Generative artificial intelligence is a complicated set of technologies. While it's not necessary to have a deep knowledge of how these technologies work to use AI tools, it's helpful to have a basic understanding of some fundamental concepts.
- Generative AI refers to technology that can create new content, such as text, images, code, audio, or video.
- Put very simply, AI text generators work by predicting the next word in a sequence. They do not "understand" your questions in the way that another person would.
- AI text generators, such as ChatGPT, are trained on a large amount of text scraped from the Internet. This training is supplemented by annotation and feedback testing done by humans. AI image generators, such as Midjourney and DALL-E are trained in a similar way.
- With some exceptions, we don't have a lot of information about how the models that drive these tools were trained. That means that, in most cases, users have no way of knowing what information an AI tool has had access to.
- Many other applications are being developed that make use of generative AI technology. In fact, AI technology is already at work in many of the tools that you use.
Some limitations and causes for concern:
- Most AI tools capture and reuse a significant amount of user data. You should not share private information with ChatGPT or similar programs.
- All AI text generators can, and often do, produce plausible sounding but false information (known as "hallucinations"), and by their nature will produce output that is culturally and politically biased.
- There are a number of ethical and societal concerns about generative AI, from the way these tools were created, to the way they are being applied now and in the future.
Adapted from JISC. Generative AI - a Primer.