By James Maroney
State Sen., D-14
James Maroney
You hear so much about artificial intelligence on the news and elsewhere, but what is it?
The term AI is fairly generic and can refer to any form of computing that is attempting to replicate human thinking. The term was coined at a 1956 computer conference at Dartmouth, so it is now new. At its core, AI is a prediction machine.
Since AI is so prevalent, and to many still intimidating, I wanted to detail some common vocabulary surrounding AI. There are several important terms when discussing AI. Knowing them helps in grasping the underlying concept more effectively. Familiarity with key terms is fundamental to understanding AI.
Artificial intelligence involves computer programs that can complete cognitive tasks typically associated with human intelligence. For example, Google Maps is a form of AI that predicts the best way to drive to get from one location to another. The text completion in Google searches is an AI that is predicting what you want to type. ChatGPT is a chatbot that predicts what you want to hear based on the prompt that you entered.
Another term is an AI model. This is a computer program trained on a set of data to recognize patterns and perform specific tasks. An example of an AI model is GPT. It is a type of large language model developed that uses deep learning techniques to understand and generate human-like text based on the input it receives.
Other important terms include:
Biased data is data that is incomplete, does not accurately represent populations or includes preferential treatment for certain individuals or groups.
A conversational AI tool processes text requests and generates text responses, (like ChatGPT).
Deepfakes are AI-generated fake photos or videos of real people saying or doing things that they did not do.
Drift is the decline in an AI model’s accuracy in predictions due to changes over time that are not reflected in the training data.
Generative AI can generate new content, like text, images or other media. Some examples are ChatGPT and Gemini.
Hallucinations is the term for AI outputs that are not true.
The human-in-the-loop approach is a combination of machine and human intelligence to train, use, verify and refine AI models.
A large language model is an AI model that is trained on large amounts of text to identify patterns between words, concepts and phrases so that it can generate responses to prompts.
Machine learning is a subset of AI focused on developing computer programs that can analyze data to make decisions or predictions.
Natural language refers to the way people talk or write when communicating with each other.
A prompt is a text input that provides instructions to the AI model on how to generate output. Prompt engineering is the practice of developing effective prompts that elicit useful output from generative AI.
Responsible AI is the principle of developing and using AI ethically, with the intent of benefiting people and society while avoiding harm.
Finally, transparency is the idea that an AI tool should provide insight into how it works, why it made a particular output and what factors contributed to that output.
Understanding terms related to AI is crucial because it enables clear communication and a deeper comprehension of this complex field. As AI continues to shape our world, familiarity with its terminology empowers individuals to engage with the technology more effectively, whether in academic, professional or everyday contexts.