• Large Language Models (LLMs) predict what comes next in a series of words
• Uses human feedback to learn how to respond satisfactorily based on instructions
• Understands the intent behind a question and provides helpful answers
• Applies a wide range of knowledge to different domains, similar to how humans do

• Bias: Results may be biased since the tool is programmed to avoid harmful topics
• Inaccuracy: Focus is on answers that feel right to humans, does not guarantee accuracy
• Outdated: Knowledge may not be up to date, as ChatGPT was trained on data prior to 2021
• Dependency: Quality of content depends on the detail and clarity of instructions provided
• Identifiable: Algorithms such as Google’s search algorithm can detect AI-generated content
• Regulation: Industry bodies may insist on ethical AI practices such as watermarking in future

• Versatile: Ability to generate content in a variety of formats – poetry, screenplay, etc., expanding its applications
• Multilingual: Understands and responds to multiple languages, finding use in customer support, translation, and so on
• Personalized: Tailors the interaction based on available data, leading to a better user experience
• Fine-tuning: Capability to be trained for specific use cases in a particular domain and with subsets of data
• Intelligent: ChatGPT’s transformer architecture is a deep learning model that recognizes word associations in a complex sequence

Pros

• As a productivity tool, experts could leverage ChatGPT for basic research on topics, reviewing and structuring the content before publishing
• Keyword research is made easier, as the tool provides a list of related keywords and phrases, and suggestions on which are easier to rank for

Cons

• Google’s algorithm values E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) which may be difficult for AI to achieve
• Lower barriers to entry for content creators may reduce the quality of content online, and negatively impact search results over time