utilize vast amounts of internet content to make predictions and generate output based on the input prompt. However, it is important to note that these predictions are not guaranteed to be accurate, despite sounding plausible. The models may also incorporate biases from the internet content they have been trained on, and it is often difficult to determine the extent of these biases. As a result, concerns have arisen regarding the potential role of generative AI in spreading misinformation.
One major drawback of generative AI models is their lack of awareness regarding the accuracy of the information they produce. In many cases, we have limited knowledge of the sources and algorithms used to process the data and generate content. This has led to instances where chatbots, for example, provide incorrect information or simply fabricate responses to fill in gaps. While the outputs of generative AI can be intriguing and entertaining, it is unwise to rely on them for reliable information or content, especially in the short term.
To address these concerns, some generative AI models, like Bing Chat or GPT-4, are attempting to bridge the gap by providing footnotes with sources. This allows users to not only know the origin of the response but also verify its accuracy. By including these sources, these models aim to enhance transparency and provide users with the means to evaluate the reliability of the generated content.