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Generative AI

This guide is a continuous process for Madison College librarians to understand, stay informed, and communicate relevant information related to the technology.

Limitations of Generative Artificial Intelligence

Limitations of ChatGPT

Lack of common sense: While ChatGPT can generate human-like responses and has access to a large amount of information, it does not possess human-level common sense — and the model also lacks the background knowledge we have. This means that ChatGPT may sometimes provide nonsensical or inaccurate responses to certain questions or situations.
Lack of emotional intelligence: While ChatGPT can generate responses that seem empathetic, it does not possess true emotional intelligence. It cannot detect subtle emotional cues or respond appropriately to complex emotional situations.
Limitations in understanding context: ChatGPT has difficulty understanding context, especially sarcasm and humor. While ChatGPT is proficient in language processing, it can struggle to grasp the subtle nuances of human communication. For example, if a user were to use sarcasm or humor in their message, ChatGPT may fail to pick up on the intended meaning and instead provide a response that is inappropriate or irrelevant.
Potentially biased responses: ChatGPT is trained on a large set of text data — and that data may contain biases or prejudices. This means the AI may sometimes generate responses that are unintentionally biased or discriminatory.
Limited knowledge: Although ChatGPT has access to a large amount of information, it is not able to access all of the knowledge that humans have. It may not be able to answer questions about very specific or niche topics, and it may not be aware of recent developments or changes in certain fields.
Accuracy problems or grammatical issues: ChatGPT's sensitivity to typos, grammatical errors, and misspellings is limited at the moment. The model may also produce responses that are technically correct but may not be entirely accurate in terms of context or relevance. This limitation can be particularly challenging when processing complex or specialized information, where accuracy and precision are crucial. You should always take steps to verify the information ChatGPT generates.
Need for fine-tuning: If you need to use ChatGPT for very specific use cases, you may need to fine-tune the model to get what you need. Fine-tuning involves training the model on a specific set of data to optimize its performance for a particular task or objective, and can be time-consuming and resource-intensive.
Computational costs and power: ChatGPT is a highly complex and sophisticated AI language model that requires substantial computational resources to operate efficiently — which means running the model can be expensive and may require access to specialized hardware and software systems. Additionally, running ChatGPT on low-end hardware or systems with limited computational power can result in slower processing times, reduced accuracy, and other performance issues. Organizations should carefully consider their computational resources and capabilities before using ChatGPT.

Source: Marr, Bernard. “The Top 10 Limitations of Chatgpt.” Forbes, Forbes Magazine, 5 Oct. 2023, www.forbes.com/sites/bernardmarr/2023/03/03/the-top-10-limitations-of-chatgpt/?sh=40da5d108f35.