AI (Artificial Intelligence), most specifically LLMs are technologies used to generate natural language content, allowing users to engage in conversations, ask questions, and receive answers. AI can help you brainstorm and generate new ideas as well as generic text to fill in gaps. It can also be used to edit drafts to ensure that the content is polished and free from errors.
A large language model (LLM) is a language model notable for its ability to achieve general-purpose language generation and understanding. LLMs acquire these abilities by learning statistical relationships from text documents during a computationally intensive self-supervised and semi-supervised training process. LLMs are artificial neural networks, the largest and most capable of which are built with a decoder-only transformer-based architecture. Some recent implementations are based on other architectures, such as recurrent neural network variants and Mamba (a state space model).
LLMs can be used for text generation, a form of generative AI, by taking an input text and repeatedly predicting the next token or word. Up to 2020, fine tuning was the only way a model could be adapted to be able to accomplish specific tasks. Larger sized models, such as GPT-3, however, can be prompt-engineered to achieve similar results. They are thought to acquire knowledge about syntax, semantics and "ontology" inherent in human language corpora, but also inaccuracies and biases present in the corpora.
Some notable LLMs are OpenAI's GPT series of models (e.g., GPT-3.5 and GPT-4, used in ChatGPT and Microsoft Copilot), Google's PaLM and Gemini (the latter of which is currently used in the chatbot of the same name), Meta's LLaMA family of open-source models, and Anthropic's Claude models.
Appropedia allows AI-generated content[edit | edit source]
Use of AI on Appropedia is allowed under the following conditions:
- There is not available content on Wikipedia, a different wiki, or any source shared under an open license.
- The content to be created will be used to support your original research.
Dangers of using AI[edit | edit source]
- The information generated by AI is not always be accurate or reliable, and you're still responsible for anything you publish on Appropedia.
- AI's may not always understand the context of a conversation or the nuances of language, so you should review and edit the content generated by AI to ensure that it is accurate, unbiased, and appropriate for the intended audience.
- Remember that AIs are programmed to generate text that makes sense, not necessarily text that is accurate or truthful, so they sometimes hallucinate. Also, they produce content based on the information they have been trained on, so depending on the type of prompt, the information may be outdated and biased.
- Large language models are built using existing materials, including content on Appropedia, sources are usually not attributed or mentioned. This undermines the work of individuals who do this type of work.
- There are inherent biases in AI that can render communities invisible, or perpetuate power imbalances.
Recommendations for using AI content[edit | edit source]
There's no requirement to cite the AIs you use to generate text (but you are encouraged to do so, and may be required to do so if you are editing Appropedia as part of your work, organization, or course), just as there's no requirement to cite the software you used for spellchecking and grammar corrections. However, it is advisable to cite the sources from where the AI generated the text, so users can verify it. Doing so may require research, or you may use AIs like Perplexity that already include the sources used.
We recommend AI for the following actions:
- Create summaries of texts (especially those authored by you or from open sources, including long pages on Appropedia).
- Sumamrize video transcripts to ensure that embedded content such as YouTube videos are accessible offline or more easily understood by others.
- Ask an AI to criticize or raise objections to an essay or piece of content.