Over the past few years, there have been incredible advances in artificial intelligence (AI). AI has the potential to help us solve some of the world's biggest problems, but it can also be used to deceive and hurt people. The introduction of generative AI, in particular, has given the public tools to create an enormous array of content. Some of the content is helpful, but there is also quite a bit of factually incorrect, damaging, and just plain illegal content as well. This libguide can help you understand the impact of AI on journalism and amateur content, and you can learn how to spot deepfakes.
Algorithm -- A mathematical equation or procedure used for solving a problem.
Artificial Intelligence (AI) -- Technology that allows computers and machines to simulate human intelligence and problem-solving capabilities.
Deepfake -- Fabricated hyper-realistic digital media, including video, image, and audio content.
Deep Learning -- A subset of machine learning that uses multiple neural networks.
Generative AI -- An AI system that learns to generate more objects that look like the data used to train it.
Hallucination -- Incorrect or misleading results generated by AI. This occurs when the system has not been trained on the correct data, or when it has been trained on inaccurate or biased data.
Large Language Model (LLM) -- A deep learning algorithm that can recognize, summarize, translate, predict, and generate text and other forms of content based on knowledge gained from massive datasets.
Machine Learning -- A branch of AI that focuses on the using data and algorithms to enable AI to imitate the way that humans learn, gradually improving its accuracy.
Neural Network -- A machine learning model that makes decisions similar to how the human brain does. It uses nodes to mimic the way biological neurons work together to identify patterns and solve problems.
Terminology adapted from: Google, IBM, MIT, NVIDIA, Stanford, and TechTarget.