Training data
Generative Al models need to be powered by large data sets, which are typically acquired through collating and processing large amounts of publicly available data. For example, ChatGPT utilises training datasets which are based on scraping billions of words from WebText datasets. The fact that data is made publicly available does not mean it can be used without restriction in a lawful manner. If you were able to use proprietary data sets, or had comfort that the data sets were appropriately licensed, a lot of the headaches around the training data phase would fall away.
Issue: Whilst the collection of the training data is a developer activity, concerns around whether or not the training data has been lawfully collected is an issue for both developers and users. Likewise relying on publicly available data raises questions as to the accuracy and completeness of training data.